June 29 | June 30 | July 1 | July 2

June 29, 2020

15:00 – 18:30 (CEST).
Workshop on Dependable and Secure Machine Learning

The DSN Workshop on Dependable and Secure Machine Learning (DSML) is an open forum for researchers, practitioners, and regulatory experts, to present and discuss innovative ideas and practical techniques and tools for producing dependable and secure machine learning (ML) systems. A major goal of the workshop is to draw the attention of the research community to the problem of establishing guarantees of reliability, security, safety, and robustness for systems that incorporate increasingly complex ML models, and to the challenge of determining whether such systems can comply with the requirements for safety-critical systems. A further goal is to build a research community at the intersection of machine learning and dependable and secure computing.

The program of the workshop is available here.

Workshop on Data-Centric Dependability and Security

Dependability and security are of the utmost importance for computing systems. Due to the scale and complexity of current systems, both aspects are a permanent and growing concern in industry and academia. On the one hand, the volume and diversity of functional and non-functional data, including open source information, along with increasingly dynamical operating environments, create additional obstacles to the dependability and security of systems. On the other hand, it creates an information rich environment that, leveraged by techniques from modern data science, machine and statistical learning, and visualization, will contribute to improve systems resilience in contexts of dynamic operating environments and unexpected operating conditions. As such, there is a strong demand for production-ready systems leveraging from data-centric solutions able to improve and, adaptively, maintain the dependability and security of computing systems.

The workshop on Data-Centric Dependability and Security (DCDS) aims at providing researchers with a forum to exchange and discuss scientific contributions and open challenges, both theoretical and practical, related to the use of data-centric approaches that promote the dependability and cybersecurity of computing systems. We want to foster joint work and knowledge exchange between the dependability and security communities, and researchers and practitioners from areas such as machine and statistical learning, and data science and visualization. The workshop provides a forum for discussing novel trends in data-centric processing technologies and the role of such technologies in the development of resilient systems. It aims to discuss novel approaches for processing and analysing data generated by the systems as well as information gathered from open sources, leveraging from data science, machine and statistical learning techniques, and visualization. The workshop shall contribute to identify new application areas as well as open and future research problems, for data-centric approaches to system dependability and security.

The program of the workshop can be checked here.

Workshop on High-performance computing platforms for dependable autonomous systems

A number of high-performance computing (HPC) commercial off-the-shelf (COTS) platforms offer the computation capabilities needed by autonomous systems in domains such as automotive, space, avionics, robotics and factory automation by means of multicores, GPUs and specialized accelerators. Unfortunately, the utilization of HPC platforms has been traditionally considered out of the reach for the safety-critical systems industry due to the difficulties or roadblocks these platforms bring to the certification process. This workshop focuses on the research towards the adoption of HPC hardware and software platforms in the context of safety- and security-critical applications. In particular, the scope of the workshop includes functional-safety and security requirements for HPC systems, including but not limited to non-functional aspects such as time predictability and energy consumption.

Topics of interest

  1. High-performance critical real-time systems
  2. Dependable systems and safety mechanisms
  3. Hardware and Software security in safety-critical systems


Carles Hernàndez (Universitat Politènica de València)
Jaume Abella (Barcelona Supercomputing Center)
Mikel Azkarate-askatsua (Ikerlan)
Roman Obermaisser​ (University of Siegen)


The program of the workshop can be checked here.

Workshop on Safety and Security of Intelligent Vehicles

Over the last years, aerial and ground vehicles as well as mobile robot systems have been receiving an increased number of electronic components, connected through wireless networks and running embedded software. As processing power increases and software becomes more sophisticated, these vehicles gain the ability to perform complex operations, becoming more autonomous, safe, efficient, adaptable, comfortable and usable. These are known as Intelligent Vehicles.

This will be the sixth edition of the workshop, aiming at continuing the success of previous editions. The vast range of open challenges to achieve Safety and Security in Intelligent Vehicles (with or without connection with the Internet) is a fundamental reason that justifies the numerous research initiatives and wide discussion on these matters, which we are currently observing everywhere. Therefore, the workshop will keep its focus on exploring the challenges and interdependencies between security, real-time, safety and certification, which emerge when introducing networked, autonomous and cooperative functionalities.

Website: https://sites.google.com/view/ssiv


15:05-15:50 (CEST). SSIV #1: AI and adaptive systems
chaired by Michaël Lauer
  • AI and Reliability Trends in Safety Critical Autonomous Systems on Ground and Air
    Jyotika Athavale (Intel), Michael Paulitsch (Intel), Andrea Baldovin (Intel), Ralf Graefe (Intel), and Rafael Rosales (Intel)

  • Reward Tuning for self-adaptive Policy in MDP based Distributed Decision-Making to ensure a Secure Mission Planning
    Mohand Hamadouche (Lab-STICC, CNRS), Catherine Dezan (Lab-STICC, CNRS), and Kalinka Regina Lucas Jauqie Castelo Branco (Universidade de Sao Paulo)
15:55-16:40 (CEST). SSIV #2: Dependability and security analysis
chaired by Joao Cunha
  • The Quantitative Risk Norm - A Proposed Tailoring of HARA for ADS
    Fredrik Warg (RISE Research Institutes of Sweden), Rolf Johansson (Autonomous Intelligent Driving), Martin Sanfridson (Volvo Technology AB), Mattias Brännström (Zenuity AB), Magnus Gyllenhammar (Zenuity AB), Martin Skoglund (RISE Research Institutes of Sweden) and Anders Thorsén (RISE Research Institutes of Sweden)

  • Analysis of Cybersecurity Mechanisms with respect to Dependability and Security Attributes
    Behrooz Sangchoolie (Dependable Transport Systems, RISE Research Institutes of Sweden), Peter Folkesson (Dependable Transport Systems, RISE Research Institutes of Sweden), Pierre Kleberger (Dependable Transport Systems, RISE Research Institutes of Sweden) and Jonny Vinter (Dependable Transport Systems, RISE Research Institutes of Sweden)

  • Exploring Fault Parameter Space using Reinforcement Learning-based Fault Injection
    Mehrdad Moradi (University of Antwerp and Flanders Make vzw), Bentley James Oakes (University of Antwerp and Flanders Make vzw), Mustafa Saraoglu (Technische Universitat Dresden), Andrey Morozov (Technische Universitat Dresden), Klaus Janschek (Technische Universitat Dresden) and Joachim Denil (University of Antwerp and Flanders Make vzw)

16:45-17:30 (CEST). SSIV #3: Architecture and deployment
chaired by Kalinka Branco
  • Flexible Deployment and Enforcement of Flight and Privacy Restrictions for Drone Applications
    Nasos Grigoropoulos (University of Thessaly) and Spyros Lalis (University of Thessaly)

  • Conceptual Design of Human-Drone Communication in Collaborative Environments
    Hans Dermot Doran (Institute of Embedded Systems, ZHAW), Monika Reif (Institute of Applied Mathematics and Physics, ZHAW), Marco Oehler (Zurich University of Applied Sciences), Curdin Stöhr (Zurich University of Applied Sciences), and Pierluigi Capone (Centre for Aviation, ZHAW).
  • A hierarchical fault tolerant architecture for an autonomous robot
    Favier Anthony (LAAS-CNRS, INPT ENSEEIHT - University of Toulouse), Messioux Antonin (LAAS-CNRS, INPT ENSEEIHT, University of Toulouse), Jérémie Guiochet (LAAS-CNRS,UPS, INPT, University of Toulouse), Jean-Charles Fabre (LAAS-CNRS, UPS, INPT, University of Toulouse) and Charles Lesire (ONERA/DTIS, University of Toulouse).

17:40-18:30 (CEST). SSIV #4: Panel and closing remarks

"Future Challenges in Safety and Security of Intelligent Vehicle"

Chair/Moderator :

  • Mario Trapp (Fraunhofer IKS, Germany)


  • Sibin Mohan (University of Illinois, USA)
  • Miriam Gruber (BMW, Germany)
  • Behrooz Sangchoolie (RISE, Sweden)


15:00 – 18:00 (CEST).
Tutorial #1:
Cross-Layer Soft-Error Resilience Analysis of Computing Systems

In a world with computation at the epicenter of every activity, computing systems must be highly resilient to errors even if miniaturization makes the underlying hardware unreliable. Techniques able to guarantee high reliability are associated to high costs. Early resilience analysis has the potential to support informed design decisions to maximize system-level reliability while minimizing the associated costs. This tutorial focuses on early cross-layer (hardware and software) resilience analysis considering the full computing continuum (from IoT/CPS to HPC applications) with emphasis on soft errors. The tutorial will guide attendees from the definition of the problem down to the proper modeling and design exploration strategies considering the full system stack (i.e., from circuit to software).

  1. Provide a deep understanding of the cross-layer impact of hardware faults on the full system
    stack, taking into account all derating factors from technology (silicon) to software.
  2. Describe and analyze methodologies and tools for the evaluation of the resilience of each
    system layer (i.e., circuit, microarchitecture, and software).
  3. Illustrate how specific approaches for resilience analysis working at different layers of the
    system stack can be integrated to provide full system level analysis.
  4. Showcase the accuracy, strengths and weaknesses of the presented techniques.

Students, researchers and practitioners working on computing systems hardware and software design, with concerns about the impact of hardware faults on the full system level operation.

It is expected a basic understanding of computing systems hardware and software such as: logic design, computer architecture and microarchitecture, operating systems and programming. Some basic background on hardware defect mechanisms, fault and error modeling.


The tutorial is organized in an incremental manner. It starts with an introduction to reliability and cross-layer techniques followed by the main techniques applied at each abstraction level (e.g., circuits, architecture and software). The last part is focused on the most advanced concepts of stochastic cross-layer modelling, analysis and optimization. The agenda will be:

  • Introduction – Basic Concepts, Terminology (30 minutes)
  • Technology level resilience assessments (30 minutes)
  • Microarchitecture level resilience assessments (30 minutes)
  • Software level resilience assessments (30 minutes)
  • Stochastic based approach for System level resilience assessments (30 minutes)

  • Alberto Bosio, École Centrale de Lyon, France
  • Stefano Di Carlo, Politecnico di Torino, Italy
  • Alessandro Savino, Politecnico di Torino, Italy
  • Dimitris Gizopoulos, University of Athens, Greece
  • Ramón Canal, Universitat Politècnica de Catalunya and Barcelona Supercomputing Center, Spain

Tutorial #2:
Into the Unknown: Unsupervised ML Algorithms for Anomaly-Based Intrusion Detection

One of the open challenges of past and recent systems is to identify errors before they escalate into failures. To such extent, most of the Error Detectors or enterprise Intrusion Detection Systems adopt signature-based detection algorithms, which consist of looking for predefined patterns (or "signatures") in the monitored data in order to detect an error or an ongoing attack. Data is usually seen as a flow of data points, which represent observations of the values of the indicators at a given time. Signature-based approaches usually score high detection capabilities and low false positive rates when experimenting known errors or attacks, but they cannot effectively adapt their behaviour when systems evolve or when their configuration is modified. As an additional consequence, signature-based approaches are not meant to detect zero day attacks, which are novel attacks that cannot be matched to any known signature. Moreover, when a zero-day attack that exploit newly added or undiscovered system vulnerabilities is identified, its signature needs to be derived and added as a new rule to the IDS.

To deal with unknowns, research moved to techniques suited to detect unseen, novel attacks. Anomaly detectors are based on the assumption that an attack generates observable deviations from an expected – normal – behaviour. Briefly, they aim at finding patterns in data that do not conform to the expected behaviour of a system: such patterns are known as anomalies. Once an expected behaviour is defined, anomaly detectors target deviations from such expectations, protecting against known attacks, zero-day attacks and emerging threats. To such extent, most of the anomaly detection algorithms are unsupervised, suiting the detection, among others, of unknown errors or zero-day attacks, without requiring labels in training data 

The primary learning objectives of the tutorial are to demonstrate the capability of unsupervised learning algorithm to detect cyber-attacks and in particular zero-day attacks, and to instruct the attendees on the process to perform a well-crafted evaluation campaign.

In fact, after showing the current threat landscape as expanded by technical reports of agencies as ENISA, we will introduce anomaly detection, which is acknowledged as the most reliable answer to the detection of unknown errors or attacks. The participants will understand and use unsupervised algorithms that are particularly suited for anomaly detection, the main families and the differences in the way they decide if a data point is anomalous or normal. Participants will be involved in an hands-on session by using the RELOAD tool, which allows executing unsupervised anomaly detection algorithms and observing metric scores they provide on different datasets. This hands-on session, which can be conducted individually or in groups, will originate the final session which will constitute the final takeover of the tutorial, based both on participants activities and organizers’ experience in the domain.

The RELOAD tutorial targets anyone who is interested in the application of unsupervised ML algorithms for intrusion detection, with PhD students or young researchers as primary target audience. Consequently, we expect a remarkable amount of conference attendees to be interested in the topics of this tutorial, which targets beginners, with some content for intermediate. In fact, the tool to be used in the hand-on session will allow PhD students, researchers and practitioners who are starting to explore the discipline to get their first quantitative estimation of attack detection capabilities of algorithms, hiding implementation details which may be difficult to control at a first stage.

The tutorial will be composed by the following blocks.

  • B1. Digression on the Current Threat Landscape (10% of tutorial time). Starting from public reports e.g., ENISA, we will describe the current state of cyber-attacks.
  • B2. Anomaly-Based Intrusion Detection (15% of tutorial time). This part highlights some key terms and components that will be used in the rest of the tutorial, alongside with its role in detecting intrusions.
  • B3. Unsupervised Algorithms and their Characteristics (10% of tutorial time). We will introduce some of the most common algorithms to be used for unsupervised anomaly detection.
  • B4. Presentation of the RELOAD Tool (15% of tutorial time): This part will let the audience understand what the RELOAD tool offers, and how to use the RELOAD tool for executing unsupervised algorithms.
  • B5. Hands-On Session (40% of tutorial time): the attendees can use the tool to perform intrusion detection on public attack datasets that are previously downloaded by the organizers and shared with the slides.
  • B6. Wrap-up and Final Discussion (10% of tutorial time): Results obtained during hand-on session will be discussed together with the audience, originating final discussions. We will prepare spare material for enriching the discussion, expanding on already existing studies.
  • Tommaso Zoppi, University of Florence, Italy
  • Andrea Ceccarelli, University of Florence, Italy
  • Andrea Bondavalli, University of Florence, Italy

Tutorial #3:
The InterPlanetary File System and the filecoin network

The InterPlanetary File System (IPFS) is a peer-to-peer content-addressable distributed file
system that seeks to connect all computing devices with the same system of files. It is an
open-source community-driven project, with reference implementations in Go and Javascript,
and a global community of millions of users.

IPFS resembles past and present efforts to build and deploy Information-Centric Networking
approaches to content storage, resolution, distribution and delivery. IPFS and libp2p , which is
the modular network stack of IPFS, are based on name-resolution based routing. The resolution
system is based on Kademlia DHT and content is addressed by flat hash-based names. IPFS
sees significant real-world usage, with over 250,000 daily active network nodes, millions of end
users and wide adoption by several other projects in the Decentralised Web space, but not only.
An adjacent project to IPFS, which was also masterminded and is also being developed within
Protocol Labs (the umbrella company of IPFS and libp2p) is filecoin . Filecoin is a cryptocurrency
that supports a decentralised storage and delivery network. Storage and retrieval miners are
rewarded according to their contribution to the network and the mechanics of filecoin secure the
network against malicious activity

The main objective of this tutorial is to let researchers, developers, and users understand IPFS
and the capabilities it provides.

More specifically, participants will:

  • Understand how IPFS brings content addressing as a core primitive for data distribution
  • Learn how to use CIDs (content identifiers) to find content and interpret what the content
    is programatically
  • Learn how to create custom data structures using IPFS and its underlying data format,
    IPLD (InterPlanetary Linked Data)
  • Understand how libp2p bring process addressing as a core primitive for P2P and
    runtime-independent applications

The attendees do not need to have prior knowledge of IPFS, libp2p or filecoin and basic
knowledge and understanding of core networking and network security principles will be
adequate in order to follow along.

  • Understanding how IPFS deals with files (60 mins)
  • Solving distributed networking problems with libp2p (60 mins)
  • The lifecycle of data in IPFS and filecoin (40 mins)
  • Developing Apps with the IPFS API (20 mins)

  • David Dias, Peer-2-Peer Software Engineer at Protocol Labs, (Palo Alto, CA and Lisbon,
  • Dr. Ioannis Psaras, EPSRC Fellow and University Lecturer (Assistant Professor) at
    University College London and a Research Scientist at Protocol Labs.


15:00-18:00 (CEST).
     Doctoral Forum
Doctoral Forum
15:00-15:15 (CEST). Welcome
by Sara Bouchenak
15:15-16:00 (CEST). Keynote: The Hard Path to Excellence or…why excellence is about details
Paulo Verissimo, University of Luxembourg
chaired by Saman Zonouz

Top-level research is a highly competitive environment: funding; recruiting; publishing; impact … If you move in the first division, academia is like a premier league, and top researchers are high-level competition athletes. Is that too stressing? Where is the fun? Depends on the perspective. There is no unique recipe, but I’ll share my own experience and hope to show that it can be a unique life, if you do the right things.

If you manage the balance between freedom, self-responsibility, and perseverance, chances are you will go far, and have moments you'll never forget. How far? Well, if you are aiming for the gold, the nice secret of this talk is that excellence … is about details.

Paulo Esteves-Veríssimo is a professor and FNR PEARL Chair at the University of Luxembourg FSTM and SnT, and Head of the CritiX lab (https://wwwen.uni.lu/snt/research/critix). He is adjunct Professor of the ECE Dept., Carnegie Mellon University. Previously, he has been a professor of the Univ. of Lisbon (PT). He is the representative of UNILU-SnT in ECSO, the European Cyber Security Organisation, and member of its Scientific & Technical Committee (STC). He was Chair of the IFIP WG 10.4 on Dependable Computing and Fault-Tolerance and vice-Chair of the Steering Committee of the IEEE/IFIP DSN conference.

He is Fellow of the IEEE and Fellow of the ACM, and associate editor of IEEE Trans. on Emerging Topics in Computing (TETC). He is currently interested in architectures, middleware and algorithms for resilient modular and distributed computing, in areas like: SDN-based infrastructures; autonomous vehicles from earth to space; digital health and genomics; or blockchain and cryptocurrencies. He is author or co-author of over 200 peer-refereed int’l publications and
co-author of 5 books. Check his pubs on GSC.

16:15-17:00 (CEST). Session 1
chaired by Isabelly Rocha
  • Safeguarding Data Consistency at the Edge
    Claudio Correia (Universidade de Lisboa, Portugal)

  • Depending on HTTP/2 for Privacy? Good Luck!
    Gargi Mitra (IIT Madras, India)

  • Towards Practical Privacy-Preserving Collaborative Machine Learning at a Scale
    Rania Talbi (INSA-Lyon, France)

17:15-18:15 (CEST). Session 2
chaired by Amy Babay
  • What Exactly Determines the Type?Inferring Types with Context
    Ligeng Che (Nanjing University, China)

  • Impact of geo-distribution and mining pools on blockchains: a study of Ethereum
    Paulo Mendes da Silva, INESC-ID & IST. U. Lisboa, Portugal

  • CanvasMirror: Secure Integration of Third-Party Library in WebVR Environment
    Jiyeon Lee, KAIST, Korea

  • A Framework for Risk Assessment in Augmented Reality-equipped Socio-technical Systems
    Soheila Sheikh Bahaei, Malardalen University, Sweden


June 29 |June 30 | July 1 | July 2

June 30, 2020

15:00 – 15:15 (CEST).
      Welcome / Opening session
Welcome / Opening session
  • Opening by Vice-rector for Research, Innovation and Transfer, UPV.
  • Welcome from Honorary & General Conference Chairs
  • Message from PC Chairs


15:15 – 15:55 (CEST).
      Keynote #1
Keynote #1: Trustworthy AI
Jeannette M. Wing, , Avenessians Director of the Data Science Institute and Professor of Computer Science Columbia University, New York (USA)
June 30 @ 15:15 - 15:55 (CEST)

Recent years have seen an astounding growth in deployment of AI systems in critical domains such as autonomous vehicles, criminal justice, healthcare, hiring, housing, human resource management, law enforcement, and public safety, where decisions taken by AI agents directly impact human lives. Consequently, there is an increasing concern if these decisions can be trusted to be correct, reliable, fair, and safe, especially under adversarial attacks. How then can we deliver on the promise of the benefits of AI but address these scenarios that have life-critical consequences for people and society? In short, how can we achieve trustworthy AI?
Under the umbrella of trustworthy computing, there is a long-established framework employing formal methods and verification techniques for ensuring trust properties like reliability, security, and privacy of traditional software and hardware systems. Just as for trustworthy computing, formal verification could be an effective approach for building trust in AI-based systems. However, the set of properties needs to be extended beyond reliability, security, and privacy to include fairness, robustness, probabilistic accuracy under uncertainty, and other properties yet to be identified and defined. Further, there is a need for new property specifications and verification techniques to handle new kinds of artifacts, e.g., data distributions, probabilistic programs, and machine learning based models that may learn and adapt automatically over time. This talk will pose a new research agenda, from a formal methods perspective, for us to increase trust in AI systems.

Jeannette M. Wing is Avanessians Director of the Data Science Institute and  Professor of Computer Science at Columbia University. From 2013 to 2017, she was a Corporate Vice President of Microsoft Research. She is Adjunct Professor of Computer Science at Carnegie Mellon where she twice served as the Head of the Computer Science Department and had been on the faculty since 1985. From 2007-2010 she was the Assistant Director of the Computer and Information Science and Engineering Directorate at the National Science Foundation. She received her S.B., S.M., and Ph.D. degrees in Computer Science, all from the Massachusetts Institute of Technology.

Professor Wing's general research interests are in the areas of trustworthy computing, specification and verification, concurrent and distributed systems, programming languages, and software engineering. Her current interests are in the foundations of security and privacy, with a new focus on trustworthy AI. She was or is on the editorial board of twelve journals, including the Journal of the ACM and Communications of the ACM.

Professor Wing is known for her work on linearizability, behavioral subtyping, attack graphs, and privacy-compliance checkers. Her 2006 seminal essay, titled "Computational Thinking" is credited with helping to establish the centrality of computer science to problem-solving in fields where previously it had not been embraced. She is currently a member of: the National Library of Medicine Blue Ribbon Panel; the Science, Engineering, and Technology Advisory Committee for the American Academy for Arts and Sciences; the Board of Trustees for the Institute of Pure and Applied Mathematics; the Advisory Board for the Association for Women in Mathematics; and the Alibaba DAMO Technical Advisory Board. She has been chair and/or a member of many other academic, government, and industry advisory boards. She received the CRA Distinguished Service Award in 2011 and the ACM Distinguished Service Award in 2014. She is a Fellow of the American Academy of Arts and Sciences, American Association for the Advancement of Science, the Association for Computing Machinery (ACM), and the Institute of Electrical and Electronic Engineers (IEEE).


16:00 – 16:45 (CEST).
      Presentation of best paper candidates
Best Paper Candidates Session
Chaired by Karthik Pattabiraman, UBC
  • KShot: Live Kernel Patching with SMM and SGX
    Lei Zhou Southern University of Science and Technology, Fengwei Zhang (Southern University of Science and Technology), Jinghui Liao (Wayne State University), Zhenyu Ning (Southern University of Science and Technology and Wayne State University, Jidong Xiao (Boise State University), Kevin Leach (University of Michigan), Westley Weimer (University of Michigan), Guojun Wang (Guangzhou University)

  • CDN Backfired: Amplification Attacks Based on HTTP Range Requests
    Weizhong Li (Tsinghua University), Kaiwen Shen (Tsinghua University), Run Guo (Tsinghua University), Baojun Liu (Tsinghua University), Jia Zhang (Tsinghua University), Haixin Duan (Tsinghua University), Shuang Hao (University of Texas at Dallas), Xiarun Chen (Peking University), Yao Wang (Beijing Information Science & Technology University)

  • Online Payments by Merely Broadcasting Messages
    Daniel Collins (EPFL), Rachid Guerraoui (EPFL), Jovan Komatovic (EPFL), Petr Kuznetsov (Telecom ParisTech), Matteo Monti (EPFL), Matej Pavlovic (EPFL), Yvonne-Anne Pignolet (DFINITY), Dragos-Adrian Seredinschi (Interchain Foundation – Lausanne), Andrei Tonkikh (NRU HSE), Athanasios Xygkis (EPFL)


16:55 – 17:10 (CEST).
      Carter Award Presentation
Winner: Bo Fang
University of British Columbia, Canada

The winner of the 2020 William C. Carter PhD Dissertation Award in Dependability is:

Bo Fang, University of British Columbia, CA

PhD Dissertation title: “Approaches for Building Error Resilient Applications”
Defense date: February 11th, 2020

Thesis Advisor:
Karthik Pattabiraman (University of British Columbia, CA)

Dissertation Summary: “Bo Fang’s thesis addresses the problem of transient hardware faults in high performance computing (HPC) systems. Starting form the idea that most transient hardware faults have no significant impact at the software layer, Bo’s thesis proposes an error propagation model and a crash model to identify which faults really matter, particularly the ones that may cause silent data corruption and crashes, in order to selectively trigger recovery actions. Subsequently, Bo proposes the innovative idea of applying the roll-forward recovery scheme in standard checkpoint/restart system to allow trading confidence in results for efficiency in both performance and energy saving. Bo’s work has already been making an impact on the design and implementation of HPC systems at two national labs in the US, namely Pacific Northwestern National Labs (PNNL), and Los Alamos National Labs (LANL). ”


17:15 – 18:30 (CEST).
      Research Track #1 || Research Track #2 || Industry Track #1 
Research Track #1. Software Dependability
Chaired by Saurabh Bagchi, Purdue Univ.
  • Comprehensive Java Metadata Tracking for Attack Detection and Repair
    Jeff Perkins (MIT/CSAIL), Jordan Eikenberry (MIT/CSAIL), Alessandro Coglio (Kestrel Institute), Martin Rinard (MIT/CSAIL)

  • Trace Sanitizer - Eliminating the Effects of Non-determinism on Error Propagation Analysis
    Habib Saissi (Technische Universität Darmstadt), Stefan Winter (Technische Universität Darmstadt), Oliver Schwahn (Technische Universität Darmstadt), Karthik Pattabiraman (University of British Columbia), Neeraj Suri (Lancaster University)

  • JSKernel: Fortifying JavaScript against Web Concurrency Attacks via a Kernel-like Structure
    Zhanhao Chen (Palo Alto Networks), Yinzhi Cao (Johns Hopkins University)

  • Scarecrow: Deactivating Evasive Malware via Its Own Evasive Logic
    Jialong Zhang (ByteDance), Zhongshu Gu (IBM Research), Jiyong Jang (IBM Research), Dhilung Kirat (IBM Research), Marc Ph. Stoecklin (IBM Research), Xiaokui Shu (IBM Research), Heqing Huang (ByteDance)

  • CATI: Context-Assisted Type Inference from Stripped Binaries
    Ligeng Chen (Nanjing University), Zhongling He (Nanjing University), Bing Mao (Nanjing University)

Research Track #2. Machine Learning Resilience
Chaired by Atul Prakash, Univ. of Michigan
    • PolygraphMR: Enhancing the Reliability and Dependability of CNNs
      Salar Latifi (University of Michigan), Babak Zamirai (University of Michigan), Scott Mahlke (University of Michigan)

    • ML-driven Malware for Targeting AV Safety Saurabh Jha (UIUC)
      Shengkun Cui (UIUC), Subho Banerjee (UIUC), James Cyriac (UIUC), Timothy Tsai (NVIDIA), Zbigniew Kalbarczyk (UIUC), Ravi Iyer (UIUC)

  • Leaky DNN: Stealing Deep-learning Model Secret with GPU Context-switching Side-channel
    Junyi Wei (Fudan University), Yicheng Zhang (University of California, Irvine), Zhe Zhou (Fudan University), Zhou Li (University of California, Irvine), Mohammad Abdullah Al Faruque (University of California, Irvine)

  • An Experimental Study of Reduced-Voltage Operation in Modern FPGAs for Neural Network Acceleration
    Behzad Salami (Barcelona Supercomputing Center (BSC)), Baturay Onural (TOBB UNIVERSITY OF ECONOMICS AND TECHNOLOGY), Ismail Emir Yuksel (TOBB UNIVERSITY OF ECONOMICS AND TECHNOLOGY), FAHRETTIN KOC (TOBB UNIVERSITY OF ECONOMICS AND TECHNOLOGY), Oguz Ergin (TOBB UNIVERSITY OF ECONOMICS AND TECHNOLOGY), Adrian Cristal (Barcelona Supercomputing Center (BSC), Osman Unsal (Barcelona Supercomputing Center (BSC)), Hamid Sarbazi-Azad (Sharif University of Technology, IPM), Onur Mutlu (ETH Zurich)

  • (Practice report): Quantifying DNN Model Robustness to the Real-World Threats Zhenyu Zhong (Baidu Research Institute)
    Zhisheng Hu (Baidu Research Institute), Xiaowei Chen (Baidu Research Institute)

Industry Track #1. Cyber-Physical Systems and Autonomous Systems
Chaired by Harigovind V. Ramasamy, Amazon
  • Robustness Inside Out Testing
    Deborah Katz (School of Computer Science, Carnegie Mellon University), Milda Zizyte (Department of Electrical and Computer Engineering, Carnegie Mellon University), Casidhe Hutchison (National Robotics Engineering Center, Carnegie Mellon University), David Guttendorf (National Robotics Engineering Center, Carnegie Mellon University), Patrick Lanigan (National Robotics Engineering Center, Carnegie Mellon University), Eric Sample (National Robotics Engineering Center, Carnegie Mellon University), Philip Koopman (Department of Electrical and Computer Engineering, Carnegie Mellon University), Michael Wagner (Edge Case Research), Claire Le Goues (School of Computer Science, Carnegie Mellon University)

  • Towards Host Intrusion Detection For Embedded Industrial Systems
    Marine Kadar (SYSGO GmbH), Sergey Tverdyshev (SYSGO GmbH), Gerhard Fohler (TU Kaiserslautern)

  • The Monitor as Key Architecture Element for Safe Self-Driving Cars
    Ayhan Mehmed (TTTech Auto AG), Moritz Antlanger (TTTech Auto AG), Wilfried Steiner ((TTTech Computertechnik AG)


June 29 | June 30 | July 1 | July 2


July 1, 2020

15:00 – 15:40 (CEST).
      Keynote #2
Keynote #2: The Journey to Libra Blockchain Core and Beyond
Dahlia Malkhi, Research Lead at Calibra (USA)
July 1 @ 15:00 - 15:40 (CEST)

At the core of cryptoeconomic systems like Libra is a mechanisms for 'agreeing' on a history of payment transactions. The journey to practical and robust solutions is accelerated by the drive to great inclusive financial services. This talk sheds light onto the efforts that led to the design of Libra's blockchain core and provides a glimpse on next steps.

Dahlia Malkhi is an applied and foundational researcher in broad aspects of distributed systems technology. Currently, she is a research lead at Calibra, where she is working on advancing the Libra technology. She is a co-inventor of HotStuff; co-founder and technical lead of VMware blockchain; co-inventor of Flexible Paxos, the technology behind Log Device; creator and tech lead of CorfuDB, a database-less database driving VMware’s NSX-T distributed control plane; and co-inventor of FairPlay project.

Dahlia is an ACM Fellow, 2011. She joined Calibra in June 2019 as a research lead. In 2014, after the closing of the Microsoft Research Silicon Valley lab, she co-founded VMware Research and became a Principal Researcher at VMware until June 2019. From 2004-2014, she was a principal researcher at Microsoft Research, Silicon Valley. From 1999-2007, she was a tenured associate professor at the Hebrew University of Jerusalem, and from 1995-1999, a senior researcher at AT&T Labs, NJ.


15:45 – 16:45 (CEST).
      Research Track #3 || Research Track #4 || Industry Track #2 || Fast Abstracts #1
Research Track #3. Systems Dependability
Chaired by Yair Amir, Johns Hopkins Univ.
  • The Mystery of the Failing Jobs: Insights from Operational Data from Two University-Wide Computing Systems
    Rakesh Kumar (Microsoft), Saurabh Jha (University of Illinois at Urbana-Champaign), Ashraf Mahgoub (Purdue University), Rajesh Kalyanam (Purdue University), Stephen L Harrell (Purdue University), Xiaohui Carol Song (Purdue University), Zbigniew Kalbarczyk (University of Illinois at Urbana-Champaign), William T Kramer (University of Illinois at Urbana-Champaign), Ravishankar K. Iye (University of Illinois at Urbana-Champaign), Saurabh Bagchi (Purdue University)

  • Reliable, Efficient Recovery for Complex Services with Replicated Subsystems
    Edward Tremel (Cornell University), Sagar Jha (Cornell University), Weijia Song (Cornell University), David Chu (Cornell University), Ken Birman (Cornell University)

  • HAMS: High Availability for Distributed Machine Learning Service Graphs
    Shixiong Zhao (University of Hong Kong), Xusheng Chen (University of Hong Kong), Cheng Wang (University of Hong Kong), Fanxin Li (University of Hong Kong), Ji Qi (University of Hong Kong), Heming Cui (University of Hong Kong), Cheng Li (University of Science and Technology of China)

  • Fine-Grained Fault Tolerance For Resilient Virtual Machine Monitors
    Djob Mvondo (Université Grenoble Alpes), Alain Tchana (ENS Lyon), Renaud Lachaize (Université Grenoble Alpes), Daniel Hagimont (Université de Toulouse), Noel De Palma (Université Grenoble Alpes)

Research Track #4. Blockchain
Chaired by Katinka Wolter, Frei University, Berlin
  • Data-Driven Model-Based Analysis of the Ethereum Verifier's Dilemma
    Maher Alharby (Newcastle University), Roben Lunardi (PUCRS), Amjad Aldweesh (Newcastle University), Aad van Moorsel (Newcastle University)

  • SMACS: Smart Contract Access Control Service
    Bowen Liu (Singapore University of Technology and Design), Siwei Sun (Chinese Academy of Sciences), Pawel Szalachowski (Singapore University of Technology and Design)

  • Smart Contracts on the Move
    Enrique Fynn (Università della Svizzera Italiana), Alysson Bessani (FCUL, University of Lisboa), Fernando Pedone (Università della Svizzera Italiana)

  • (practice report): Impact of Geo-distribution and Mining Pools on Blockchains: A Study of Ethereum
    Paulo Silva (University of Lisbon), David Vavřička (University of Lisbon), João Barreto (University of Lisbon), Miguel Matos (University of Lisbon)

Industry Track #2. ML for Dependable and Secure Systems
Chaired by Wilfried Steiner, TTTech
  • Predicting Remediations for Hardware Failures in Large-Scale Datacenters
    Fred Lin (Facebook Inc.), Antonio Davoli (Facebook Inc.), Imran Akbar (Facebook Inc.), Sukumar Kalmanje (Facebook Inc.), Leandro Silva (Facebook Inc.), John Stamford (Facebook Inc.), Yanai Golany (Facebook Inc.), Jim Piazza (Facebook Inc.), Sriram Sankar (Facebook Inc.)

  • ZTE-Predictor: a Disk Failure Prediction System based on LSTM
    Hongzhang Yang (School of Software & Microelectronics, Peking University, and ZTE Corporation), Zongzhao Li (ZTE Corporation), Huiyuan Qiang (ZTE Corporation), Zhongliang Li (ZTE Corporation), Yaofeng Tu (ZTE Corporation), Yahui Yang (School of Software & Microelectronics, Peking University)

  • Neuraltran: Optimal Data Transformation for Privacy-Preserving Machine Learning by Leveraging Neural Networks
    Changchang Liu (IBM T. J. Watson Research Center), Wei-Han Lee (IBM T. J. Watson Research Center), Seraphin Calo (IBM T. J. Watson Research Center)

Fast Abstracts #1
Chaired by Regina Moraes, U. Campinas
  • Secure Consensus Generation with Distributed DoH
    Philipp Jeitner (Technical University of Darmstadt), Haya Shulman (Fraunhofer Institute for Secure Information Technology SIT), Michael Waidner (Fraunhofer Institute for Secure Information Technology SIT)
  • Design and Performance Analysis of Software Defined Networking based Web Services adopting Moving Target Defense
    Dong Seong Kim (University of Queensland), Minjune Kim (University of Queensland), Jin-Hee Cho (Virginia Tech), Hyuk Lim (Gwangju Institute of Science & Technology), Terrence J. Moore (Army Research Lab), Frederica F. Nelson (Army Research Lab)

  • Tomographic measuring sensors system for analysis and visualization of technological processes
    Mariusz Mazurek (Institute of Philosophy and Sociology of the Polish Academy of Sciences), Tomasz Rymarczyk (R&D Center Netrix S.A., and University of Economics and Innovation in Lublin), Grzegorz Kłosowski (Lublin University of Technology), Michał Maj (R&D Center Netrix S.A., and University of Economics and Innovation in Lublin), Przemysław Adamkiewicz (R&D Center Netrix S.A., and University of Economics and Innovation in Lublin)


16:55 – 17:55 (CEST).
      Research Track #5 || Research Track #6 || Industry Track #3 || Fast Abstracts #2
Research Track #5. Network Security and Privacy
Chaired by Yennun Huang, Academia Sinica, Taiwan
  • Ephemeral Exit Bridges for Tor
    Zhao Zhang (Georgetown University), Tavish Vaidya (Georgetown University), Kartik Subramanian (Jericho High School), Wenchao Zhou (Georgetown University), Micah Sherr (Georgetown University)

  • The Impact of DNS Insecurity on Time
    Philipp Jeitner (Tu Darmstadt), Haya Shulman (Fraunhofer SIT), Michael Waidner (Fraunhofer SIT, TU Darmstadt)

  • (practice report): Depending on HTTP/2 for Privacy? Good Luck!
    Gargi Mitra (Indian Institute of Technology Madras), Prasanna Karthik Vairam (Indian Institute of Technology Madras), Patanjali SLPSK (Indian Institute of Technology Madras), V. Kamakoti (Indian Institute of Technology Madras), Nitin Chandrachoodan (Indian Institute of Technology Madras)
  • (practice report): Diving Into Email Bomb Attack
    Markus Schneider (Fraunhofer SIT), Haya Shulman (Fraunhofer SIT), Adi Sidis (Fraunhofer SIT), Ravid Sidis (Fraunhofer SIT), Michael Waidner (Fraunhofer SIT, TU Darmstadt)

Research Track #6. Embedded and Mobile
Chaired by Marc Dacier, Eurocom
  • HardSnap: Leveraging Hardware Snapshotting for Embedded Systems Security Testing
    Nassim Corteggiani (EURECOM), Aurélien Francillon (EURECOM)

  • iScanU: A Portable Scanner for Undocumented Instructions on RISC Processors
    Rens Dofferhoff (Leiden University), Michael Göebel (Leiden University), Kristian Rietveld (Leiden University)

  • Libspector: Context-Aware Large-Scale Network Traffic Analysis of Android Applications
    Onur Zungur (Boston University), Gianluca Stringhini (Boston University), Manuel Egele (Boston University)

Industry Track #3. Networks
Chaired by Harigovind V. Ramasamy, Amazon
  • Simulating Reliability of IoT Networks with RelIoT
    Kazim Ergun (University of California San Diego), Xiaofan Yu (University of California San Diego), Nitish Nagesh (University of California San Diego), Ludmila Cherkasova (Arm Research), Pietro Mercati (Intel Corporation), Raid Ayoub (Intel Corporation), Tajana Rosing (University of California San Diego)

  • Performance-Aware Wi-Fi Problem Diagnosis and Mitigation through Peer-to-Peer Data Sharing
    Nathan Mickulicz (YinzCam, Inc)
    Priya Narasimhan (Electrical and Computer Engineering, Carnegie Mellon University)

Fast Abstracts #2
Chaired by Nuno Antunes, U. Coimbra
  • MPC for Securing Internet Infrastructure
    Kris Shrishak (Technical University of Darmstadt), Haya Shulman (Fraunhofer Institute for Secure Information Technology SIT)
  • Pitfalls of Provably Secure Systems in Internet - The Case of Chronos-NTP Philipp Jeitner (Technical University of Darmstadt), Haya Shulman (Technical University of Darmstadt), Michael Waidner (Technical University of Darmstadt, and Fraunhofer Institute for Secure Information Technology SIT)
  • SIMBA: An Efficient Simulator for Blockchain Applications
    Seyed Mehdi Fattahi (New York Institute of Technology), Tokunbo Makanju (New York Institute of Technology), Amin Milani Fard (New York Institute of Technology)


18:00 – 18:30 (CEST).
      Research Track #7 || Research Track #8 || Industry Track #4 
Research Track #7. Memory and Storage
Chaired by Devesh Tiwari, Northeastern University
  • Foosball Coding: Correcting Shift Errors and Bit Flip Errors in 3D Racetrack Memory
    Samantha Archer (Duke University), Georgios Mappouras (Duke University), Daniel J. Sorin (Duke University), Robert Calderbank (Duke University)

  • Extreme Protection against Data Loss with Single-Overlap Declustered Parity
    Huan Ke (The University of Chicago), Haryadi S. Gunawi (The University of Chicago), David Bonnie (Los Alamos National Laboratory), Nathan DeBardeleben (Los Alamos National Laboratory), Michael Grosskopf (Los Alamos National Laboratory), Terry Grové (Los Alamos National Laboratory), Dominic Manno (Los Alamos National Laboratory), Elisabeth Moore (Los Alamos National Laboratory), Brad Settlemyer (Los Alamos National Laboratory)

Research Track #8. Fault Injection Tools
Chaired by Long Wang, IBM Research
  • Chaser: A Enhanced Fault Injection Tool for Tracing Soft Errors in MPI Applications
    Qiang Guan (Kent State University), Xunchao Hu (DeepBits Technology), Terence Grove (Los Alamos National Lab), Bo Fang (University of British Columbia), Hailong Jiang (Kent State University), Heng Yin (University of California, Riverside), Nathen DeBardeleben (Los Alamos National Lab)

  • ProFIPy: Programmable Software Fault Injection as-a-Service
    Domenico Cotroneo (Università degli Studi di Napoli Federico II), Luigi De Simone (Università degli Studi di Napoli Federico II), Pietro Liguori (Università degli Studi di Napoli Federico II), Roberto Natella (Università degli Studi di Napoli Federico II)

Industry Track #4. Panel: "Reflections on dealing with the Next Set of Dependability Challenges - Patterns and Anti-Patterns"
Chaired by Wilfried Steiner, TTTech

With the intervention of the following panelists:

  • John Meyer, University of Michigan.
  • Hermann Kopetz,  Vienna University of Technology.
  • Jay Lala, Raytheon Company.


18:30 – 19:00 (CEST). 
      Awards announcement & Recognitions
Awards announcement & Recognitions
Award Announcements
  • Jean-Claude Laprie Award
  • William C. Carter Award
  • Raising Start in Dependability
  • Test-of-Time
  • DSN2020 best paper
  • Sponsor Recognition and Intel intervention as DSN 2020 Platinum Sponsor
  • The memory of DSN



June 29 | June 30 | July 1 | July 2

July 2, 2020

15:00 – 15:15 (CEST).
      Rising Star in Dependability award presentation
Winner: Karthik Pattabiraman
University of British Columbia, Canada

The winner of the 2020 Rising Star in Dependability Award is:

Karthik Pattabiraman
University of British Columbia, Canada

Citation from the nomination letter:

"While traditionally, dependable computer systems have been confined to domains where cost was not a primary concern, Dr. Pattabiraman has developed innovative techniques to make computer systems dependable at low cost, thereby allowing their use in our daily lives."

Bio: Karthik Pattabiraman received his M.S and PhD. degrees from the University of Illinois at Urbana-Champaign (UIUC) in 2004 and 2009 respectively. After a post-doctoral stint at Microsoft Research (MSR), Karthik joined the University of British Columbia (UBC) in 2010, where he is now an Associate Professor of Electrical and Computer Engineering (ECE). Karthik's research interests are in error-resilient software systems, software reliability, and Internet of Things (IoT) security.  He is a recipient of numerous awards and honors including the William Carter award in 2008, the distinguished alumni early career educator award from UIUC’s Computer Science department in 2018, the 2018 Killam Faculty Research Prize and the 2016 Killam Faculty Research Fellowship from UBC, and the NSERC Discovery Accelerator Supplement (DAS) award in Canada in 2015. Karthik is a senior member of the IEEE and the ACM, and the vice-chair of the IFIP Working Group on Dependable Computing and Fault Tolerance (10.4).

Webpage: http://blogs.ubc.ca/karthik


15:15 – 15:55 (CEST).
      Keynote #3
Keynote #3: Guaranteeing acceptable levels of performability in modern interconnection networks despite congestion
Jose Duato, Member of the Spanish Royal Academy of Sciences and Professor of Computer Architecture, Universitat Politècnica de València (Spain)
July 2 @ 15:15 - 15:55 (CEST)

As the number, variety, and sophistication of Internet applications keeps growing and the number of client requests per time unit keeps increasing, datacenters are adopting hyperscale computing solutions to scale with the demand, and provide appropriate support for interactive services. As system size increases, the cost of the interconnection network grows faster than system size, thus becoming increasingly important to carefully design it to prevent overprovisioning. However, by doing so, the network operation point moves closer to saturation, and sudden traffic bursts may lead to congestion. This situation is aggravated by the recent introduction of flow control in datacenter networks to cope with RDMA requirements. The result is a massive performance degradation whenever some network region becomes congested. Moreover, performance degradation may remain for long even after the traffic bursts that congested the network have already been transmitted. This performance degradation is not compatible with trustworthiness. In this keynote, I will show why congestion appears in an interconnection network, how it propagates, and why performance may degrade so dramatically. Different kinds of congestion will be identified. Also, a global solution to address the congestion problem will be proposed. It consists of several complementary mechanisms that cooperate to address all kinds of congestion and operate at different time scales. Some of these mechanisms have been recently incorporated into commercial products and are being standardized. Keywords: Interconnection network, congestion management, datacenters

Jose Duato is Professor in the Department of Computer Engineering (DISCA) at the Technical University of Valencia (Universitat Politècnica de València). His current research interests include interconnection networks, multicore and multiprocessor architectures, and accelerators for deep learning. He published over 500 refereed papers. According to Google Scholar, his publications received more than 16,000 citations. He proposed a theory of deadlock-free adaptive routing that has been used in the design of the routing algorithms for the Cray T3E supercomputer, the on-chip router of the Alpha 21364 microprocessor, and the IBM BlueGene/L supercomputer. He also developed RECN, a scalable congestion management technique, and a very efficient routing algorithm for fat trees that has been incorporated into Sun Microsystem's 3456-port InfiniBand Magnum switch. Prof. Duato led the Advanced Technology Group in the HyperTransport Consortium, and was the main contributor to the High Node Count HyperTransport Specification 1.0. He also led the development of rCUDA, which enables remote virtualized access to GP-GPU accelerators using a CUDA interface. Prof. Duato is the first author of the book "Interconnection Networks: An Engineering Approach". He also served as a member of the editorial boards of IEEE Transactions on Parallel and Distributed Systems, IEEE Transactions on Computers, and IEEE Computer Architecture Letters. Prof. Duato was awarded with the National Research Prize in 2009 and the “Rey Jaime I” Prize in 2006. He is a member of the Spanish Royal Academy of Sciences.


16:00 – 17:00 (CEST).
      Research Track #09 || Research Track #10 || Industry Track 5 || Fast Abstracts #3
Research Track #9. IoT and Cyber-physical Systems
Chaired by Chung Hwan Kim, NEC Research
  • Hybrid Firmware Analysis for Known Mobile and IoT Security Vulnerabilities
    Pengfei Sun (Shape Security), Luis Garcia (University of California, Los Angeles), Gabriel Salles-Loustau (Rutgers University), Saman Zonouz (Rutgers University)

  • Real-Time Context-aware Detection of Unsafe Events in Robot-Assisted Surgery
    Mohammad Samin Yasar (University of Virginia), Homa Alemzadeh (University of Virginia)

  • Scalable Approach to Enhancing ICS Resilience by Network Diversity
    Tingting Li (Cardiff University), Cheng Feng (Siemens Corporate Technology), Chris Hankin (Imperial College London)

  • Cross-App Interference Threats in Smart Homes: Categorization, Detection and Handling
    Haotian Chi (Temple University), Qiang Zeng (University of South Carolina), Xiaojiang Du (Temple University), Jiaping Yu (Temple University)

Research Track #10. Byzantine to Blockchain
Chaired by Miguel Correia, University of Lisboa
  • From Byzantine Replication to Blockchain: Consensus is only the Beginning
    Alysson Bessani (FCUL, University of Lisboa), Eduardo Alchieri (University of Brasilia), João Sousa (FCUL, University of Lisboa), André Oliveira (FCUL, University of Lisboa), Fernando Pedone (University of Lugano)

  • EPIC: Efficient Asynchronous BFT with Adaptive Security
    Chao Liu (UMBC)
    Sisi Duan (UMBC)
    Haibin Zhang (UMBC)

  • On Incentive Compatible Role-based Reward Distribution in Algorand
    Mehdi Fooladgar (Isfahan University of Technology), Mohammad Hossein Manshaei (Florida International University), Murtuza Jadliwala (University of Texas at San Antonio), Mohammad Ashiqur Rahman (Florida International University)

  • FSTR: Funds Skewness aware Transaction Routing for Payment Channel Networks

Industry Track #5. Modelling and Knowledge Representation
Chaired by Harigovind V. Ramasamy, Amazon
  • Fundamental Challenges of Cyber-Physical Systems Security Modeling
    Georgios Bakirtzis (University of Virginia), Garrett Ward (Honeywell International Inc.), Christopher Deloglos (Virginia Commonwealth University), Carl Elks (Virginia Commonwealth University), Barry Horowitz (University of Virginia), Cody Fleming (University of Virginia)

  • Ontology Configuration Management for Knowledge-Centric Systems Engineering in Industry
    Borja Lopez (The REUSE Company), Jose María Alvarez Rodríguez (Universidad Carlos III de Madrid), Eugenio Parra (Universidad Carlos III de Madrid), Jose Luis de la Vara (Universidad de Castilla-La Mancha)

Fast Abstracts #3
Chaired by Roberto Natella, Univ of Napoli
  • Fault Tree Analysis: Identifying Maximum Probability Minimal Cut Sets with MaxSAT
    Martín Barrère (Institute for Security Science and Technology, Imperial College London), Chris Hankin (Institute for Security Science and Technology, Imperial College London)

  • Impact of Coding Styles on Behaviours of Static Analysis Tools for Web Applications
    Ibéria Medeiros (LASIGE, Faculdade de Ciencias, Universidade de Lisboa), Nuno Neves (LASIGE, Faculdade de Ciencias, Universidade de Lisboa)
  • A Novel Graphical Security Model for Evolving Cyber Attacks in Internet of Things
    Dong Seong Kim (The University of Queensland), Kok Onn Chee (The University of Queensland), Mengmeng Ge (Deakin University)


17:10 – 18:10 (CEST).
      Research Track #11 || Research Track #12 || Best of SELSE || Fast Abstracts #4
Research Track #11. Trusted Cloud Computing
Chaired by Zhongshu Gu, IBM Research
  • SeGShare: Secure Group File Sharing in the Cloud using Enclaves
    Benny Fuhry (SAP SE), Lina Hirschoff (SAP SE), Samuel Koesnadi (SAP SE), Florian Kerschbaum (University of Waterloo)

  • Omega: a Secure Event Ordering Service for the Edge
    Cláudio Correia (Instituto Superior Técnico, Universidade de Lisboa), Luis Rodrigues (INESC-ID, IST, ULisboa), Miguel Correia (INESC-ID / IST / Univ. Lisboa)

  • Trust Management as a Service: Enabling Trusted Execution in the Face of Byzantine Stakeholders
    Franz Gregor (TU Dresden), Wojciech Ozga (TU Dresden), Sébastien Vaucher (University of Neuchâtel), Rafael Pires (University of Neuchâtel), Do Le Quoc (TU Dresden), Sergei Arnautov (Scontain UG), André Martin (TU Dresden), Valerio Schiavoni (University of Neuchâtel), Pascal Felber (University of Neuchâtel), Christof Fetzer (TU Dresden)

  • UPA: An Automated, Accurate and Efficient Differentially Private Big-data Mining System
    Tsz On Li (The University of Hong Kong), Jianyu Jiang (The University of Hong Kong), Qi Ji (The University of Hong Kong), Chi Chiu So (The University of Hong Kong), JiaCheng Ma (The University of Hong Kong), Xusheng Chen (The University of Hong Kong), Tianxiang Shen (The University of Hong Kong), Heming Cui (The University of Hong Kong), Amy Wang (The University of Hong Kong)

Research Track #12. Formal and ML Modeling
Chaired by Gueyoung Jung, AT&T Research
  • Enhancing Reliability-Aware Speedup Modelling via Replication
    Zaeem Hussain (University of Pittsburgh), Taieb Znati (University of Pittsburgh), Rami Melhem (University of Pittsburgh)

  • Service-based Resilience for Embedded IoT Networks
    Doganalp Ergenc (University of Hamburg), Jacek Rak (Gdansk University of Technology), Mathias Fischer (University of Hamburg)

  • Mining Multivariate Discrete Event Sequences for Knowledge Discovery and Anomaly Detection
    Bin Nie (College of William and Mary), Jianwu Xu (NEC Laboratories America), Jacob Alter (College of William and Mary), Haifeng Chen (NEC Laboratories America), Evegenia Smirni (College of William and Mary)

  • (practice report): Learning to Reliably Deliver Streaming Data with Apache Kafka
    Han Wu (Free University of Berlin), Zhihao Shang (Free University of Berlin), Katinka Wolter (Free University of Berlin)

Best of SELSE
  • Software-only Triple Diverse Redundancy on GPUs for Autonomous Driving Platforms
    Sergi Alcaide (UPC - Barcelona Supercomputing Center), Leonidas Kosmidis (UPC - Barcelona Supercomputing Center), Carles Hernandez (UPV - Barcelona Supercomputing Center), Jaume Abella (Barcelona Supercomputing Center)

  • A Machine Learning-based Error Model of Voltage-Scaled Circuits
    Dongning Ma (ECE Department, Villanova), Xun Jiao (ECE Department, Villanova)
  • An Overview of the Risk Posed by Thermal Neutrons to the Reliability of Computing Devices
    Daniel Oliveira (UFPR), Sean Blanchard (LANL), Nathan DeBardeleben (LANL), Stephen Wender (LANL), Fernando F. dos Santos (UFRGS), Gabriel Piscoya Davila (UFRGS), Philippe Navaux (UFRGS), Carlo Cazzaniga (STFC), Christopher Frost (STFC), Robert C. Baumann (consultant), Paolo Rech (UFRGS/LANL).
Fast Abstracts #4
Chaired by Nuno Antunes, U. Coimbra
  • The Effect of Motion on PPG Heart Rate Sensors
    Daniel Hu (Purdue University), Calvin Henry (Purdue University), Saurabh Bagchi (Purdue University)

  • Reliability Analysis of Edge Scenarios using Pedestrian Mobility
    Kshitiz Goel (Purdue University), Abhishek Bhaumick (Purdue University), Peepika Kaushal (Purdue University), Saurabh Bagchi (Purdue University)
  • Improving the dependability of the ECG signal for classification of heart diseases
    Bartosz Przysucha (Departmetn of Quantitative Methods in Management, Lublin University of Technology), Tomasz Rymarczyk (Research and Development Center Netrix S.A., and University of Economics and Innovation in Lublin), Dariusz Wójcik (Research and Development Center Netrix S.A.), Michał Woś (Research and Development Center Netrix S.A.), Andres Vejar ((Research and Development Center Netrix S.A., and University of Economics and Innovation in Lublin))


18:15 – 18:30(CEST).
      Business Meeting
Business Meeting
  • Intro (moderator: Mohamed Kaaniche)

Future DSNs (decided and proposals)

  • DSN-2021, Sy Yen Kuo, National Taiwan University, Taipei (Taiwan)
  • DSN-2022, Yair Amir,  Johns Hopkins University, Baltimore (USA)
  • DSN-2023, Domenico Cotroneo, Federico II University of Naples, Naples (Italy)
  • DSN-2024 (beyond) Henrique Madeira, Univ. Coimbra, Coimbra (Portugal)
  • Questions & Remarks


June 29 | June 30 | July 1 | July 2