5 Search Results for "Wang, Xi"

Document
DOI: 10.4230/LIPIcs.SEA.2023.10
Solving Directed Feedback Vertex Set by Iterative Reduction to Vertex Cover

Authors: Sebastian Angrick, Ben Bals, Katrin Casel, Sarel Cohen, Tobias Friedrich, Niko Hastrich, Theresa Hradilak, Davis Issac, Otto Kißig, Jonas Schmidt, and Leo Wendt

Published in: LIPIcs, Volume 265, 21st International Symposium on Experimental Algorithms (SEA 2023)

Abstract
In the Directed Feedback Vertex Set (DFVS) problem, one is given a directed graph G = (V,E) and wants to find a minimum cardinality set S ⊆ V such that G-S is acyclic. DFVS is a fundamental problem in computer science and finds applications in areas such as deadlock detection. The problem was the subject of the 2022 PACE coding challenge. We develop a novel exact algorithm for the problem that is tailored to perform well on instances that are mostly bi-directed. For such instances, we adapt techniques from the well-researched vertex cover problem. Our core idea is an iterative reduction to vertex cover. To this end, we also develop a new reduction rule that reduces the number of not bi-directed edges. With the resulting algorithm, we were able to win third place in the exact track of the PACE challenge. We perform computational experiments and compare the running time to other exact algorithms, in particular to the winning algorithm in PACE. Our experiments show that we outpace the other algorithms on instances that have a low density of uni-directed edges.
Cite as

Sebastian Angrick, Ben Bals, Katrin Casel, Sarel Cohen, Tobias Friedrich, Niko Hastrich, Theresa Hradilak, Davis Issac, Otto Kißig, Jonas Schmidt, and Leo Wendt. Solving Directed Feedback Vertex Set by Iterative Reduction to Vertex Cover. In 21st International Symposium on Experimental Algorithms (SEA 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 265, pp. 10:1-10:14, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2023)

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@InProceedings{angrick_et_al:LIPIcs.SEA.2023.10,
  author =	{Angrick, Sebastian and Bals, Ben and Casel, Katrin and Cohen, Sarel and Friedrich, Tobias and Hastrich, Niko and Hradilak, Theresa and Issac, Davis and Ki{\ss}ig, Otto and Schmidt, Jonas and Wendt, Leo},
  title =	{{Solving Directed Feedback Vertex Set by Iterative Reduction to Vertex Cover}},
  booktitle =	{21st International Symposium on Experimental Algorithms (SEA 2023)},
  pages =	{10:1--10:14},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-279-2},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{265},
  editor =	{Georgiadis, Loukas},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SEA.2023.10},
  URN =		{urn:nbn:de:0030-drops-183602},
  doi =		{10.4230/LIPIcs.SEA.2023.10},
  annote =	{Keywords: directed feedback vertex set, vertex cover, reduction rules}
}
Document
DOI: 10.4230/LIPIcs.ECOOP.2023.35
Synthesis-Aided Crash Consistency for Storage Systems

Authors: Jacob Van Geffen, Xi Wang, Emina Torlak, and James Bornholt

Published in: LIPIcs, Volume 263, 37th European Conference on Object-Oriented Programming (ECOOP 2023)

Abstract
Reliable storage systems must be crash consistent - guaranteed to recover to a consistent state after a crash. Crash consistency is non-trivial as it requires maintaining complex invariants about persistent data structures in the presence of caching, reordering, and system failures. Current programming models offer little support for implementing crash consistency, forcing storage system developers to roll their own consistency mechanisms. Bugs in these mechanisms can lead to severe data loss for applications that rely on persistent storage. This paper presents a new synthesis-aided programming model for building crash-consistent storage systems. In this approach, storage systems can assume an angelic crash-consistency model, where the underlying storage stack promises to resolve crashes in favor of consistency whenever possible. To realize this model, we introduce a new labeled writes interface for developers to identify their writes to disk, and develop a program synthesis tool, DepSynth, that generates dependency rules to enforce crash consistency over these labeled writes. We evaluate our model in a case study on a production storage system at Amazon Web Services. We find that DepSynth can automate crash consistency for this complex storage system, with similar results to existing expert-written code, and can automatically identify and correct consistency and performance issues.
Cite as

Jacob Van Geffen, Xi Wang, Emina Torlak, and James Bornholt. Synthesis-Aided Crash Consistency for Storage Systems. In 37th European Conference on Object-Oriented Programming (ECOOP 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 263, pp. 35:1-35:26, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2023)

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@InProceedings{vangeffen_et_al:LIPIcs.ECOOP.2023.35,
  author =	{Van Geffen, Jacob and Wang, Xi and Torlak, Emina and Bornholt, James},
  title =	{{Synthesis-Aided Crash Consistency for Storage Systems}},
  booktitle =	{37th European Conference on Object-Oriented Programming (ECOOP 2023)},
  pages =	{35:1--35:26},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-281-5},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{263},
  editor =	{Ali, Karim and Salvaneschi, Guido},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ECOOP.2023.35},
  URN =		{urn:nbn:de:0030-drops-182285},
  doi =		{10.4230/LIPIcs.ECOOP.2023.35},
  annote =	{Keywords: program synthesis, crash consistency, file systems}
}
Document
Extended Abstract
DOI: 10.4230/OASIcs.Tokenomics.2021.10
Detecting and Quantifying Crypto Wash Trading (Extended Abstract)

Authors: Lin William Cong, Xi Li, Ke Tang, and Yang Yang

Published in: OASIcs, Volume 97, 3rd International Conference on Blockchain Economics, Security and Protocols (Tokenomics 2021)

Abstract
We introduce systematic tests exploiting robust statistical and behavioral patterns in trading to detect fake transactions on 29 cryptocurrency exchanges. Regulated exchanges feature patterns consistently observed in financial markets and nature; abnormal first-significant-digit distributions, size rounding, and transaction tail distributions on unregulated exchanges reveal rampant manipulations unlikely driven by strategy or exchange heterogeneity. We quantify the wash trading on each unregulated exchange, which averaged over 70% of the reported volume. We further document how these fabricated volumes (trillions of dollars annually) improve exchange ranking, temporarily distort prices, and relate to exchange characteristics (e.g., age and userbase), market conditions, and regulation.
Cite as

Lin William Cong, Xi Li, Ke Tang, and Yang Yang. Detecting and Quantifying Crypto Wash Trading (Extended Abstract). In 3rd International Conference on Blockchain Economics, Security and Protocols (Tokenomics 2021). Open Access Series in Informatics (OASIcs), Volume 97, pp. 10:1-10:6, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2022)

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@InProceedings{cong_et_al:OASIcs.Tokenomics.2021.10,
  author =	{Cong, Lin William and Li, Xi and Tang, Ke and Yang, Yang},
  title =	{{Detecting and Quantifying Crypto Wash Trading}},
  booktitle =	{3rd International Conference on Blockchain Economics, Security and Protocols (Tokenomics 2021)},
  pages =	{10:1--10:6},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-220-4},
  ISSN =	{2190-6807},
  year =	{2022},
  volume =	{97},
  editor =	{Gramoli, Vincent and Halaburda, Hanna and Pass, Rafael},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.Tokenomics.2021.10},
  URN =		{urn:nbn:de:0030-drops-159072},
  doi =		{10.4230/OASIcs.Tokenomics.2021.10},
  annote =	{Keywords: Bitcoin, Cryptocurrency, FinTech, Forensic Finance, Fraud Detection, Regulation}
}
Document
DOI: 10.4230/LITES.7.1.1
Randomization as Mitigation of Directed Timing Inference Based Attacks on Time-Triggered Real-Time Systems with Task Replication

Authors: Kristin Krüger, Nils Vreman, Richard Pates, Martina Maggio, Marcus Völp, and Gerhard Fohler

Published in: LITES, Volume 7, Issue 1 (2021): Special Issue on Embedded System Security. Leibniz Transactions on Embedded Systems, Volume 7, Issue 1

Abstract
Time-triggered real-time systems achieve deterministic behavior using schedules that are constructed offline, based on scheduling constraints. Their deterministic behavior makes time-triggered systems suitable for usage in safety-critical environments, like avionics. However, this determinism also allows attackers to fine-tune attacks that can be carried out after studying the behavior of the system through side channels, targeting safety-critical victim tasks. Replication -- i.e., the execution of task variants across different cores -- is inherently able to tolerate both accidental and malicious faults (i.e. attacks) as long as these faults are independent of one another. Yet, targeted attacks on the timing behavior of tasks which utilize information gained about the system behavior violate the fault independence assumption fault tolerance is based on. This violation may give attackers the opportunity to compromise all replicas simultaneously, in particular if they can mount the attack from already compromised components. In this paper, we analyze vulnerabilities of time-triggered systems, focusing on safety-certified multicore real-time systems. We introduce two runtime mitigation strategies to withstand directed timing inference based attacks: (i) schedule randomization at slot level, and (ii) randomization within a set of offline constructed schedules. We evaluate these mitigation strategies with synthetic experiments and a real case study to show their effectiveness and practicality.
Cite as

Kristin Krüger, Nils Vreman, Richard Pates, Martina Maggio, Marcus Völp, and Gerhard Fohler. Randomization as Mitigation of Directed Timing Inference Based Attacks on Time-Triggered Real-Time Systems with Task Replication. In LITES, Volume 7, Issue 1 (2021): Special Issue on Embedded System Security. Leibniz Transactions on Embedded Systems, Volume 7, Issue 1, pp. 01:1-01:29, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2021)

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@Article{kruger_et_al:LITES.7.1.1,
  author =	{Kr\"{u}ger, Kristin and Vreman, Nils and Pates, Richard and Maggio, Martina and V\"{o}lp, Marcus and Fohler, Gerhard},
  title =	{{Randomization as Mitigation of Directed Timing Inference Based Attacks on Time-Triggered Real-Time Systems with Task Replication}},
  journal =	{Leibniz Transactions on Embedded Systems},
  pages =	{01:1--01:29},
  ISSN =	{2199-2002},
  year =	{2021},
  volume =	{7},
  number =	{1},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LITES.7.1.1},
  doi =		{10.4230/LITES.7.1.1},
  annote =	{Keywords: real-time systems, time-triggered systems, security}
}
Document
DOI: 10.4230/LIPIcs.SNAPL.2015.103
Toward a Dependability Case Language and Workflow for a Radiation Therapy System

Authors: Michael D. Ernst, Dan Grossman, Jon Jacky, Calvin Loncaric, Stuart Pernsteiner, Zachary Tatlock, Emina Torlak, and Xi Wang

Published in: LIPIcs, Volume 32, 1st Summit on Advances in Programming Languages (SNAPL 2015)

Abstract
We present a near-future research agenda for bringing a suite of modern programming-languages verification tools - specifically interactive theorem proving, solver-aided languages, and formally defined domain-specific languages - to the development of a specific safety-critical system, a radiotherapy medical device. We sketch how we believe recent programming-languages research advances can merge with existing best practices for safety-critical systems to increase system assurance and developer productivity. We motivate hypotheses central to our agenda: That we should start with a single specific system and that we need to integrate a variety of complementary verification and synthesis tools into system development.
Cite as

Michael D. Ernst, Dan Grossman, Jon Jacky, Calvin Loncaric, Stuart Pernsteiner, Zachary Tatlock, Emina Torlak, and Xi Wang. Toward a Dependability Case Language and Workflow for a Radiation Therapy System. In 1st Summit on Advances in Programming Languages (SNAPL 2015). Leibniz International Proceedings in Informatics (LIPIcs), Volume 32, pp. 103-112, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2015)

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@InProceedings{ernst_et_al:LIPIcs.SNAPL.2015.103,
  author =	{Ernst, Michael D. and Grossman, Dan and Jacky, Jon and Loncaric, Calvin and Pernsteiner, Stuart and Tatlock, Zachary and Torlak, Emina and Wang, Xi},
  title =	{{Toward a Dependability Case Language and Workflow for a Radiation Therapy System}},
  booktitle =	{1st Summit on Advances in Programming Languages (SNAPL 2015)},
  pages =	{103--112},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-939897-80-4},
  ISSN =	{1868-8969},
  year =	{2015},
  volume =	{32},
  editor =	{Ball, Thomas and Bodík, Rastislav and Krishnamurthi, Shriram and Lerner, Benjamin S. and Morriset, Greg},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SNAPL.2015.103},
  URN =		{urn:nbn:de:0030-drops-50208},
  doi =		{10.4230/LIPIcs.SNAPL.2015.103},
  annote =	{Keywords: Synthesis, Proof Assistants, Verification, Dependability Cases, Domain Specific Languages, Radiation Therapy}
}
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