6 Search Results for "Wang, Ji"

Document
DOI: 10.4230/LITES.8.2.5
Bayesian Hybrid Automata: A Formal Model of Justified Belief in Interacting Hybrid Systems Subject to Imprecise Observation

Authors: Paul Kröger and Martin Fränzle

Published in: LITES, Volume 8, Issue 2 (2022): Special Issue on Distributed Hybrid Systems. Leibniz Transactions on Embedded Systems, Volume 8, Issue 2

Abstract
Hybrid discrete-continuous system dynamics arises when discrete actions, e.g. by a decision algorithm, meet continuous behaviour, e.g. due to physical processes and continuous control. A natural domain of such systems are emerging smart technologies which add elements of intelligence, co-operation, and adaptivity to physical entities, enabling them to interact with each other and with humans as systems of (human-)cyber-physical systems or (H)CPSes.Various flavours of hybrid automata have been suggested as a means to formally analyse CPS dynamics. In a previous article, we demonstrated that all these variants of hybrid automata provide inaccurate, in the sense of either overly pessimistic or overly optimistic, verdicts for engineered systems operating under imprecise observation of their environment due to, e.g., measurement error. We suggested a revised formal model, called Bayesian hybrid automata, that is able to represent state tracking and estimation in hybrid systems and thereby enhances precision of verdicts obtained from the model in comparison to traditional model variants.In this article, we present an extended definition of Bayesian hybrid automata which incorporates a new class of guard and invariant functions that allow to evaluate traditional guards and invariants over probability distributions. The resulting framework allows to model observers with knowledge about the control strategy of an observed agent but with imprecise estimates of the data on which the control decisions are based.
Cite as

Paul Kröger and Martin Fränzle. Bayesian Hybrid Automata: A Formal Model of Justified Belief in Interacting Hybrid Systems Subject to Imprecise Observation. In LITES, Volume 8, Issue 2 (2022): Special Issue on Distributed Hybrid Systems. Leibniz Transactions on Embedded Systems, Volume 8, Issue 2, pp. 05:1-05:27, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2022)

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@Article{kroger_et_al:LITES.8.2.5,
  author =	{Kr\"{o}ger, Paul and Fr\"{a}nzle, Martin},
  title =	{{Bayesian Hybrid Automata: A Formal Model of Justified Belief in Interacting Hybrid Systems Subject to Imprecise Observation}},
  journal =	{Leibniz Transactions on Embedded Systems},
  pages =	{05:1--05:27},
  ISSN =	{2199-2002},
  year =	{2022},
  volume =	{8},
  number =	{2},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LITES.8.2.5},
  doi =		{10.4230/LITES.8.2.5},
  annote =	{Keywords: }
}
Document
DOI: 10.4230/LITES.8.1.1
Susceptibility to Image Resolution in Face Recognition and Training Strategies to Enhance Robustness

Authors: Martin Knoche, Stefan Hörmann, and Gerhard Rigoll

Published in: LITES, Volume 8, Issue 1 (2022): Special Issue on Embedded Systems for Computer Vision. Leibniz Transactions on Embedded Systems, Volume 8, Issue 1

Abstract
Many face recognition approaches expect the input images to have similar image resolution. However, in real-world applications, the image resolution varies due to different image capture mechanisms or sources, affecting the performance of face recognition systems. This work first analyzes the image resolution susceptibility of modern face recognition. Face verification on the very popular LFW dataset drops from 99.23% accuracy to almost 55% when image dimensions of both images are reduced to arguable very poor resolution. With cross-resolution image pairs (one HR and one LR image), face verification accuracy is even worse. This characteristic is investigated more in-depth by analyzing the feature distances utilized for face verification. To increase the robustness, we propose two training strategies applied to a state-of-the-art face recognition model: 1) Training with 50% low resolution images within each batch and 2) using the cosine distance loss between high and low resolution features in a siamese network structure. Both methods significantly boost face verification accuracy for matching training and testing image resolutions. Training a network with different resolutions simultaneously instead of adding only one specific low resolution showed improvements across all resolutions and made a single model applicable to unknown resolutions. However, models trained for one particular low resolution perform better when using the exact resolution for testing. We improve the face verification accuracy from 96.86% to 97.72% on the popular LFW database with uniformly distributed image dimensions between 112 × 112 px and 5 × 5 px. Our approaches improve face verification accuracy even more from 77.56% to 87.17% for distributions focusing on lower images resolutions. Lastly, we propose specific image dimension sets focusing on high, mid, and low resolution for five well-known datasets to benchmark face verification accuracy in cross-resolution scenarios.
Cite as

Martin Knoche, Stefan Hörmann, and Gerhard Rigoll. Susceptibility to Image Resolution in Face Recognition and Training Strategies to Enhance Robustness. In LITES, Volume 8, Issue 1 (2022): Special Issue on Embedded Systems for Computer Vision. Leibniz Transactions on Embedded Systems, Volume 8, Issue 1, pp. 01:1-01:20, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2022)

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@Article{knoche_et_al:LITES.8.1.1,
  author =	{Knoche, Martin and H\"{o}rmann, Stefan and Rigoll, Gerhard},
  title =	{{Susceptibility to Image Resolution in Face Recognition and Training Strategies to Enhance Robustness}},
  journal =	{Leibniz Transactions on Embedded Systems},
  pages =	{01:1--01:20},
  ISSN =	{2199-2002},
  year =	{2022},
  volume =	{8},
  number =	{1},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LITES.8.1.1},
  doi =		{10.4230/LITES.8.1.1},
  annote =	{Keywords: recognition, resolution, cross, face, identification}
}
Document
DOI: 10.4230/LITES.8.1.3
HW-Flow: A Multi-Abstraction Level HW-CNN Codesign Pruning Methodology

Authors: Manoj-Rohit Vemparala, Nael Fasfous, Alexander Frickenstein, Emanuele Valpreda, Manfredi Camalleri, Qi Zhao, Christian Unger, Naveen-Shankar Nagaraja, Maurizio Martina, and Walter Stechele

Published in: LITES, Volume 8, Issue 1 (2022): Special Issue on Embedded Systems for Computer Vision. Leibniz Transactions on Embedded Systems, Volume 8, Issue 1

Abstract
Convolutional neural networks (CNNs) have produced unprecedented accuracy for many computer vision problems in the recent past. In power and compute-constrained embedded platforms, deploying modern CNNs can present many challenges. Most CNN architectures do not run in real-time due to the high number of computational operations involved during the inference phase. This emphasizes the role of CNN optimization techniques in early design space exploration. To estimate their efficacy in satisfying the target constraints, existing techniques are either hardware (HW) agnostic, pseudo-HW-aware by considering parameter and operation counts, or HW-aware through inflexible hardware-in-the-loop (HIL) setups. In this work, we introduce HW-Flow, a framework for optimizing and exploring CNN models based on three levels of hardware abstraction: Coarse, Mid and Fine. Through these levels, CNN design and optimization can be iteratively refined towards efficient execution on the target hardware platform. We present HW-Flow in the context of CNN pruning by augmenting a reinforcement learning agent with key metrics to understand the influence of its pruning actions on the inference hardware. With 2× reduction in energy and latency, we prune ResNet56, ResNet50, and DeepLabv3 with minimal accuracy degradation on the CIFAR-10, ImageNet, and CityScapes datasets, respectively.
Cite as

Manoj-Rohit Vemparala, Nael Fasfous, Alexander Frickenstein, Emanuele Valpreda, Manfredi Camalleri, Qi Zhao, Christian Unger, Naveen-Shankar Nagaraja, Maurizio Martina, and Walter Stechele. HW-Flow: A Multi-Abstraction Level HW-CNN Codesign Pruning Methodology. In LITES, Volume 8, Issue 1 (2022): Special Issue on Embedded Systems for Computer Vision. Leibniz Transactions on Embedded Systems, Volume 8, Issue 1, pp. 03:1-03:30, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2022)

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@Article{vemparala_et_al:LITES.8.1.3,
  author =	{Vemparala, Manoj-Rohit and Fasfous, Nael and Frickenstein, Alexander and Valpreda, Emanuele and Camalleri, Manfredi and Zhao, Qi and Unger, Christian and Nagaraja, Naveen-Shankar and Martina, Maurizio and Stechele, Walter},
  title =	{{HW-Flow: A Multi-Abstraction Level HW-CNN Codesign Pruning Methodology}},
  journal =	{Leibniz Transactions on Embedded Systems},
  pages =	{03:1--03:30},
  ISSN =	{2199-2002},
  year =	{2022},
  volume =	{8},
  number =	{1},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LITES.8.1.3},
  doi =		{10.4230/LITES.8.1.3},
  annote =	{Keywords: Convolutional Neural Networks, Optimization, Hardware Modeling, Pruning}
}
Document
DOI: 10.4230/LIPIcs.CP.2021.57
Making Rigorous Linear Programming Practical for Program Analysis

Authors: Tengbin Wang, Liqian Chen, Taoqing Chen, Guangsheng Fan, and Ji Wang

Published in: LIPIcs, Volume 210, 27th International Conference on Principles and Practice of Constraint Programming (CP 2021)

Abstract
Linear programming is a key technique for analysis and verification of numerical properties in programs, neural networks, etc. In particular, in program analysis based on abstract interpretation, many numerical abstract domains (such as Template Constraint Matrix, constraint-only polyhedra, etc.) are designed on top of linear programming. However, most state-of-the-art linear programming solvers use floating-point arithmetic in their implementations, leading to an approximate result that may be unsound. On the other hand, the solvers implemented using exact arithmetic are too costly. To this end, this paper focuses on advancing rigorous linear programming techniques based on floating-point arithmetic for building sound and efficient program analysis. Particularly, as a supplement to existing techniques, we present a novel rigorous linear programming technique based on Fourier-Mozkin elimination. On this basis, we implement a tool, namely, RlpSolver, combining our technique with existing techniques to lift effectiveness of rigorous linear programming in the scene of analysis and verification. Experimental results show that our technique is complementary to existing techniques, and their combination (RlpSolver) can achieve a better trade-off between cost and precision via heuristic rules.
Cite as

Tengbin Wang, Liqian Chen, Taoqing Chen, Guangsheng Fan, and Ji Wang. Making Rigorous Linear Programming Practical for Program Analysis. In 27th International Conference on Principles and Practice of Constraint Programming (CP 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 210, pp. 57:1-57:17, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2021)

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@InProceedings{wang_et_al:LIPIcs.CP.2021.57,
  author =	{Wang, Tengbin and Chen, Liqian and Chen, Taoqing and Fan, Guangsheng and Wang, Ji},
  title =	{{Making Rigorous Linear Programming Practical for Program Analysis}},
  booktitle =	{27th International Conference on Principles and Practice of Constraint Programming (CP 2021)},
  pages =	{57:1--57:17},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-211-2},
  ISSN =	{1868-8969},
  year =	{2021},
  volume =	{210},
  editor =	{Michel, Laurent D.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CP.2021.57},
  URN =		{urn:nbn:de:0030-drops-153486},
  doi =		{10.4230/LIPIcs.CP.2021.57},
  annote =	{Keywords: Linear programming, rigorous linear programming, abstract interpretation, program analysis, Fourier-Mozkin elimination}
}
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.TQC.2013.192
Symmetries of Codeword Stabilized Quantum Codes

Authors: Salman Beigi, Jianxin Chen, Markus Grassl, Zhengfeng Ji, Qiang Wang, and Bei Zeng

Published in: LIPIcs, Volume 22, 8th Conference on the Theory of Quantum Computation, Communication and Cryptography (TQC 2013)

Abstract
Symmetry is at the heart of coding theory. Codes with symmetry, especially cyclic codes, play an essential role in both theory and practical applications of classical error-correcting codes. Here we examine symmetry properties for codeword stabilized (CWS) quantum codes, which is the most general framework for constructing quantum error-correcting codes known to date. A CWS code Q can be represented by a self-dual additive code S and a classical code C, i.e., Q=(S,C), however this representation is in general not unique. We show that for any CWS code Q with certain permutation symmetry, one can always find a self-dual additive code S with the same permutation symmetry as Q such that Q=(S,C). As many good CWS codes have been found by starting from a chosen S, this ensures that when trying to find CWS codes with certain permutation symmetry, the choice of S with the same symmetry will suffice. A key step for this result is a new canonical representation for CWS codes, which is given in terms of a unique decomposition as union stabilizer codes. For CWS codes, so far mainly the standard form (G,C) has been considered, where G is a graph state. We analyze the symmetry of the corresponding graph of G, which in general cannot possess the same permutation symmetry as Q. We show that it is indeed the case for the toric code on a square lattice with translational symmetry, even if its encoding graph can be chosen to be translational invariant.
Cite as

Salman Beigi, Jianxin Chen, Markus Grassl, Zhengfeng Ji, Qiang Wang, and Bei Zeng. Symmetries of Codeword Stabilized Quantum Codes. In 8th Conference on the Theory of Quantum Computation, Communication and Cryptography (TQC 2013). Leibniz International Proceedings in Informatics (LIPIcs), Volume 22, pp. 192-206, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2013)

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@InProceedings{beigi_et_al:LIPIcs.TQC.2013.192,
  author =	{Beigi, Salman and Chen, Jianxin and Grassl, Markus and Ji, Zhengfeng and Wang, Qiang and Zeng, Bei},
  title =	{{Symmetries of Codeword Stabilized Quantum Codes}},
  booktitle =	{8th Conference on the Theory of Quantum Computation, Communication and Cryptography (TQC 2013)},
  pages =	{192--206},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-939897-55-2},
  ISSN =	{1868-8969},
  year =	{2013},
  volume =	{22},
  editor =	{Severini, Simone and Brandao, Fernando},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.TQC.2013.192},
  URN =		{urn:nbn:de:0030-drops-43129},
  doi =		{10.4230/LIPIcs.TQC.2013.192},
  annote =	{Keywords: CWS Codes, Union Stabilizer Codes, Permutation Symmetry, Toric Code}
}
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