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A Predictive Runtime Verification Framework for Cyber-Physical Systems 8

A Predictive Runtime Verification Framework for Cyber-Physic...

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8th IEEE International Conference on Software Security and Reliability-Companion (SERE-C)

作者： Yu, Kang Chen, Zhenbang Dong, Wei Natl Univ Def Technol Sch Comp Changsha Hunan Peoples R China

ISBN: (纸本)9781479958436

Runtime verification with a predictive semantics defines how to monitor a temporal property in a predictive manner. In this paper, we propose a predictive runtime verification framework for Cyber-Physical Systems (CPSs), which are usually open embedded systems, aiming to predict the runtime failures of CPSs before the failures really happen. We present the method for online predications using the program information and the runtime information. We have implemented a prototype framework based on JavaMOP. The experimental results demonstrate that our framework is generally applicable.

关键词： prediction runtime verification control flow graph

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graphRTL: an Agile Design Framework of RTL Code from Data flow graphs

GraphRTL: an Agile Design Framework of RTL Code from Data Fl...

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2nd International Symposium of Electronics Design Automation (ISEDA)

作者： Qiao, Yuheng Xie, Cai Ou, Zhaoting Lei, Peizhi Tian, Yan Chen, Jienan Univ Elect Sci & Technol China Chengdu 611731 Peoples R China

ISBN: (纸本)9798350352047;9798350352030

As the increasing demand for large and complex signal processing requirements, the efficient and fast design of signal processing circuits becomes an important issues. Agile design offers a new approach for rapid hardware design cycles. While this approach is a standard for software design, how to adapt it to hardware design properly remains an open question. In our work, we propose a framework for agile software and hardware co-design named graphRTL. The tool addresses the challenge of designing hardware for Digital Signal Processing (DSP). Instead of direct coding and debugging iteration, we employ data flow graphs (DFG) and control flow graphs (CFG) to automatically generate RTL code. The input to graphRTL is the flow graph of the designed circuit. Subsequently, the tool checks the graphs, reconstructs it, and then translates it into a configuration file for the compiler. Finally, the compiler autonomously generates the corresponding software to hardware code and RTL code. Compared to the traditional design route, graphRTL enhances design efficiency and broadens the design space. In our experiments, we achieved up to an 70% reduction in design time while maintaining a 5 to 10% reduction in hardware overhead for the designed circuits.

关键词： Data flow graph control flow graph Agile Design Compilers Digital Signal Processing RTL

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C500-CFG: A Novel Algorithm to Extract control flow-based Features for IoT Malware Detection 19

C500-CFG: A Novel Algorithm to Extract Control Flow-based Fe...

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19th International Symposium on Communications and Information Technologies (ISCIT)

作者： Tran Nghi Phu Le Hoang Nguyen Ngoc Toan Nguyen Dai Tho Nguyen Ngoc Binh VNU Univ Engn & Technol Hanoi Vietnam Peoples Secur Acad PSA Hanoi Vietnam

ISBN: (纸本)9781728150093

Static characteristic extraction method control flow-based features proposed by Ding has the ability to detect malicious code with higher accuracy than traditional Text-based methods. However, this method resolved NP-hard problem in a graph, therefore it is not feasible with the large-size and high-complexity programs. So, we propose the C500-CFG algorithm in control flow-based features based on the idea of dynamic programming, solving Ding's NP-hard problem in O( N-2) time complexity, where N is the number of basic blocks in decompiled executable codes. Our algorithm is more efficient and more outstanding in detecting malware than Ding's algorithm: fast processing time, allowing processing large files, using less memory and extracting more feature information. Applying our algorithms with IoT data sets gives outstanding results on 2 measures: Accuracy = 99.34%, F1-Score = 99.32%.

关键词： IoT Malware detection C500-CFG control flow graph

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Algorithm Classification Using Worst-Case Execution Time

Algorithm Classification Using Worst-Case Execution Time

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2nd IEEE International Conference on Computer Science and Information Technology

作者： Mehrotra, Mudit Goel, Ankur Agarwal, Nipun Bindu, M. Hima Sharma, Bhudev Jaypee Inst Informat Technol Univ Dept Comp Sci & Engn Noida India

ISBN: (纸本)9781424445189

Problems in computer science require some time to produce an output. Some can be executed in few seconds or minutes. Others require hours, days or even centuries to produce an output. In this paper, we propose a technique to classify a problem in any of the above two categories without executing the input source code for a large test case. First, a control flow graph is generated from the Intermediate code of the input source code. Then, this CFG is reduced and a set of linear equations is framed. The solution of these linear equations along with execution count of the loops is used to determine Worst Case Execution Time. This WCET is compared with a threshold to classify the problem as either having a definite or indefinite execution time. The main advantage of this approach is that control flow analysis is automatic and user annotations in terms of markers and scope are not required in the input code.

关键词： Worst Case Execution Time control flow graph Intermediate Code Symbol Table

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RELIABILITY ANALYSIS OF TEST CASES FOR PROGRAM SLICING 1

RELIABILITY ANALYSIS OF TEST CASES FOR PROGRAM SLICING

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1st International Conference on Innovation and Challenges in Cyber Security (ICICCS)

作者： Negi, Gaurav Elias, Eldo Kohli, Rashi Bibhu, Vimal Dr APJ AKTU CSE Dept Lucknow Uttar Pradesh India Amity Univ CSE Dept Greater Noida India

ISBN: (纸本)9781509020843

The concept used in the research paper includes program slicing which is referred as the process of computing the chosen set of instructions of the program, The slicing criterion refers to the slice that is likely to affect the values at some point while executing the program. The paper highlights the different test cases and comparative analysis of program slicing methods which corresponds to the applications which are usually utilized in software modification activities i.e. Debugging process, testing analysis and its phases, calculating complexity and program understanding etc. In the approach used in the paper the "slicing" method of the program focus on precise & definedsub-components of a program;which can further be used to produce the instructions needed for the program, relevant to an explicit method of computation. Applying slicing techniques to software's using slicing tools, we can determine which components can be facilitated and reused. The process of designing phase of and the reused patterns are likely to suggest improvement in the respective code.

关键词： control flow graph Dynamic slicing Program dependence graph Program slicing Static slicing Test cases

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JSAC: A Novel Framework to Detect Malicious JavaScript via CNNs over AST and CFG

JSAC: A Novel Framework to Detect Malicious JavaScript via C...

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International Joint Conference on Neural Networks (IJCNN)

作者： Jiang, Hongliang Yang, Yuxing Sun, Lu Jiang, Lin Beijing Univ Posts & Telecommun Scool Comp Sci Beijing Peoples R China

ISBN: (纸本)9781728119854

JavaScript (JS) is a dominant programming language in web/mobile development, while it is also notoriously abused by attackers due to its powerful characteristics, e.g., dynamic, prototype-based and multi-paradigm, which foil most static and dynamic analysis approaches. To detect malicious JS instances, several machine learning-based methods have been developed recently. However, these methods took JS as a natural language instead of a programming one, which can not capture its syntactic and semantic features. In this paper, we present JSAC, a novel framework to detect JS malware. It combines deep learning and program analysis techniques to capture the syntactic and semantic features of JS programs. Specifically, to get a JS program's syntactic information, we build its abstract syntax tree and employ a tree-based convolutional neural network (CNN) to extract features from it. To get its semantic information, we construct its control flow graph and feed it to another graph-based CNN. Last, the features extracted from two CNNs are fused for final detection. Evaluation on a corpus of 69,523 JS files indicates that JSAC outperforms 4 other models with 98.73% F1-score in detecting JS malware.

关键词： Malicious JavaScript CNN Abstract Syntax Tree control flow graph

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Improving Mobile User Interface Testing with Model Driven Monkey Search 14

Improving Mobile User Interface Testing with Model Driven Mo...

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14th IEEE Conference on Software Testing, Verification and Validation (ICST)

作者： Doyle, Jordan Saber, Takfarinas Arcaini, Paolo Ventresque, Anthony Univ Coll Dublin Sch Comp Sci Lero UCD Dublin Ireland Natl Inst Informat Tokyo Japan

ISBN: (纸本)9781665444569

Testing mobile applications often relies on tools, such as Exerciser Monkey for Android systems, that simulate user input. Exerciser Monkey, for example, generates random events (e.g., touches, gestures, navigational keys) that give developers a sense of what their application will do when deployed on real mobile phones with real users interacting with it. These tools, however, have no knowledge of the underlying applications' structures and only interact with them randomly or in a predefined manner (e.g., if developers designed scenarios, a labour-intensive task) - making them slow and poor at finding bugs. In this paper, we propose a novel control flow structure able to represent the code of Android applications, including all the interactive elements. We show that our structure can increase the effectiveness (higher coverage) and efficiency (removing duplicate/redundant tests) of the Exerciser Monkey by giving it knowledge of the test environment. We compare the interface coverage achieved by the Exerciser Monkey with our new Monkey++ using a depth first search of our control flow structure and show that while the random nature of Exerciser Monkey creates slow test suites of poor coverage, the test suite created by a depth first search is one order of magnitude faster and achieves full coverage of the user interaction elements. We believe this research will lead to a more effective and efficient Exerciser Monkey, as well as better targeted search based techniques for automated Android testing.

关键词： Android control flow graph Exerciser Monkey Test Generation

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Regression Test Selection for Android Applications

Regression Test Selection for Android Applications

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IEEE/ACM International Conference on Mobile Software Engineering and Systems (MOBILESoft)

作者： Do, Quan Yang, Guowei Che, Meiru Hui, Darren Ridgeway, Jefferson Texas State Univ Dept Comp Sci San Marcos TX 78666 USA Univ Texas Austin Dept Elect & Comp Engn Austin TX 78712 USA Elizabeth City State Univ Elizabeth City NC 27909 USA

ISBN: (纸本)9781450341783

Mobile platform pervades human life, and much research in recent years has focused on improving the reliability of mobile applications on this platform, for example by applying automatic testing. However, researchers have primarily considered testing of single version of mobile applications. Although regression testing has been extensively studied for desktop applications, the approaches for desktop applications cannot be directly applied to mobile applications. Our approach leverages the combination of static impact analysis and dynamic code coverage information, and identifies a subset of test cases for re-execution on the modified app version. We implement our approach for Android apps, and illustrate its usefulness based on an Android application.

关键词： Change impact analysis coverage control flow graph

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A case against indirect jumps for secure programs 19

A case against indirect jumps for secure programs

引用

9th Software Security, Protection, and Reverse Engineering Workshop (SSPREW)

作者： Gonzalvez, Alexandre Lashermes, Ronan IMT Atlantique INRIA TAMIS Nantes France INRIA SED&LHS Rennes France

ISBN: (纸本)9781450377461

A desired property of secure programs is control flowintegrity (CFI): an attacker must not be able to alter how instructions are chained as specified in the program. Numerous techniques try to achieve this property with various trade-offs. But to achieve fine-grained CFI, one is required to extract a precise control flow graph (CFG), describing how instructions are chained together. Unfortunately it is not achievable in general. In this paper, we propose a way to overcome this impossibility result by restricting the instruction set architecture (ISA) semantics. We show that forbidding indirect jumps unlocks a precise CFG extraction for all acceptable programs. We discuss the implications and limitations of the new semantics and argue for the adoption of restricted ISAs for security-related computation.

关键词： control flow integrity control flow graph instruction set architecture

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Exploiting Sub-graph Isomorphism and Probabilistic Neural Networks for the Detection of Hardware Trojans at RTL 19

Exploiting Sub-Graph Isomorphism and Probabilistic Neural Ne...

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19th IEEE International High Level Design Validation and Test Workshop (HLDVT)

作者： Demrozi, Florenc Zucchelli, Riccardo Pravadelli, Graziano Univ Verona Dept Comp Sci Verona Italy

ISBN: (纸本)9781509039975

Hardware Trojans (HTs) have been generally inserted at the lower levels of the digital system design and fabrication process, where, due to the high complexity of the hardware model, their detection is more difficult. However, RTL models are becoming more and more complex, making difficult the identification of malicious behaviours also at this level. Unfortunately, only a few verification techniques have been proposed for the identification of HTs in RTL descriptions. To fill in the gap, this paper proposes a technique that exploits graph-based features and a probabilistic neural network to identify and classify HTs at RTL. The approach identifies suspicious locations inside the RTL description according to a set of known HTs. In addition, it returns a couple of similarity indexes to measure the probability that a suspicious location actually contains a malicious behaviour.

关键词： Hardware Trojan Probabilistic Neural Network control flow graph graphlet

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