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control flow graph Based Multiclass Malware Detection Using Bi-normal Separation

DEFENCE SCIENCE JOURNAL 2016年第2期66卷 138-145页

作者： Kapoor, Akshay Dhavale, Sunita Def Inst Adv Technol Dept Comp Engn Girinagar 411025 India

control flow graphs (CFG) and OpCodes extracted from disassembled executable files are widely used for malware detection. Most of the research in static analysis is focused on binary class malware detection which only classifies an executable as benign or malware. To overcome this issue, CFG based multiclass malware detection system that automatically classifies the malware into their respective families is proposed. The use Bi-normal separation (BNS) as a feature scoring metric. Experimental results show that proposed method using BNS outperforms compared to hitherto use technique of document Frequency for multiclass metamorphic malware detection and achieves detection accuracy of 99.5 per cent.

关键词： separation control flow graph machine learning malware detection

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control flow graph Matching for Detecting Obfuscated Programs 50th

Control Flow Graph Matching for Detecting Obfuscated Program...

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50th Annual Convention of the Computer-Society-of-India (CSI) on Digital Life

作者： Behera, Chandan Kumar Sanjog, Genius Bhaskari, D. Lalitha Andhra Univ Dept Comp Sci & Syst Engn Visakhapatnam Andhra Pradesh India

ISBN: (纸本)9789811088483;9789811088476

Malicious programs like the viruses, worms, Trojan horses, and backdoors infect host computers by taking advantage of flaws of the software and thereby introducing some kind of secret functionalities. The authors of these malicious programs attempt to find new methods to get avoided from detection engines. They use different obfuscation techniques such as dead code insertion, instruction substitution to make the malicious programs more complex. Initially, obfuscation techniques those are used by software developers to protect their software from piracy are now misused by these malware authors. This paper intends to detect such obfuscated programs or malware using control flow graph (CFG) matching technique, using VF2 algorithm. If the original CFG of the executable is found to be isomorphic to subgraph of obfuscated CFG (under examination), then it can be classified as an obfuscated one.

关键词： Obfuscation Decompilation Optimization graph isomorphism control flow graph

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Performance analysis of automatic lookahead generation by control flow graph: some experiments

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SIMULATION PRACTICE AND THEORY 2001年第8期8卷 511-527页

作者： Zarei, B Pidd, M Univ Lancaster Dept Management Sci Lancaster LA1 4YW England

The performance of parallel discrete event models is highly dependent on lookahead, particularly when a conservative algorithm is employed. Unfortunately lookahead is known to be problem-dependent, which restricts the implementations of conservative algorithms. This paper uses a simple queuing network to show how this lookahead affects performance and discusses various techniques for automatic generation of lookahead using control flow graphs (CFGs). These methods are tested on the queuing network simulation running on a CRAY T3E 1200E. Results indicate that the automatic lookahead techniques, though requiring some time to compute, perform as well as the best manually extracted lookahead injected into the parallel program. (C) 2001 Elsevier Science BY. All rights reserved.

关键词： lookahead automatic lookahead generation parallel simulation control flow graph queuing network performance analysis

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Turna: a control flow graph reconstruction tool for RISC-V architecture

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COMPUTING 2023年第8期105卷 1821-1845页

作者： Sahin, Veysel Harun Sakarya Univ Dept Software Engn TR-54050 Serdivan Sakarya Turkiye

A control flow graph (CFG) is a type of directed graph that shows the execution paths of the programs. It is a mathematical structure that is actively used in software testing. It can be constructed from the source or the executable of the program. Construction of the CFG from the executable is called CFG reconstruction. CFG reconstruction is used in many areas of computer science, like reverse engineering, security analysis, and worst-case execution time analysis. CFG reconstruction can be performed using a static, dynamic, or hybrid approach. This paper introduces a new CFG reconstruction tool named Turna that uses a hybrid approach. Turna works on programs that are compiled for RISC-V architecture. One of the main phases of CFG reconstruction is basic block detection. Therefore, together with Turna, a new rule set and an algorithm for basic block detection from RISC-V executables are also introduced. The CFG reconstruction process and the outputs of Turna are shared and discussed.

关键词： Basic block control flow graph CFG reconstruction RISC-V ISA Software testing

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The flowing nature matters: feature learning from the control flow graph of source code for bug localization

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MACHINE LEARNING 2022年第3期111卷 853-870页

作者： Ma, Yi-Fan Li, Ming Nanjing Univ Nanjing Peoples R China

Bug localization plays an important role in software maintenance. Traditional works treat the source code from the lexical perspective, while some recent researches indicate that exploiting the program structure is beneficial for improving bug localization. control flow graph (CFG) is a widely used graph representation, which essentially represents the program structure. Although using graph neural network for feature learning is a straightforward way and has been proven effective in various software mining problems, this approach is inappropriate since adjacent nodes in the CFG could be totally unrelated in semantics. On the other hand, previous statements may affect the semantics of subsequent statements along the execution path, which we call the flowing nature of control flow graph. In this paper, we claim that the flowing nature should be explicitly considered and propose a novel model named cflow for bug localization, which employs a particular designed flow-based GRU for feature learning from the CFG. The flow-based GRU exploits the program structure represented by the CFG to transmit the semantics of statements along the execution path, which reflects the flowing nature. Experimental results on widely-used real-world software projects show that cflow significantly outperforms the state-of-the-art bug localization methods, indicating that exploiting the program structure from the CFG with respect to the flowing nature is beneficial for improving bug localization.

关键词： control flow graph Bug localization flow-based GRU Software mining

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Over-Approximated control flow graph Construction on Pure Esterel

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IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS 2010年第5期E93D卷 985-993页

作者： Kim, Chul-Joo Yun, Jeong-Han Kim, Seonggun Choe, Kwang-Moo Han, Taisook Korea Adv Inst Sci & Technol Div Comp Sci Taejon 305701 South Korea

Esterel is an imperative synchronous language for control-dominant reactive systems. Regardless of imperative features of Esterel, combination of parallel execution and preemption makes it difficult to build control flow graphs (CFGs) of Esterel programs. Simple and convenient CFGs can help to analyze Esterel programs. However, previous researches are not suitable for flow analyses of imperative languages. In this work, we present a method to construct over-approximated CFGs for Pure Esterel. Generated CFCs expose invisible interferences among threads and show program structures explicitly so that they are useful for program analyses based on graph theory or control-/data- flows.

关键词： esterel control flow graph synchronous language

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Integrating Path Testing with Software Reliability Estimation Using control flow graph

Integrating Path Testing with Software Reliability Estimatio...

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IEEE International Conference on Management of Innovation and Technology

作者： Hsu, Chao-Jung Huang, Chin-Yu Natl Tsing Hua Univ Dept Comp Sci Hsinchu 30043 Taiwan

ISBN: (纸本)9781424423293

In this paper, we propose a new approach to calculate a path's reliability along three basic programming structures, which include sequential, branching, and looping structures. The path's reliability is then taken to approximate the system's reliability, and an example is evaluated to validate and show the effectiveness of proposed method. The numerical example yields several findings. First, the proposed method can be effectively used in the early stages of testing. Second, the path reliability is highly relative to system reliability, and the estimated error of the proposed method is acceptable. Third, with higher test coverage on path testing, the accuracy of system reliability estimation can be further improved. Therefore, the proposed method is a viable alternative method for architecture-based software reliability modeling.

关键词： Architecture-based software reliability model Markov chain control flow graph Path testing

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Generating control flow graph from Java Card Byte Code 3

Generating Control Flow Graph from Java Card Byte Code

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3rd IEEE International Colloquium on Information Science and Technology (CIST)

作者： Amine, Achkar Mohammed, Benattou Jean-Louis, Lanet Ibn Tofail Univ Kenitra Morocco Univ Limoges Lab XLIM Secure Smart Devices F-87065 Limoges France

ISBN: (纸本)9781479959792

The verification process in industrial context of embedded software in smart card is considered difficult, extremely time-consuming, and costly, with very few tools and techniques available to aid in the verification process. The work proposed in this paper consist to define the main architecture of testing java card application and a specific test model which consists of reducing a given java-card application to one method which have one input and one output data which correspond with the real communication between the card and the off-card applications. The paper details the first step of testing constraint specifications which consist of modeling and generating control flow graph in inter and intra procedural level from the byte code of java-card applications.

关键词： Java embedded systems flow graphs program testing program verification smart cards software architecture Java card application Java card byte code architecture constraint specifications testing control flow graph embedded software industrial context inter procedural level intra procedural level off-card applications smart card test model verification process flow graphs Process control Silicon Smart cards Switches Testing Health Smart Cards flowcharts control flow diagram Java Java programming language experimental model Embedded software program testing program verification address byte Software architecture Process control Switches Embedded systems Java Card

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Survey of Malware Analysis through control flow graph using Machine Learning 22

Survey of Malware Analysis through Control Flow Graph using ...

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IEEE 22nd International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom) / BigDataSE Conference / CSE Conference / EUC Conference / ISCI Conference

作者： Mitra, Shaswata Torri, Stephen A. Mittal, Sudip Mississippi State Univ Dept Comp Sci & Engn Mississippi State MS 39762 USA

ISBN: (纸本)9798350381993;9798350382006

Malware is a significant threat to the security of computer systems and networks, requiring sophisticated techniques to analyze its behavior and functionality for detection. Due to their rapid evolution, traditional signature-based malware detection methods have become ineffective in detecting new and unknown malware. One of the most promising techniques to overcome the limitations of signature-based detection is using control flow graphs (CFGs). CFGs leverage the structural information of a program to represent the possible paths of execution as a graph, where nodes represent instructions and edges represent control flow dependencies. Machine learning (ML) algorithms extract these features from CFGs and classify them as malicious or benign. In this survey, we aim to review some state-of-the-art methods for malware detection through CFGs using ML, focusing on the different ways of extracting, representing, and classifying. Specifically, we present a comprehensive overview of various CFG features and different ML algorithms applied to CFG-based malware detection. We provide an in-depth analysis of the challenges and limitations of these approaches, as well as suggest potential solutions to address persisting open problems and promising future directions for research in this field.

关键词： Cybersecurity Malware Analysis control flow graph Machine Learning

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Malware Variant Detection and Classification Using control flow graph

Malware Variant Detection and Classification Using Control F...

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5th International Conference on Convergence and Hybrid Information Technology (ICHIT)

作者： Shin, Donghwi Lee, Kwangwoo Won, Dongho Sungkyunkwan Univ Sch Informat & Commun Engn Informat Secur Grp Suwon 440746 Gyeonggi Do South Korea

ISBN: (纸本)9783642241055;9783642241062

The number of malware increases steadily and is too many. So a malware analyst cannot analyze these manually. Therefore many researchers are working on automatic malware analysis. As a result of these researches, there are so many algorithms. The representative example may be a behavior based malware automatic analysis system. For example, these are the Bitblaze [1], Anubis[2], and so on. However these behaviors based analysis result is not enough. So for more detail analysis and advanced automatic analysis feature, the automatic static analysis engine is necessary. Then some projects apply an automatic static analysis engine and the research on automatic static analysis is working. These analysis methods use the structural characteristic of malware, and that is the reason the malware is also software, there is a toolkit for a malware generation, and a malware author reuse some codes. For automatic static analysis, it is so useful that the static analysis engine uses the structural characteristic of malware. However previous researches have some problem. For example, these are a performance, false positive, detection ratio, and so on. Therefore we'll describe another method that used the structural characteristic of malware.

关键词： Malware Malicious Software control flow graph Structural Analysis Profiling Signature Security

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