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A data type inference method based on long short-term memory by improved feature for weakness analysis in binary code

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FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE 2019年 100卷 1044-1052页

作者： Jeong, Junho Lim, Joong Yeon Son, Yunsik Dongguk Univ Dept Comp Sci & Engn 30 Pildong Ro 1 Gil Seoul 04620 South Korea Dongguk Univ Dept Mech Robot & Energy Engn 30 Pildong Ro 1 Gil Seoul 04620 South Korea

As software is used in various areas today, software security has become a crucial issue. Third-party libraries, which play a major role in software development, pose difficulties in analyzing and testing software security. It is essential to know the variables used in software and the data type information of each variable in order to identify the major weaknesses in the software. However, because the third-party library is generally of the binary code form, the variables, variable data type, program syntax, and semantic information in the source code are removed. Therefore, reconstructing the variables used and the data type information of the variables from binary code is the most important step in weak point analysis. Traditionally, this step of reconstructing information is based on pattern matching;however, the inference of data types is limited. We herein proposed a method of inferring data types using deep learning for variables determined based on pattern matching in binary code, and analyzed its performance. The proposed study has improved the feature generation method to solve the inconsistent problems of the features generated in the previous studies. As a result, the accuracy of prediction of float and double is improved by average 7.2% compared to the previous study, and the result is that the accuracy of 5.1% is increased overall. (C) 2019 Published by Elsevier B.V.

关键词： Data type inference Long short-term memory Reconstruction data information Software weakness binary code

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Pavement Marking Incorporated With binary code for Accurate Localization of Autonomous Vehicles

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IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 2022年第11期23卷 22290-22300页

作者： Wang, Yuhao Wang, Yuhong Ho, Ivan Wang-Hei Sheng, Wei Chen, Ling Hong Kong Polytech Univ Dept Elect & Informat Engn Hong Kong Peoples R China Hong Kong Polytech Univ Dept Civil & Environm Engn Hong Kong Peoples R China Xidian Univ Acad Adv Interdisciplinary Res Xian 710071 Peoples R China

Accurate localization is a critically important issue for autonomous vehicles as it is closely related to the safety and efficiency of autonomous driving. However, current technologies for autonomous vehicle localization face many challenges. To provide accurate and robust localization services to autonomous vehicles, we propose a novel solution by employing a newly designed pavement marking. This marking operates on color contrast, temperature contrast, and binary code with some special features. We also trained and customized an object detector based on a deep learning model: YOLOv5, and integrated it with the decoding algorithm. The localization system is capable of running at a steady frame rate of more than 50 FPS. Road trials up to 80 km/h were conducted, and satisfactory results confirmed the feasibility and robustness of the localization system. Specifically, with a common onboard camera, more than four continuous frames can be detected and decoded correctly when the speed is slower than 30 km/h. At least one frame can be detected and decoded correctly at a higher speed (i.e., 30 - 50 km/h). With a high-speed camera, more than 18 frames can be detected and decoded even at 80 km/h. The findings suggest that the specially designed road marking and associated algorithms can provide a viable and economical option for accurate localization of autonomous vehicles. The performance of the system has potentials for further improvement by using better hardware such as faster CPUs, GPUs, and thermal imaging techniques.

关键词： Roads Location awareness Autonomous vehicles Global Positioning System Image color analysis Cameras Wireless fidelity Accurate localization pavement marking object detection binary code

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binary code Similarity Detection 36

Binary Code Similarity Detection

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36th IEEE/ACM International Conference on Automated Software Engineering (ASE)

作者： Liu, Zian Swinburne Univ Technol Dept Comp Sci & Software Engn Data61 CSIRO Melbourne Vic Australia

ISBN: (纸本)9781665403375

binary code similarity detection is to detect the similarity of code at binary (assembly) level without source code. Existing work still has their limitation when dealing with mutated binary code with different compiling options. We proposed a novel approach to address this problem. By inspecting the binary code, we found that generally, within a function, some instructions aim to calculate (prepare) value for some other instructions. The latter instructions are defined by us the key instructions. Currently, we define four categories of key instructions: calling subfunctions, comparing instruction, returning instruction, and memory address writing instruction. Thus if we symbolically execute similar binary codes, the symbolic value at these key instructions should be similar. We implemented our idea into a tool. This prototype tool can: 1. symbolically execute binary code, 2. extract symbolic values at key instructions into a graph, and 3. compare the symbolic graph similarity. In our implementation, we also address some problems, including path explosion and loop handling.

关键词： binary code code analysis symbolic execution

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A new algorithm of links labelling for the isomorphism detection of various kinematic chains using binary code

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MECHANISM AND MACHINE THEORY 2019年 131卷 1-32页

作者： Rai, Rajneesh Kumar Punjabi, Sunil Ujjain Engn Coll Dept Mech Engn Ujjain 456010 Madhya Pradesh India

Isomorphism of kinematic chains (KCs) has always been a critical issue for the researchers dealing with structural synthesis. Consequently, many researchers of repute presented various methods during the last eight decades for the KCs with either simple and/or multiple joints. binary code is one of such various methods, but the major problem lies in the algorithm of links labelling, which becomes cumbersome, in particular, for large KCs. The paper presents a simple algorithm of links labelling used to find out a binary sequence which, in turn, provides a maximum binary code (chain invariant). The algorithm is tested for six, seven, eight, nine, ten, eleven, twelve and fifteen links with simple joints, seven and eight links KCs with multiple joints and finally, the Epicyclic gear trains (EGTs) with four, five and six links for its efficiency and reliability. The results are in full agreement with the references taken for the purpose. The paper discusses, in a unique way, the decoding of the binary codes of different KCs also. (C) 2018 Elsevier Ltd. All rights reserved.

关键词： Algorithm binary sequence binary code Isomorphism detection Links labelling Structural synthesis

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A NEW binary code OF LENGTH 10 AND COVERING RADIUS-1

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IEEE TRANSACTIONS ON INFORMATION THEORY 1991年第1期37卷 179-180页

作者： OSTERGARD, PRJ Digital Systems Laboratory Helsinki University of Technology Espoo Finland

A mixed code of covering radius 1 that has 60 codewords is constructed. This code is then used to show that K(10,1)>or=120.

关键词： code length binary code codes

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binary code Vulnerability Location Identification with Fine-grained Slicing 3

Binary Code Vulnerability Location Identification with Fine-...

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3rd Asia-Pacific Conference on Communications Technology and Computer Science (ACCTCS)

作者： Cui, Ningning Chen, Liwei Shi, Gang Univ Chinese Acad Sci Inst Informat Engn Chinese Acad Sci Sch Cyber Secur Beijing Peoples R China

ISBN: (纸本)9798350310801

Precise binary code vulnerability detection is an important research topic in software security. Currently, most software is released in binary form, which requires corresponding binary code vulnerability detection methods. Existing deep learning-based detection techniques can only detect binary code vulnerabilities but cannot accurately identify the location of vulnerabilities. Meanwhile, binary vulnerability detection is usually performed at the program or function level, which requires a large amount of markup data and cannot better focus on the vulnerable code. In order to mine the syntactic and semantic information of binary vulnerability code in a more fine-grained way, this paper proposes BVLIFS, a binary code vulnerability location identification system based on program slice. BVLIFS generates binary slices based on control dependencies and data dependencies of library/API function calls, and then uses hierarchical attention neural networks to extract the semantic information at the slice and basic block levels. After that, vulnerability locations are identified by combining the attention mechanism and vulnerability location matrix. We mark different codes with different colors depending on the level of contribution to vulnerability detection, which can help developers to locate and fix vulnerabilities. The experimental results show that our proposed method performs better and can locate vulnerabilities quickly compared to existing methods.

关键词： binary code vulnerability detection neural network vulnerability location identification program slicing

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On the dual distance and the gap of a binary code

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DISCRETE MATHEMATICS 1998年第1-3期192卷 333-336页

作者： Sole, P Tillich, JP ESSI CNRS I3S Lab Informat 650 F-06903 Sophia Antipolis France Univ Caen Dept Informat F-14032 Caen France

The coset graph of a nondegenerate cyclic code is orbital regular. This yields a lower bound on its average distance, a parameter which measures the average distortion of a code used in data compression. Using results of Shahrokhi and Szekely we generalize this bound to binary codes with a transitive automorphism group. (C) 1998 Elsevier Science B.V. All rights reserved.

关键词： average distortion averge distance carried Automorphism codes Transitive Data compression Dual DISTANCE Coset binary code

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CcNav: Understanding Compiler Optimizations in binary code

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IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS 2021年第2期27卷 667-677页

作者： Devkota, Sabin Aschwanden, Pascal Kunen, Adam Legendre, Matthew Isaacs, Katherine E. Univ Arizona Tucson AZ 85721 USA LLNI Belfast Antrim North Ireland

Program developers spend significant time on optimizing and tuning programs. During this iterative process, they apply optimizations, analyze the resulting code, and modify the compilation until they are satisfied. Understanding what the compiler did with the code is crucial to this process but is very time-consuming and labor-intensive. Users need to navigate through thousands of lines of binary code and correlate it to source code concepts to understand the results of the compilation and to identify optimizations. We present a design study in collaboration with program developers and performance analysts. Our collaborators work with various artifacts related to the program such as binary code, source code, control flow graphs, and call graphs. Through interviews, feedback, and pair-analytics sessions, we analyzed their tasks and workflow. Based on this task analysis and through a human-centric design process, we designed a visual analytics system Compilation Navigator (CcNav) to aid exploration of the effects of compiler optimizations on the program. CcNav provides a streamlined workflow and a unified context that integrates disparate artifacts. CcNav supports consistent interactions across all the artifacts making it easy to correlate binary code with source code concepts. CcNav enables users to navigate and filter large binary code to identify and summarize optimizations such as inlining, vectorization, loop unrolling, and code hoisting. We evaluate CcNav through guided sessions and semi-structured interviews. We reflect on our design process, particularly the immersive elements, and on the transferability of design studies through our experience with a previous design study on program analysis.

关键词： Design study program analysis compilation binary code transferability immersion

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Phase offset of binary code and its application to the CDMA mobile communications

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IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES 1998年第6期E81A卷 1145-1151页

作者： Han, YY Song, YJ Hanyang Univ Dept Elect Commun Engn Digital Commun Lab Sungdong Gu Seoul 133791 South Korea

It is important to know phase offsets of a binary code in the field of mobile communications because different phase offsets of the same code are used to distinguish signals received at a mobile station from those of different base stations. When the period of the code is not very long, the relative phase offset between the code and its shifted code can be found by counting the number of bits delayed from the code of the same bit streams. But as the period of the code increases, it becomes difficult to find the phase offset. This paper proposes a new method to calculate the phase offset of a binary code. We define an accumulator function, which is used to calculate the phase offsets between the code and its shifted code. Also the properties of the accumulator function are investigated. This number theoretical approach and its results show that this method is very easy for the phase offset calculation. Its application to the code division multiple access (CDMA) system to define a reference code is given. The simple circuit realization of the accumulator function to calculate the phase offset between the received code and receiver stored replica code is described.

关键词： phase offset binary code accumulator function code division multiple access system

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A new binary code of length 16 and minimum distance 3

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INFORMATION PROCESSING LETTERS 2015年第12期115卷 975-976页

作者： Milshtein, Moshe Hudson New Hampshire United States

关键词： Block code binary code Hamming distance Lower bound Combinatorial problems

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