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  • Open Access

    ARTICLE

    Software Vulnerability Mining and Analysis Based on Deep Learning

    Shibin Zhao*, Junhu Zhu, Jianshan Peng

    CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 3263-3287, 2024, DOI:10.32604/cmc.2024.041949 - 15 August 2024

    Abstract In recent years, the rapid development of computer software has led to numerous security problems, particularly software vulnerabilities. These flaws can cause significant harm to users’ privacy and property. Current security defect detection technology relies on manual or professional reasoning, leading to missed detection and high false detection rates. Artificial intelligence technology has led to the development of neural network models based on machine learning or deep learning to intelligently mine holes, reducing missed alarms and false alarms. So, this project aims to study Java source code defect detection methods for defects like null pointer… More >

  • Open Access

    ARTICLE

    Binary Program Vulnerability Mining Based on Neural Network

    Zhenhui Li1, Shuangping Xing1, Lin Yu1, Huiping Li1, Fan Zhou1, Guangqiang Yin1, Xikai Tang2, Zhiguo Wang1,*

    CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 1861-1879, 2024, DOI:10.32604/cmc.2023.046595 - 27 February 2024

    Abstract Software security analysts typically only have access to the executable program and cannot directly access the source code of the program. This poses significant challenges to security analysis. While it is crucial to identify vulnerabilities in such non-source code programs, there exists a limited set of generalized tools due to the low versatility of current vulnerability mining methods. However, these tools suffer from some shortcomings. In terms of targeted fuzzing, the path searching for target points is not streamlined enough, and the completely random testing leads to an excessively large search space. Additionally, when it… More >

  • Open Access

    ARTICLE

    Research on Known Vulnerability Detection Method Based on Firmware Analysis

    Wenjing Wang1, Tengteng Zhao1, Xiaolong Li1,*, Lei Huang1, Wei Zhang1, Hui Guo2

    Journal of Cyber Security, Vol.4, No.1, pp. 1-15, 2022, DOI:10.32604/jcs.2022.026816 - 05 May 2022

    Abstract At present, the network security situation is becoming more and more serious. Malicious network attacks such as computer viruses, Trojans and hacker attacks are becoming more and more rampant. National and group network attacks such as network information war and network terrorism have a serious damage to the production and life of the whole society. At the same time, with the rapid development of Internet of Things and the arrival of 5G era, IoT devices as an important part of industrial Internet system, have become an important target of infiltration attacks by hostile forces. This More >

  • Open Access

    ARTICLE

    A Survey on Binary Code Vulnerability Mining Technology

    Pengzhi Xu1,2, Zetian Mai1,2, Yuhao Lin1, Zhen Guo1,2,*, Victor S. Sheng3

    Journal of Information Hiding and Privacy Protection, Vol.3, No.4, pp. 165-179, 2021, DOI:10.32604/jihpp.2021.027280 - 22 March 2022

    Abstract With the increase of software complexity, the security threats faced by the software are also increasing day by day. So people pay more and more attention to the mining of software vulnerabilities. Although source code has rich semantics and strong comprehensibility, source code vulnerability mining has been widely used and has achieved significant development. However, due to the protection of commercial interests and intellectual property rights, it is difficult to obtain source code. Therefore, the research on the vulnerability mining technology of binary code has strong practical value. Based on the investigation of related technologies,… More >

  • Open Access

    ARTICLE

    PS-Fuzz: Efficient Graybox Firmware Fuzzing Based on Protocol State

    Xiaoyi Li, Xiaojun Pan, Yanbin Sun*

    Journal on Artificial Intelligence, Vol.3, No.1, pp. 21-31, 2021, DOI:10.32604/jai.2021.017328 - 02 April 2021

    Abstract The rise of the Internet of Things (IoT) exposes more and more important embedded devices to the network, which poses a serious threat to people’s lives and property. Therefore, ensuring the safety of embedded devices is a very important task. Fuzzing is currently the most effective technique for discovering vulnerabilities. In this work, we proposed PS-Fuzz (Protocol State Fuzz), a gray-box fuzzing technique based on protocol state orientation. By instrumenting the program that handles protocol fields in the firmware, the problem of lack of guidance information in common protocol fuzzing is solved. By recording and… More >

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