INTELLIGENT DETECTION AND ANALYSIS OF SOFTWARE VULNERABILITIES BASED ON ENCRYPTION ALGORITHMS AND FEATURE EXTRACTION

被引：0
|
作者：
Li, Heng [1 ]
Li, Xinqiang [2 ]
Wei, Hongchang [3 ]
机构：
[1] Shijiazhuang Informat Engn Vocat Coll, Software Engn Dept, Shijiazhuang 050000, Hebei, Peoples R China
[2] Shijiazhuang Informat Engn Vocat Coll, Mech & Elect Engn Dept, Shijiazhuang 050000, Hebei, Peoples R China
[3] Shijiazhuang Informat Engn Vocat Coll, Software Engn Dept, Shijiazhuang 050000, Hebei, Peoples R China
来源：
SCALABLE COMPUTING-PRACTICE AND EXPERIENCE | 2024年 / 25卷 / 02期
关键词：
Encryption algorithm; feature extraction; software vulnerabilities; intelligent detection;
D O I：
暂无
中图分类号：
TP31 [计算机软件];
学科分类号：
081202 ; 0835 ;
摘要：
Implement status detection of ship software, identify the source of faults in problematic software, and release new software versions. Based on the above requirements, the author regards the detection and control of ship software status as the core research content. Based on the actual operating environment of ship software, the functional requirements of software status detection were studied and analyzed, and a set of ship software status detection was designed and implemented, a software inspection and maintenance platform that integrates ship software operation and maintenance, as well as ship software version release and update. The author conducted practical verification of the SM3 and SM2 hybrid encryption algorithm and selected software on the ship for detection. After analyzing the experimental results, it has been proven that using a hybrid algorithm for encryption and decryption, the server can accurately obtain software information on the ship's platform, detect the software status on the ship, and locate specific problem files. For software that does not meet the standard status, the server can accurately transmit software information to the "component integration framework" and put the component in a "prohibited" scheduling state. After the server repairs the problematic software, the detection results of the software change and display as legal, while the software is in the "allowed" scheduling state in the "component integration framework".
引用
收藏
页数：9
相关论文
共 50 条
  • [1] INTELLIGENT DETECTION AND ANALYSIS OF SOFTWARE VULNERABILITIES BASED ON ENCRYPTION ALGORITHMS AND FEATURE EXTRACTION
    Li, Heng
    Li, Xinqiang
    Wei, Hongchang
    Scalable Computing, 2024, 25 (02): : 900 - 907
  • [2] On the Detection and Analysis of Software Security Vulnerabilities
    Wijesiriwardana, Chaman
    Wimalaratne, Prasad
    2017 IEEE INTERNATIONAL CONFERENCE ON IOT AND ITS APPLICATIONS (IEEE ICIOT), 2017,
  • [3] An analysis of Feature extraction and Classification Algorithms for Dangerous Object Detection
    Kibria, Sakib B.
    Hasan, Mohammad S.
    2017 2ND INTERNATIONAL CONFERENCE ON ELECTRICAL & ELECTRONIC ENGINEERING (ICEEE), 2017,
  • [4] Analysis of Edge Detection Algorithms for Feature Extraction in Satellite Images
    Pirzada, Syed Jahanzeb Hussain
    Siddiqui, Ayesha
    2013 IEEE INTERNATIONAL CONFERENCE ON SPACE SCIENCE AND COMMUNICATION (ICONSPACE), 2013, : 238 - 242
  • [5] Malicious software identification based on deep learning algorithms and API feature extraction
    Sun, Wei
    EURASIP JOURNAL ON INFORMATION SECURITY, 2025, 2025 (01):
  • [6] PermutEx: Feature-Extraction-Based Permutation A New Diffusion Scheme for Image Encryption Algorithms
    Khan, Muhammad Shahbaz
    Ahmad, Jawad
    Al-Dubai, Ahmed
    Jaroucheh, Zakwan
    Pitropakis, Nikolaos
    Buchanan, William J.
    2023 IEEE 28TH INTERNATIONAL WORKSHOP ON COMPUTER AIDED MODELING AND DESIGN OF COMMUNICATION LINKS AND NETWORKS, CAMAD 2023, 2023, : 188 - 193
  • [7] Comparative analysis of UWB deconvolution and feature extraction algorithms for GPR landmine detection
    Savelyev, TG
    Sato, M
    DETECTION AND REMEDIATION TECHNOLOGIES FOR MINES AND MINELIKE TARGETS IX, PTS 1 AND 2, 2004, 5415 : 1008 - 1018
  • [8] Software Defect Detection Based on Feature Fusion and Alias Analysis
    Li, Xuejian
    Zhu, Zhengguang
    2023 IEEE INTERNATIONAL TEST CONFERENCE IN ASIA, ITC-ASIA, 2023,
  • [9] On image matrix based feature extraction algorithms
    Wang, LW
    Wang, X
    Feng, JF
    IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS, 2006, 36 (01): : 194 - 197
  • [10] KPCA based on cultural algorithms feature extraction
    Institute of Automation, East China University of Science and Technology, Shanghai 200237, China
    Hua Dong Li Gong Da Xue/J East China Univ Sci Technol, 2008, 2 (256-260+300):
12345