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High Power Laser and Particle Beams, Volume. 36, Issue 4, 043018(2024)

Leakage signal classification and recognition method based on fusion features

Yunfeng Kou1, Fei Dai2, Zhiguo Zhao3, Jianming Lü1, and Xie Ma1
Author Affiliations
  • 1Chengdu Xinxinshenfeng Electronics Co, Ltd, Chengdu 611731, China
  • 2Beihang University, Beijing 100083, China
  • 3China Electronics Technology Cyber Security Co., Ltd, Chengdu 610041, China
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    References(15)

    [1] Liu Wenbin, Ding Jianfeng, Kou Yunfeng, . Research on electromagnetic vulnerability of air-gapped network[J]. High Power Laser and Particle Beams, 31, 103215(2019).

    [2] Liu Wenbin, Wang Menghan, Kou Yunfeng, . Behavior recognition and security application of electronic equipment based on electromagnetic leakage signal[J]. Communications Technology, 52, 1761-1765(2019).

    [3] Liu Wenbin, Ding Jianfeng, Kou Yunfeng, . Software-defined electromagnetic leakage technology and its application[J]. Communications Technology, 50, 2094-2099(2017).

    [4] Wang Menghan, Kou Yunfeng, Liu Wenbin, . Real-time monitoring and intelligent recognition of electromagnetic leakage signals in computer networks[J]. Communications Technology, 52, 1755-1760(2019).

    [5] Guan Tianmin, Han Zhenzhong, Mao Jian. Research on the detection method of electromagnetic information leakage from display by machine learning[J]. Journal of Cyber Security, 6, 101-109(2021).

    [6] Xu Yanyun, Zhang Meng, Huang Weiqing. Study on detectable distance for electromagnetic information leakage of information equipment[J]. Journal of Cyber Security, 5, 44-56(2020).

    [7] Sehatbakhsh N, Nazari A, Alam M, et al. REMOTE: robust external malware detection framework by using electromagnetic signals[J]. IEEE Transactions on Computers, 69, 312-326(2020).

    [8] Werner F T, Yilmaz B B, Prvulovic M, et al. Leveraging EM side-channels for recognizing components on a motherboard[J]. IEEE Transactions on Electromagnetic Compatibility, 63, 502-515(2021).

    [9] Jorgensen E J, Werner F T, Prvulovic M, et al. Deep learning classification of motherboard components by leveraging EM side-channel signals[J]. Journal of Hardware and Systems Security, 5, 114-126(2021).

    [10] Ding Jianfeng, Liu Wenbin, Ding Lei, . New threat analysis of electromagnetic information leakage in electronic equipment based on active detection[J]. Communications Technology, 51, 936-940(2018).

    [11] Ding Jianfeng, Liu Wenbin, Wang Menghan, . Threat analysis of computer information leakage in intermodulation of acoustic, optical and electromagnetic signals[J]. Communications Technology, 52, 967-970(2019).

    [12] Cheng Lei, Luo Rujun, Kou Yunfeng, . Verification of conductive electromagnetic information leakage model based on power line[J]. Communications Technology, 51, 941-946(2018).

    [13] Qi Guolei, Kou Yunfeng, Hu Hao, . Information leakage based on acoustic convert channel for air-gapped computers[J]. Communications Technology, 51, 700-704(2018).

    [14] Hu Hao, Luo Rujun, Qi Guolei, . Covert-optical transmission channel based on LED display[J]. Communications Technology, 51, 1689-1693(2018).

    [15] Guri M, Zadov B, Bykhovsky D, et al. PowerHammer: Exfiltrating data from air-gapped computers through power lines[J]. IEEE Transactions on Information Forensics and Security, 15, 1879-1890(2020).

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    Yunfeng Kou, Fei Dai, Zhiguo Zhao, Jianming Lü, Xie Ma. Leakage signal classification and recognition method based on fusion features[J]. High Power Laser and Particle Beams, 2024, 36(4): 043018

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    Paper Information

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    Received: Jun. 19, 2023

    Accepted: Aug. 29, 2023

    Published Online: Apr. 22, 2024

    The Author Email:

    DOI:10.11884/HPLPB202436.230186

    Topics

    laser devices and laser physics
    Lasers and Laser Optics
    Laser physics
    laser manufacturing
    Instrumentation, Measurement and Metrology