Visible to the public Biblio

Filters: Author is Liang, H.  [Clear All Filters]
2021-01-20
Wang, H., Yang, J., Wang, X., Li, F., Liu, W., Liang, H..  2020.  Feature Fingerprint Extraction and Abnormity Diagnosis Method of the Vibration on the GIS. 2020 IEEE International Conference on High Voltage Engineering and Application (ICHVE). :1—4.

Mechanical faults of Gas Insulated Switchgear (GIS) often occurred, which may cause serious losses. Detecting vibration signal was effective for condition monitoring and fault diagnosis of GIS. The vibration characteristic of GIS in service was detected and researched based on a developed testing system in this paper, and feature fingerprint extraction method was proposed to evaluate vibration characteristics and diagnose mechanical defects. Through analyzing the spectrum of the vibration signal, we could see that vibration frequency of operating GIS was about 100Hz under normal condition. By means of the wavelet transformation, the vibration fingerprint was extracted for the diagnosis of mechanical vibration. The mechanical vibration characteristic of GIS including circuit breaker and arrester in service was detected, we could see that the frequency distribution of abnormal vibration signal was wider, it contained a lot of high harmonic components besides the 100Hz component, and the vibration acoustic fingerprint was totally different from the normal ones, that is, by comparing the frequency spectra and vibration fingerprint, the mechanical faults of GIS could be found effectively.

2018-03-26
Liu, W., Chen, F., Hu, H., Cheng, G., Huo, S., Liang, H..  2017.  A Novel Framework for Zero-Day Attacks Detection and Response with Cyberspace Mimic Defense Architecture. 2017 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC). :50–53.

In cyberspace, unknown zero-day attacks can bring safety hazards. Traditional defense methods based on signatures are ineffective. Based on the Cyberspace Mimic Defense (CMD) architecture, the paper proposes a framework to detect the attacks and respond to them. Inputs are assigned to all online redundant heterogeneous functionally equivalent modules. Their independent outputs are compared and the outputs in the majority will be the final response. The abnormal outputs can be detected and so can the attack. The damaged executive modules with abnormal outputs will be replaced with new ones from the diverse executive module pool. By analyzing the abnormal outputs, the correspondence between inputs and abnormal outputs can be built and inputs leading to recurrent abnormal outputs will be written into the zero-day attack related database and their reuses cannot work any longer, as the suspicious malicious inputs can be detected and processed. Further responses include IP blacklisting and patching, etc. The framework also uses honeypot like executive module to confuse the attacker. The proposed method can prevent the recurrent attack based on the same exploit.