Efficient Autonomous Defense System Using Machine Learning on Edge Device

作     者：Jaehyuk Cho 

作者机构：School of Electronic EngineeringSoongsil UniversitySeoul06978Korea 

出 版 物：《Computers, Materials & Continua》 (计算机、材料和连续体（英文）)

年 卷 期：2022年第70卷第2期

页      面：3565-3588页

核心收录：

学科分类：0831[工学-生物医学工程（可授工学、理学、医学学位）] 0808[工学-电气工程] 0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 0805[工学-材料科学与工程（可授工学、理学学位）] 0701[理学-数学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 0801[工学-力学（可授工学、理学学位）] 

基　　金：This research was funded by Korea Environmental Industry&Technology Institute(KEITI) Grant Number RE202101551and The APC was funded by Ministry of Environment(ME) 

主　　题：Autonomous defense side channel attack intrusion prevention system edge computing machine learning 

摘      要：As a large amount of data needs to be processed and speed needs to be improved,edge computing with ultra-low latency and ultra-connectivity is emerging as a new *** changes can lead to new cyber risks,and should therefore be considered for a security threat *** this end,we constructed an edge system to study security in two directions,hardware and ***,on the hardware side,we want to autonomically defend against hardware attacks such as side channel attacks by configuring field programmable gate array(FPGA)which is suitable for edge computing and identifying communication status to control the communication method according to *** addition,on the software side,data collected on the server performs end-to-end encryption via symmetric encryption ***,we modeled autonomous defense systems on the server by using machine learning which targets to incoming and outgoing *** log utilizes existing intrusion detection datasets that should be used in real-world *** log was used to detect intrusion early by modeling an intrusion prevention system to identify behaviors that violate security policy,and to utilize the existing intrusion detection data set that should be used in a real *** this,we designed an efficient autonomous defense system that can provide a stable system by detecting abnormal signals from the device and converting them to an effective method to control edge computing,and to detect and control abnormal intrusions on the server side.