{"title":"Network Attack Detection based on Domain Attack Behavior Analysis","authors":"Weifeng Wang, Xinyu Zhang, Likai Dong, Yuling Fan, Xinyi Diao, Tao Xu","doi":"10.1109/CISP-BMEI51763.2020.9263663","DOIUrl":null,"url":null,"abstract":"Network security has become an important issue in our work and life. Hackers' attack mode has been upgraded from normal attack to APT( ( Advanced Persistent Threat, APT) attack. The key of APT attack chain is the penetration and intrusion of active directory, which can not be completely detected via the traditional IDS and antivirus software. Further more, lack of security protection of existing solutions for domain control aggravates this problem. Although researchers have proposed methods for domain attack detection, many of them have not yet been converted into effective market-oriented products. In this paper, we analyzes the common domain intrusion methods, various domain related attack behavior characteristics were extracted from ATT&CK matrix (Advanced tactics, techniques, and common knowledge) for analysis and simulation test. Based on analyzing the log file generated by the attack, the domain attack detection rules are established and input into the analysis engine. Finally, the available domain intrusion detection system is designed and implemented. Experimental results show that the network attack detection method based on the analysis of domain attack behavior can analyze the log file in real time and effectively detect the malicious intrusion behavior of hackers , which could facilitate managers find and eliminate network security threats immediately.","PeriodicalId":346757,"journal":{"name":"2020 13th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","volume":"10 6","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 13th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CISP-BMEI51763.2020.9263663","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Network security has become an important issue in our work and life. Hackers' attack mode has been upgraded from normal attack to APT( ( Advanced Persistent Threat, APT) attack. The key of APT attack chain is the penetration and intrusion of active directory, which can not be completely detected via the traditional IDS and antivirus software. Further more, lack of security protection of existing solutions for domain control aggravates this problem. Although researchers have proposed methods for domain attack detection, many of them have not yet been converted into effective market-oriented products. In this paper, we analyzes the common domain intrusion methods, various domain related attack behavior characteristics were extracted from ATT&CK matrix (Advanced tactics, techniques, and common knowledge) for analysis and simulation test. Based on analyzing the log file generated by the attack, the domain attack detection rules are established and input into the analysis engine. Finally, the available domain intrusion detection system is designed and implemented. Experimental results show that the network attack detection method based on the analysis of domain attack behavior can analyze the log file in real time and effectively detect the malicious intrusion behavior of hackers , which could facilitate managers find and eliminate network security threats immediately.
网络安全已经成为我们工作和生活中的一个重要问题。黑客攻击模式由普通攻击升级为APT(Advanced Persistent Threat, APT)攻击。APT攻击链的关键是活动目录的渗透和入侵,传统的IDS和杀毒软件无法完全检测到。此外,现有的域控制解决方案缺乏安全保护,加剧了这一问题。虽然研究人员提出了一些领域攻击检测的方法,但许多方法尚未转化为有效的市场产品。本文分析了常用的领域入侵方法,从ATT&CK矩阵(Advanced tactics, techniques, and common knowledge)中提取了各种领域相关的攻击行为特征,用于分析和仿真测试。通过对攻击产生的日志文件进行分析,建立域攻击检测规则,并输入到分析引擎中。最后,设计并实现了可用的域入侵检测系统。实验结果表明,基于域攻击行为分析的网络攻击检测方法能够实时分析日志文件,有效检测黑客的恶意入侵行为,便于管理者及时发现并消除网络安全威胁。