基于LSTM的DNS隐蔽信道检测方法
信息技术与网络安全 4期
陈解元
(国家计算机网络与信息安全管理中心,北京100032)
摘要: DNS滥用已成为网络空间安全治理中面临的最具挑战性的威胁之一。针对现有检测方法多以DNS请求流量为研究对象,忽略了响应流量特征的问题,提出一种基于长短期记忆网络(Long-Short Term Memory,LSTM)的DNS隐蔽信道检测方法。综合分析请求与响应流量特征,提取响应流量中时间戳、TTL、响应分组长度等特征点,并构建LSTM模型进行训练。实验结果表明,该方法在准确率、F1评分等指标方面取得了良好的结果,较现有方法有显著提高。
中圖分類號: TP393.08
文獻標識碼: A
DOI: 10.19358/j.issn.2096-5133.2022.04.009
引用格式: 陳解元. 基于LSTM的DNS隱蔽信道檢測方法[J].信息技術(shù)與網(wǎng)絡安全,2022,41(4):60-64,89.
文獻標識碼: A
DOI: 10.19358/j.issn.2096-5133.2022.04.009
引用格式: 陳解元. 基于LSTM的DNS隱蔽信道檢測方法[J].信息技術(shù)與網(wǎng)絡安全,2022,41(4):60-64,89.
DNS covert channel detection method based on LSTM
Chen Xieyuan
(National Computer Network Emergency Response Technical Team/Coordination Center of China(CNCERT/CC), Beijing 100032,China)
Abstract: DNS abuse has become one of the most challenging threats in cyberspace security governance.As the existing detection methods mostly focus on DNS request traffic but ignore the characteristics of response traffic,this paper proposed a DNS covert channel detection method based on Long Short Term Memory(LSTM). The characteristics of request and response traffic were comprehensively analyzed and the feature points such as timestamp, TTL and response packet length from response traffic were extracted,then the LSTM model was constructed for training.The experimental results show that the proposed method achieves good results in accuracy, F1 score and other indicators, which are significantly improved compared with existing methods.
Key words : DNS covert channel;machine learning;Long-Short Term Memory(LSTM)
0 引言
域名系統(tǒng)(Domain Name System,DNS)是把域名和IP地址相互映射的一種層次化分布式數(shù)據(jù)庫系統(tǒng),是互聯(lián)網(wǎng)上進行域名解析的核心基礎(chǔ)設施?;ヂ?lián)網(wǎng)訪問不可避免地需要進行域名解析服務,正由于DNS協(xié)議的必要性,大部分網(wǎng)絡中的防火墻不會攔截53端口上的數(shù)據(jù)包[1]。隨著DNSCat2、Iodine等工具的開源,越來越多的黑客開始利用DNS協(xié)議創(chuàng)建隱蔽信道[2],實現(xiàn)木馬控制、數(shù)據(jù)竊取、高級可持續(xù)威脅攻擊(Advanced Persistent Threat,APT)等,嚴重危害信息系統(tǒng)運營者權(quán)益和用戶個人隱私。
DNS隱蔽信道[3]是指將其他協(xié)議的內(nèi)容封裝在DNS數(shù)據(jù)包的可定義字段中,然后以DNS請求和響應包完成數(shù)據(jù)傳輸?shù)耐ǖ?。常見的可利用字段有QNAME字段、RDATA字段等[4]。
本文詳細內(nèi)容請下載:http://m.ihrv.cn/resource/share/2000004100
作者信息:
陳解元
(國家計算機網(wǎng)絡與信息安全管理中心,北京100032)

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