Cloud Computing for Malicious Encrypted Traffic Analysis and Collaboration

Cloud Computing for Malicious Encrypted Traffic Analysis and Collaboration

Tzung-Han Jeng, Wen-Yang Luo, Chuan-Chiang Huang, Chien-Chih Chen, Kuang-Hung Chang, Yi-Ming Chen
Copyright: © 2021 |Pages: 18
DOI: 10.4018/IJGHPC.2021070102
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Abstract

As the application of network encryption technology expands, malicious attacks will also be protected by encryption mechanism, increasing the difficulty of detection. This paper focuses on the analysis of encrypted traffic in the network by hosting long-day encrypted traffic, coupled with a weighted algorithm commonly used in information retrieval and SSL/TLS fingerprint to detect malicious encrypted links. The experimental results show that the system proposed in this paper can identify potential malicious SSL/TLS fingerprints and malicious IP which cannot be recognized by other external threat information providers. The network packet decryption is not required to help clarify the full picture of the security incident and provide the basis of digital identification. Finally, the new threat intelligence obtained from the correlation analysis of this paper can be applied to regional joint defense or intelligence exchange between organizations. In addition, the framework adopts Google cloud platform and microservice technology to form an integrated serverless computing architecture.
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Botnets are one of the most serious security threats today. Many cybercrimes are related to botnets such as DDoS, click fraud, phishing, spamming, sniffing traffic and spreading new malware (Anwar et al., 2014). The botmaster or botherder can use the C&C servers to remotely control the compromised hosts by installing a RAT (Remote Administration Tool or Remote Access Trojan). The C&C communication techniques are based on IRC, HTTP and P2P protocols. Many researches focus on C&C communication detection (Chen et al., 2017; Hong et al., 2015a; Hong et al., 2015b; Jeng et al., 2018; Sun et al., 2017), but most of them have no solution for detecting malicious encrypted traffic. More recently, attackers have used encrypted channels or covert communication mechanisms instead of plaintext transmission. For example, C&C traffic can occur through pages and images on online social networks, covert DNS traffic, and Tor (The Onion Router) (Gardiner et al., 2014).

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