#Twiti: Social Listening for Threat Intelligence


연구 분야: Safety



학회: WWW '21: Proceedings of the Web Conference 2021


초록

Twitter is a popular public source for threat hunting. Many security vendors and security professionals use Twitter in practice for collecting Indicators of Compromise (IOCs). However, little is known about IOCs on Twitter. Their important characteristics such as earliness, uniqueness, and accuracy have never been investigated. Moreover, how to extract IOCs from Twitter with high accuracy is not obvious. In this paper, we present Twiti, a system that automatically extracts various forms of malware IOCs from Twitter. Based on the collected IOCs, we conduct the first empirical assessment and thorough analysis of malware IOCs on Twitter. Twiti extracts IOCs from tweets identified as having malware IOC information by leveraging natural language processing and machine learning techniques. With extensive evaluation, we demonstrate that not only can Twiti extract malware IOCs accurately, but also the extracted IOCs are unique and early. By analyzing IOCs in Twiti from various aspects, we find that Twitter captures ongoing malware threats such as Emotet variants and malware distribution sites better than other public threat intelligence (TI) feeds. We also find that only a tiny fraction of IOCs on Twitter come from commercial vendor accounts and individual Twitter users are the main contributors of the early detected or exclusive IOCs, which indicates that Twitter can provide many valuable IOCs uncovered in commercial domain


Author Profile
Hyejin Shin

Samsung Research Republic of Korea

Korea
Author Profile
Woo-chul Shim

Samsung Research Republic of Korea

Korea
Author Profile
Saebom Kim

Samsung Research Republic of Korea

Korea

📄 논문 정보

발행 연도 2021년
인용수 16
출판 국가 Korea
사이트 ACM
좋아요 수 0

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