@inproceedings{5e9f35cf653241d381fbf5ca397bad7d,
title = "A novel search engine to uncover potential victims for APT investigations",
abstract = "Advanced Persistent Threats (APT) are sophisticated and target-oriented cyber attacks which often leverage customized malware and bot control techniques to control the victims for remotely accessing valuable information. As the APT malware samples are specific and few, the signature-based or learning-based approaches are weak to detect them. In this paper, we take a more flexible strategy: developing a search engine for APT investigators to quickly uncover the potential victims based on the attributes of a known APT victim. We test our approach in a real APT case happened in a large enterprise network consisting of several thousands of computers which run a commercial antivirus system. In our best effort to prove, the search engine can uncover the other unknown 33 victims which are infected by the APT malware. Finally, the search engine is implemented on Hadoop platform. In the case of 440GB data, it can return the queries in 2 seconds.",
author = "Liu, {Shun Te} and Chen, {Yi Ming} and Lin, {Shiou Jing}",
year = "2013",
doi = "10.1007/978-3-642-40820-5_34",
language = "???core.languages.en_GB???",
isbn = "9783642408199",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "405--416",
booktitle = "Network and Parallel Computing - 10th IFIP International Conference, NPC 2013, Proceedings",
note = "10th IFIP International Conference on Network and Parallel Computing, NPC 2013 ; Conference date: 19-09-2013 Through 21-09-2013",
}