@inproceedings{e64bef0fec5845b9bb37ec068f9ae5c6,
title = "Idea: Automatic localization of malicious behaviors in android malware with hidden Markov models",
abstract = "The lack of ground truth about malicious behaviors exhibited by current Android malware forces researchers to embark upon a lengthy process of manually analyzing malware instances. In this paper, we propose a method to automatically localize malicious behaviors residing in representations of apps{\textquoteright} runtime behaviors. Our initial evaluation using generated API calls traces of Android apps demonstrates the method{\textquoteright}s feasibility and applicability.",
author = "Aleieldin Salem and Tabea Schmidt and Alexander Pretschner",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG, part of Springer Nature 2018.; 10th International Symposium on Engineering Secure Software and Systems, ESSoS 2018 ; Conference date: 26-06-2018 Through 27-06-2018",
year = "2018",
doi = "10.1007/978-3-319-94496-8_8",
language = "English",
isbn = "9783319944951",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "108--115",
editor = "Such, {Jose M.} and Awais Rashid and Mathias Payer",
booktitle = "Engineering Secure Software and Systems - 10th International Symposium, ESSoS 2018, Proceedings",
}