loading
Papers

Research.Publish.Connect.

Paper

Authors: Tal Hadad ; Bronislav Sidik ; Nir Ofek ; Rami Puzis and Lior Rokach

Affiliation: Ben-Gurion University of the Negev, Israel

ISBN: 978-989-758-209-7

Keyword(s): Mobile Malware, Malware Detection, User Feedback Analysis, Text Mining, Review Mining.

Abstract: With the increasing number of smartphone users, mobile malware has become a serious threat. Similar to the best practice on personal computers, the users are encouraged to install anti-virus and intrusion detection software on their mobile devices. Nevertheless, their devises are far from being fully protected. Major mobile application distributors, designated stores and marketplaces, inspect the uploaded application with state of the art malware detection tools and remove applications that turned to be malicious. Unfortunately, many malicious applications have a large window of opportunity until they are removed from the marketplace. Meanwhile users install the applications, use them, and leave comments in the respective marketplaces. Occasionally such comments trigger the interest of malware laboratories in inspecting a particular application and thus, speedup its removal from the marketplaces. In this paper, we present a new approach for mining user comments in mobile application marketplaces with a purpose of detecting malicious apps. Two computationally efficient features are suggested and evaluated using data collected from the "Amazon Appstore". Using these two features, we show that feedback generated by the crowd is effective for detecting malicious applications without the need for downloading them. (More)

PDF ImageFull Text

Download
CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 18.207.134.98

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Hadad, T.; Sidik, B.; Ofek, N.; Puzis, R. and Rokach, L. (2017). User Feedback Analysis for Mobile Malware Detection.In Proceedings of the 3rd International Conference on Information Systems Security and Privacy - Volume 1: ICISSP, ISBN 978-989-758-209-7, pages 83-94. DOI: 10.5220/0006131200830094

@conference{icissp17,
author={Tal Hadad. and Bronislav Sidik. and Nir Ofek. and Rami Puzis. and Lior Rokach.},
title={User Feedback Analysis for Mobile Malware Detection},
booktitle={Proceedings of the 3rd International Conference on Information Systems Security and Privacy - Volume 1: ICISSP,},
year={2017},
pages={83-94},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006131200830094},
isbn={978-989-758-209-7},
}

TY - CONF

JO - Proceedings of the 3rd International Conference on Information Systems Security and Privacy - Volume 1: ICISSP,
TI - User Feedback Analysis for Mobile Malware Detection
SN - 978-989-758-209-7
AU - Hadad, T.
AU - Sidik, B.
AU - Ofek, N.
AU - Puzis, R.
AU - Rokach, L.
PY - 2017
SP - 83
EP - 94
DO - 10.5220/0006131200830094

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.