Mobile keylogger detection using machine learning

  S.Vinoth kumar,  Aruna sankaralingam

Keylogger, a highly specialized tool designed to record every keystroke made on the machine to giving the attacker the ability to steal large amounts of sensitive information silently. The primary objective of this project is to detect keylogger applications and prevent data loss and sensitive information leakage. In This project aims to identify the set of permissions and storage level owned by each of the applications and hence differentiate applications with proper permissions and keylogger applications that can abuse permissions .This technique of detecting keyloggers is completely Black-box its based on behavioral characteristics common to all keyloggers and it does not rely on the internal structure of the keylogger. The paper intends to develop a machine learning-based keylogger detection system on mobile phones to detect malware applications.

Keywords- Keylogger, Black-box, malware, machine learning, Smartphone, spyware.

Unique Identification Number - IJEDRCP1403011
Page Number(s) - 53-59
Pubished in - Volume 2 | Issue NCETSE Conference | March 2014
DOI (Digital Object Identifier) -   
Publisher - IJEDR (ISSN - 2321-9939)

  S.Vinoth kumar,  Aruna sankaralingam,   "Mobile keylogger detection using machine learning", International Journal of Engineering Development and Research (IJEDR), ISSN:2321-9939, Volume.2, Issue NCETSE Conference, pp.53-59, March 2014, Available at :http://www.ijedr.org/papers/IJEDRCP1403011.pdf