publication . Conference object . 2011

Detecting Scareware by Mining Variable Length Instruction Sequences

Shahzad, Raja Khurram; Lavesson, Niklas;
Open Access English
  • Published: 01 Jan 2011
  • Publisher: Johannesburg : IEEE Press
Abstract
Scareware is a recent type of malicious software that may pose financial and privacy-related threats to novice users. Traditional countermeasures, such as anti-virus software, require regular updates and often lack the capability of detecting novel (unseen) instances. This paper presents a scareware detection method that is based on the application of machine learning algorithms to learn patterns in extracted variable length opcode sequences derived from instruction sequences of binary files. The patterns are then used to classify software as legitimate or scareware but they may also reveal interpretable behavior that is unique to either type of software. We hav...
Subjects
free text keywords: Computer Sciences, Datavetenskap (datalogi), Instruction Sequences, Scareware, Classification
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publication . Conference object . 2011

Detecting Scareware by Mining Variable Length Instruction Sequences

Shahzad, Raja Khurram; Lavesson, Niklas;