Using a Subtractive Center Behavioral Model to Detect Malware

Table 3

Summary of related works on malware detection methods.

Paper	Feature representation	Goal/success	Year
Wagener et al. [14]	System calls, Hellinger distance, phylogenetic tree	Identify new and different forms of malware	2008
Park et al. [15]	Creating system call diagrams	Identify different forms of malware	2013
Islam et al. [16]	Printable strings, API method frequencies	Identify malware with 97% accuracy	2013
Naval et al. [17]	Diagram of system calls and relations	Detect code insertion attacks	2015
Das et al. [18]	System call frequencies, n-gram	Identify new and different forms of malware	2016
Zhang et al. [19]	API calls sequence to construct a behavior chain	It achieved 98.64% accuracy with 2% FPR	2019