چكيده به لاتين
Abstract:
The number of malware which is most communicative networks challenge increases quickly. These malicious programs effect on systems based on their roguish aims. Worms are a type of malware which spread through emails, p2p, Internet automatically. Various distribution behaviors of worms help us to classify them. To classify worms, both benign and malicious programs are executed within a sandbox to screen API calls. Therefore, we analyze the sequence of extracted API calls to derive propagation features. Also, a set of features is provided by Apriori algorithm. Further, random forest algorithm classified worms based on both feature sets and worms are classified with an accuracy 100%.
Keywords: Worms, Worm Detection, Classification, Data mining, Decision tree
