Title :
A new approach for detection of insider attacks
Author_Institution :
Bilgisayar Muhendisligi Bolumu, Hacettepe Univ., Ankara, Turkey
Abstract :
Insider attacks are among the top security threats today. The basic assumption underlying detection of these attacks is that the insider attackers will deviate from the typical behavior of his victims in order to carry out his malicious activities. In this research, we propose a new approach to detect insider attacks based on this assumption as well.
Keywords :
security of data; insider attack detection; insider attackers; malicious activities; security threats; underlying detection; Computational modeling; Computer security; Conferences; Data models; Grammar; Text categorization; Naive Bayes classification; anomaly detection; insider threats;
Conference_Titel :
Signal Processing and Communications Applications Conference (SIU), 2013 21st
Conference_Location :
Haspolat
Print_ISBN :
978-1-4673-5562-9
Electronic_ISBN :
978-1-4673-5561-2
DOI :
10.1109/SIU.2013.6531506
