Title :
A self learning model for detecting SIP malformed message attacks
Author :
Aziz, Sohail ; Gul, Mehroz
Author_Institution :
Comput. Sci. Dept., Nat. Univ. of Comput. & Emerging Sci., Islamabad, Pakistan
Abstract :
This paper analyses the vulnerabilities exist in SIP protocol, and how these vulnerabilities can be exploited by attackers to attack the SIP based networks i.e VoIP and IMS [IP Multimedia Subsystem]. An attack tool is developed to exploit those vulnerabilities and a two-gram self learning solution is proposed to protect SIP based networks from these attacks.
Keywords :
Internet telephony; multimedia systems; protocols; unsupervised learning; IMS; IP multimedia subsystem; SIP protocol; VoIP; self learning model; Computer crashes; IP networks; Multimedia communication; SIP attack; SIP fuzzing; SIP malformed messages; malformed message detection; self learning; two-gram detection model;
Conference_Titel :
Broadband Network and Multimedia Technology (IC-BNMT), 2010 3rd IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-6769-3
DOI :
10.1109/ICBNMT.2010.5705189
