DocumentCode
2397696
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
fYear
2010
fDate
26-28 Oct. 2010
Firstpage
744
Lastpage
749
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;
fLanguage
English
Publisher
ieee
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
Type
conf
DOI
10.1109/ICBNMT.2010.5705189
Filename
5705189
Link To Document