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Design of Cyber Attack Precursor Symptom Detection Algorithm through System Base Behavior Analysis and Memory Monitoring.

Authors :
Jung, Sungmo
Kim, Jong hyun
Cagalaban, Giovanni
Lim, Ji-hoon
Kim, Seoksoo
Source :
Communication & Networking: International Conference, Fgcn 2010, Held as Part of the Future Generation Information Technology Conference, Fgit 2010, Jeju Island, Korea, December 13-15, 2010. Proceedings, Part II; 2010, p276-283, 8p
Publication Year :
2010

Abstract

More recently, botnet-based cyber attacks, including a spam mail or a DDos attack, have sharply increased, which poses a fatal threat to Internet services. At present, antivirus businesses make it top priority to detect malicious code in the shortest time possible (Lv.2), based on the graph showing a relation between spread of malicious code and time, which allows them to detect after malicious code occurs. Despite early detection, however, it is not possible to prevent malicious code from occurring. Thus, we have developed an algorithm that can detect precursor symptoms at Lv.1 to prevent a cyber attack using an evasion method of `an executing environment aware attack΄ by analyzing system behaviors and monitoring memory. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISBNs :
9783642176036
Database :
Complementary Index
Journal :
Communication & Networking: International Conference, Fgcn 2010, Held as Part of the Future Generation Information Technology Conference, Fgit 2010, Jeju Island, Korea, December 13-15, 2010. Proceedings, Part II
Publication Type :
Book
Accession number :
76882074
Full Text :
https://doi.org/10.1007/978-3-642-17604-3_33