Design of cyber attack precursor symptom detection algorithm through system base behavior analysis and memory monitoring

S Jung, J Kim, G Cagalaban, J Lim, S Kim - International Conference on …, 2010 - Springer
S Jung, J Kim, G Cagalaban, J Lim, S Kim
International Conference on Future Generation Communication and Networking, 2010Springer
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 …
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.
Springer
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