کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
566870 | 1452083 | 2013 | 6 صفحه PDF | دانلود رایگان |
Being a vital element for the different domains such as communication system, authentication, and payment, multiple attackers manipulate the Card fraudulently in order to access to the services offered by this one. Smartcards are often the target of software and hardware attacks. The most recent attacks are based on fault injection which modifies the application behavior. By disrupting the Java Card operation, the fault attack modifies the compiled code intended to be executed in order to meet what the attacker wants instead of the initial program. So, to tackle this problem, we suggest two classification and detection methods based on artificial intelligence, especially the neural and Bayesian networks. Then, we compare between the obtained results of these two methods in terms of the detection rate.
Journal: AASRI Procedia - Volume 4, 2013, Pages 132-137