Akademik Veri Yönetim Sistemi
18th European Conference on the Applications of Evolutionary Computation, EvoApplications 2015, Copenhagen, Danimarka, 8 - 10 Nisan 2015, cilt.9028, ss.745-756
© Springer International Publishing Switzerland 2015.The number of mobile devices has increased dramatically in the past few years. These smart devices provide many useful functionalities accessible from anywhere at anytime, such as reading and writing e-mails, surfing on the Internet, showing facilities nearby, and the like. Hence, they become an inevitable part of our daily lives. However the popularity and adoption of mobile devices also attract virus writers in order to harm our devices. So, many security companies have already proposed new solutions in order to protect our mobile devices from such malicious attempts. However developing methodologies that detect unknown malwares is a research challenge, especially on devices with limited resources. This study presents a method that evolves automatically variants of malwares from the ones in the wild by using genetic programming (GP). We aim to evaluate the efficacy of current anti-virus products, using static analysis techniques, in the market.The experimental results showtheweaknesses of the static analysis tools available in the market, and the need of new detection techniques suitable for mobile devices.