چکیده مقاله
Nowadays malwares are serious threat for android systems In recent years with increasing use of Android platform on mobile devices, researchers have focused to this issue more Various techniques have been introduced for the detection of Android malwares but it seems that growth of these techniques is not comparable with malware growth rate Every day new malwares hit the Android Market that cannot be identified, and cause serious damage to the hardware and software of mobile devices The most efficient approach with minimal overhead so far, is using Support Vector Machine SVM algorithm To detect malwares by SVM method, applications are classified in two classes: malware and software This classification is done by analyzing the features of each program and specific weights which are allocated to features based on the risks that they may have In this study, a new approach for detecting android’s malwares is proposed This approach uses fuzzy systems to weight the features and it combines Support Vector Machines and Fuzzy logic Simulation results show that the proposed approach provides more efficiency and transparency than other methods
کلیدواژهها
نویسندگان
Zahra Ayoubianzadeh
Computer Engineering Department, Science and Art University, Yazd, Iran
ولی درهمی
Computer Engineering Department, Yazd University, Yazd, Iran
شیوه ارجاع
Ayoubianzadeh, Zahra and Derhami, Vali,1396,Android malware detection using combination of Support vector machines and fuzzy logic,2rd International Conference on Soft Computing,Rudsar
ارائهشده در
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