The sharp increase in smartphone malware has become one of the most serious security problems. Since the Android platform has taken the dominant position in smartphone popularity, the number of Android malware has grown correspondingly and represents critical threat to the smartphone users. This rise in malware is primarily attributable to the occurrence of variants of existing malware. A set o...

Over the decades or so, Anti-Malware (AM) communities have been faced with a substantial increase in malware activity, including the development of ever-more-sophisticated methods of evading detection. Researchers have argued that an AM strategy which is successful in a given time period cannot work at a much later date due to the changes in malware design. Despite this argument, in this paper,...

A number of machine learning based malware detection systems have been suggested to replace signature based detection methods. These systems have shown that they can provide a high detection rate when recognising non-previously seen malware samples. However, in systems based on behavioural features, some new malware can go undetected as a result of changes in behaviour compared to the training ...

Assembly Code Clone Detection for Malware Binaries Mohammad Reza Farhadi Malware, such as a virus or trojan horse, refers to software designed specifically to gain unauthorized access to a computer system and perform malicious activities. To analyze a piece of malware, one may employ a reverse engineering approach to perform an in-depth analysis on the assembly code of a malware. Yet, the rever...

Today malware is a serious threat to our society. Several researchers are studying detection and mitigation of malware threats. On the other hand malware authors try to use obfuscation techniques for evading detection. Unfortunately usual approach (e.g., antivirus software) use signature based method which can easily be evaded. For addressing these shortcomings dynamic methods have been introdu...

Context Over the past decades malware authorship grew to become a profession. Nowadays, there exists a plethora of malware instances that span various targets, structures, motivations, and objectives [1]. Despite the different objectives they pursue, the majority of malware authors strive to prolong the period of time their instances remain operational within the infected system. In this contex...

The rapid growing adoption of android operating system around the world affects the growth of malware that attacks this platform. One possible solution to overcome the threat of malware is building a comprehensive system to detect existing malware. This paper proposes multilayer perceptron artificial neural network trained with backpropagation algorithm to determine an application is malware or...

Malware analysis and detection has become a prime research area in the case of smartphones, particularly based on android due to its widespread usage and increase in the number of malwares involving huge monetary gains. The exploding number of Android malware calls for automated analysis of the systems. There are two common techniques used for detecting malware, signature based and behaviour ba...

Recently, Android malicious code has increased dramatically and the technology of reinforcement is increasingly powerful. Due to the development of code obfuscation and polymorphic deformation technology, the current Android malicious code static detection method whose feature selected is the semantic of application source code can not completely extract malware’s code features. The Android mal...