With the sharp increase in the number of smartphones, the Android platform pose to becoming a market leader that makes the need for malware analysis on this platform an urgent issue. The current Artificial Immune-Based malware detection systems research focus on traditional computers that uses information from OS or network, but the smartphone software behavior has its own structure and semanti...

Signature-based malware detection is a very fundamental technique that detects malware by generating signatures. The detection however, is unable to detect obfuscated malware unless pre-generated signature is stored in the database. In this paper, we propose a combination of known packer detection, unpacking module, and heuristic scanning techniques to find and block a malicious program before ...

Mobile malware has been growing in scale and complexity as smartphone usage continues to rise. Android has surpassed other mobile platforms as the most popular whilst also witnessing a dramatic increase in malware targeting the platform. A worrying trend that is emerging is the increasing sophistication of Android malware to evade detection by traditional signature-based scanners. As such, Andr...

Android is currently the most popular smartphone operating system. However, users feel their private information at threat, facing a rapidly increasing number of malware for Android which significantly exceeds that of other platforms. Antivirus software promises to effectively protect against malware on mobile devices and many products are available for free or at reasonable prices. Their effec...

The word wide sharply increase in the number of smartphones user, the Android platform pose to becoming a market fugleman that makes the need for malware analysis on this platform an urgent issue. The current Artificial Immune Based malware detection systems they focus on traditional computers that uses information from OS or network, but the smartphone software behavior has its own structure a...

The aim of this article is to present an approach to develop and verify a method of formal modeling of cyber threats directed at computer systems. Moreover, the goal is to prove that the method enables one to create models resembling the behavior of malware that support the detection process of selected cyber attacks and facilitate the application of countermeasures. The most common cyber threa...

With over 50 billion downloads and more than 1.3 million apps in Google’s official market, Android has continued to gain popularity amongst smartphone users worldwide. At the same time there has been a rise in malware targeting the platform, with more recent strains employing highly sophisticated detection avoidance techniques. As traditional signature based methods become less potent in detect...

Previous work has shown that well-designed metamorphicmalware can evade many commonly-used malware detection techniques, including signature scanning. In this paper, we consider a previously developed score which is based on function call graph analysis. We test this score on challenging classes of metamorphic malware and we show that the resulting detection rates yield an improvement over othe...

Malwares are malignant software’s .It is designed to damage computer systems without the knowledge of the owner using the system. Software’s from reputable vendors also contain malicious code that affects the system or leaks information’s to remote servers.Malware’s includes computer viruses, spyware, dihonest ad-ware,rootkits,Trojans,dialers etc. The paper focuses on various Malware detection ...

144 Abstract: The malware expert system is an enhance approach for analyzing malware and other kinds of software. So, it is necessary to develop an effective malware expert system that can analyze, detect, classify and remove the malware codes. This system is necessary because it removes the errors done by human intervention in determining whether the files to be scanned contain any malicious d...