The advent of internet protocol version 6 (IPv6) as a replacement of internet protocol version 4 (ipv4) has raised the necessity for efficient and effective malware detection techniques for IPv6 networks. Because of the evolvable and polymorphic malware, current malware detection technologies cannot cope with the exponential growth of malwares. This paper proposes a new intelligent approach bas...

Metamorphism is a technique that mutates the binary code using different obfuscations. It is difficult to write a new metamorphic malware and in general malware writers reuse old malware. To hide detection the malware writers change the obfuscations (syntax) more than the behavior (semantic) of such a new malware. On this assumption and motivation, this paper presents a new framework named MARD...

Mobile malware has been growing in scale and complexity spurred by the unabated uptake of smartphones worldwide. Android is fast becoming the most popular mobile platform resulting in sharp increase in malware targeting the platform. Additionally, Android malware is evolving rapidly to evade detection by traditional signature-based scanning. Despite current detection measures in place, timely d...

Malware detection and prevention is critical for the protection of computing systems across the Internet. The problem in detecting malware is that they evolve over a period of time and hence, traditional signature-based malware detectors fail to detect obfuscated and previously unseen malware executables. However, as malware evolves, some semantics of the original malware are preserved as these...

Malware detection is a crucial aspect of software security. Malware typically recur to a variety of disguise and concealing techniques in order to avoid detection. Metamorphism is the ability of a program to mutate its form yet keeping unchanged its functionality and therefore its danger in case of malware. A major challenge in this field is the development of general automatic/systematic detec...

In the Internet-age, malware poses a serious and evolving threat to security, making the detection of malware of utmost concern. Many research efforts have been conducted on intelligent malware detection by applying data mining and machine learning techniques. Though great results have been obtained with these methods, most of them are built on shallow learning architectures, which are still so...

Protecting the integrity of code is generally considered as one of the most effective approaches to counteract malicious software (malware). However, the fundamental problem with code-based detection approaches is that they rely on the false assumption that all malware consists of executable instructions. This makes them vulnerable to data-only malware, which, in contrast to traditional malware...

The volume and the sophistication of malware are continuously increasing and evolving. Automated dynamic malware analysis is a widely-adopted approach for detecting malicious software. However, many recent malware samples try to evade detection by identifying the presence of the analysis environment itself, and refraining from performing malicious actions. Because of the sophistication of the t...

On the Internet, malware is one of the most serious threats to system security. Most complex issues and problems on any systems are caused by malware and spam. Networks and systems can be accessed and compromised by malware known as botnets, which compromise other systems through a coordinated attack. Such malware uses anti-forensic techniques to avoid detection and investigation. To prevent sy...

The number of Android malware apps are increasing very quickly. Simply detecting and removing malware apps is insufficient, since they can damage or alter other files, data, or settings; install additional applications; etc. To determine such behavior, a security engineer can significantly benefit from identifying the specific family to which an Android malware belongs. Techniques for detecting...