The detection of malware analysis environments has become popular and commoditized. Detection techniques previously reserved for more sophisticated forms of malware are now available to any novice cyber criminal. The use of next-generation virtualizationbased malware analysis technologies considerably reduces the number of possible transparency shortcomings, but still fails to handle pathologic...

Traditional antivirus software relies on signatures to uniquely identify malicious files. Malware writers, on the other hand, have responded by developing obfuscation techniques with the goal of evading content-based detection. A consequence of this arms race is that numerous new malware instances are generated every day, thus limiting the effectiveness of static detection approaches. For effec...

Nowadays, malicious URLs are the common threat to the businesses, social networks, net-banking etc. Existing approaches have focused on binary detection i.e. either the URL is malicious or benign. Very few literature is found which focused on the detection of malicious URLs and their attack types. Hence, it becomes necessary to know the attack type and adopt an effective countermeasure. This pa...

In recent years, email is the basic service for person to person communication, and email facilitates by its high speed, and process ability. The email malware exhibits two new propagation features; reinfection and self-start. Reinfection is the process by which an infected user sends out malware copies, whenever the infected user opens the malicious hyperlink or attachment. Self-Start is the p...

With explosive growth in the number of mobile devices, the mobile malware is rapidly spreading as well, and the number of encountered malware families is increasing. Existing solutions, which are mainly based on one malware detector running on the phone or in the cloud, are no longer effective. Main problem lies in the fact that it might be impossible to create a unique mobile malware detector ...

With explosive growth in the number of mobile devices, the mobile malware is rapidly spreading as well, and the number of encountered malware families is increasing. Existing solutions, which are mainly based on one malware detector running on the phone or in the cloud, are no longer effective. Main problem lies in the fact that it might be impossible to create a unique mobile malware detector ...

Malware or malicious code intends to harm computer systems without the knowledge of system users. These malicious softwares are unknowingly installed by naive users while browsing the Internet. Once installed, the malware performs unintentional activities like (a) steal username, password; (b) install spy software to provide remote access to the attackers; (c) flood spam messages; (d) perform d...

To understand completely the malicious intents of a zero-day malware there is really no automated way. There is no single best approach for malware analysis so it demands to combine existing static, dynamic and manual malware analysis techniques in a single unit. In this paper a hybrid real-time analysis and reporting system is presented. The proposed system integrates various malware analysis ...

Nowadays, malware has become a critical security threat. Traditional antiviruses such as signature-based techniques and code emulation become insufficient and easy to get around. Thus, it is important to have efficient and robust malware detectors. In [23,21], CTL model-checking for PushDown Systems (PDSs) was shown to be a robust technique for malware detection. However, the approach of [23,21...

Malicious software (‘malware’) detection systems are usually signature-based and cannot stop attacks by malicious files they have never encountered. To stop these attacks, we need statistical learning approaches to identify root patterns behind execution of malware. We propose a machine learning approach for detection of malware from portable executable (PE) files. We create an ‘entropy time se...