As computer technology is becoming necessity in our day to day life in various aspects like education, communication, banking etc., computer system’s security becomes the main concern nowadays. Malware is getting its roots strong due to this emerging growth of high speed internet, so detection and removal of these malware in an effective manner is very essential. Malware detectors are the tools...

The sophistication of modern computer malware demands run-time malware detection strategies which are not only efficient but also robust to obfuscation and evasion attempts. In this paper, we investigate the suitability of recently proposed Dendritic Cell Algorithms (DCA), both classical DCA (cDCA) and deterministic DCA (dDCA), for malware detection at run-time. We have collected API call trace...

Machine Learning (ML) has found it particularly useful in malware detection. However, as the malware evolves very fast, the stability of the feature extracted from malware serves as a critical issue in malware detection. The recent success of deep learning in image recognition, natural language processing, and machine translation indicates a potential solution for stabilizing the malware detect...

Program obfuscation is increasingly popular among malware creators. Objectively comparing different malware detection approaches with respect to their resilience against obfuscation is challenging. To the best of our knowledge, there is no common empirical framework for evaluating the resilience of malware detection approaches w.r.t. behavior obfuscation. We propose and implement such a framewo...

Malware is any malicious code that has the potential to harm any computer or network. The amount of malware is increasing faster every year and poses a serious security threat. Thus, malware detection is a critical topic in computer security. Currently, signature-based detection is the most extended method for detecting malware. Although this method is still used on most popular commercial comp...

Because of the interference of obfuscation and polymorphism on malware analysis and detection, the dynamic analysis of malware binaries during run-time is becoming a research hotspot in intrusion detection field. Malware classification is a key problem in the research of dynamic malware behavior analysis. On the basis of the malware behavior monitoring result reports, after discussing of malwar...

Android malware is rapidly becoming a potential threat to users. The number of Android malware is growing exponentially; they become significantly sophisticated and cause potential financial and information losses for users. Hence, there is a need for effective and efficient techniques to detect the Android malware applications. This paper proposes an intelligent hybrid approach for Android mal...

The emergence of mobile platforms with increased storage and computing capabilities and the pervasive use of these platforms for sensitive applications such as online banking, e-commerce and the storage of sensitive information on these mobile devices have led to increasing danger associated with malware targeted at these devices. Detecting such malware presents inimitable challenges as signatu...

Android, the name is quite enough to show its dominance in the mobile computing world. Android is now the market leader among all its competitors. As, it is the largest shareholder in the market it has become bull’s eye for the attackers. Security is one of the major concerns for android users today. It has become the most viable target of security threats. With the increase in power and featur...

Malware is a found to be a big threat in computing world. It continues to grow and evolve in complexity. Modern malware hide from static and dynamic analysis tools using advanced techniques. The existing system uses classification based and regression based approach for detection. The proposed system utilizes the classification based approach and regression based approach for detection for the ...