Malware is one of the most serious security threats on the Internet today. In fact, most Internet problems such as spam e-mails and denial of service attacks have malware as their underlying cause. That is, computers that are compromised with malware are often networked together to form botnets, and many attacks are launched using these malicious, attacker-controlled networks. With the increasi...

Malware stands for malicious software. It is software that is designed with a harmful intent. A malware detector is a system that attempts to identify malware using Application Programming Interface (API) call graph technique and/or other techniques. Matching the API call graph using graph matching algorithm have NP-complete problem and is slow because of computational complexity .In this study...

Machine Learning-based malware detection is a promising scalable method for identifying suspicious applications. In particular, in today’s mobile computing realm where thousands of applications are daily poured into markets, such a technique could be valuable to guarantee a strong filtering of malicious apps. The success of machine-learning approaches however is highly dependent on (1) the qual...

Various dynamic approaches have been developed to detect or categorize Android malware. These approaches execute software, collect call traces, and then detect abnormal system calls or sensitive API usage. Consequently, attackers can evade these approaches by intentionally obfuscating those calls under focus. Additionally, existing approaches treat detection and categorization of malware as sep...

Security for the Common Man (SCM) is a new approach for detecting hidden malware by identifying a legitimate reason for outbound traffic. This method is combined with an interface that encourages user involvement. Users know what they were doing online and when they were doing it. We believe this knowledge can improve automated detection systems. SCM identifies legitimate outbound sessions by e...

A malware is a program that has a malicious intent. Nowadays, attack from malwares is rising in alarming fashion and thousands of malwares are injected to the Internet. Malware authors use many techniques like obfuscation and packing to avoid detection. A number of techniques for malware detection are available and none of them able to detect all types of malwares. In this paper, a more efficie...

A malware is a program that has a malicious intent. Nowadays, attack from malwares is rising in alarming fashion and thousands of malwares are injected to the Internet. Malware authors use many techniques like obfuscation and packing to avoid detection. A number of techniques for malware detection are available and none of them able to detect all types of malwares. In this paper, a more efficie...

Sophisticated!malware,!such!as!those!used!by!Advanced!Persistent!Threat!(APT)! groups,!will!attempt!to!avoid!detection!wherever!and!whenever!it!can.!However,! even!the!stealthiest!malware!will!have!to!communicate!at!some!point,!and!when!it! does!so,!it!provides!an!opportunity!for!detection.!This!paper!looks!at!a!number!of! techniques!to!identify!the!presence!of!malware!which!attempts!to!masquer...

The underground malware-based economy is flourishing and it is evident that the classical ad-hoc signature detection methods are becoming insufficient. Malware authors seem to share some source code and malware samples often feature similar behaviors, but such commonalities are difficult to detect with signature-based methods because of an increasing use of numerous freelyavailable randomized o...

Combating malware is very important for software/systems security, but to prevent the software/systems from the advanced malware, viz. metamorphic malware is a challenging task, as it changes the structure/code after each infection. Therefore in this paper, we present a novel approach to detect the advanced malware with high accuracy by analyzing the occurrence of opcodes (features) by grouping...