Identification and isolation of malicious nodes in a distributed system is a challenging problem. This problem is further aggravated in a wireless network because the unreliable channel hides the actions of each node from one another. Therefore, a regular node can only construct a belief about a malicious node through monitoring and observation. In this paper, we use game theory to study the in...

Client-side attacks have become an increasing problem on the Internet today. Malicious web pages launch so-called drive-by-download attacks that are capable to gain complete control of a user’s machine by merely having that user visit a malicious web page. Criminals that are behind the majority of these malicious web pages are highly sensitive to location, language and economic trends to increa...

Detecting unknown malicious executables is a challenging task. Traditional anti-virus systems use signatures to detect malicious executables. However, the method cannot detect unseen instances or variants. Inspired by biological immune systems, an immune-based approach for detection of unknown malicious executables is proposed in this paper, which is referred to MEDMI. The approach can use the ...

Though many techniques for finding malicious code have been developed, we found few publicized techniques for creating and hiding malicious code. Traditional malicious code examples include viruses, trojans, and worms, but we define malicious code to be any code that does not behave as the user intended. Our goal is to analyze current methods for the creation and hiding of malicious code and to...

Collaborative spectral sensing can fuse the perceived results of multiple cognitive users, and thus will improve the accuracy of perceived results. However, the multi-source features of the perceived results result in security problems in the system. When there is a high probability of a malicious user attack, the traditional algorithm can correctly identify the malicious users. However, when t...

General image classification approaches differentiate classes using strong distinguishing features but some classes cannot be easily separated because they contain very similar visual features. To deal with this problem, we can use keywords relevant to a particular class. To implement this concept we have newly constructed a malicious crowd dataset which contains crowd images with two events, b...