Malicious code refers to a broad category of software threats to your network and systems. Perhaps the most sophisticated types of threats to computer systems are presented by malicious codes that exploit vulnerabilities in computer systems. Any code which modifies or destroys data, steals data , allows unauthorized access Exploits or damage a system, and does something that user did not intend...

Computer security addresses the problem of enforcement of security policies in the presence of malicious users and software. Systems enforcing mandatory policies can create confinement domains that limit the damage incurred by malicious software executing in applications. To achieve assurance that the confinement domains cannot be breached, the underlying enforcement mechanism must be construct...

Malicious code is a way of attempting to acquire sensitive information by sending malicious code to the trustworthy entity in an electronic communication. JavaScript is the most frequently used command language in the web page environment. If the hackers misuse the JavaScript code there is a possibility of stealing the authentication and confidential information about an organization and user. ...

A recent line of work has explored the use of physically uncloneable functions (PUFs) for secure computation, with the goals of (1) achieving universal composability without additional setup, and/or (2) obtaining unconditional security (i.e., avoiding complexity-theoretic assumptions). Initial work assumed that all PUFs, even those created by an attacker, are honestly generated. Subsequently, r...

Signature-based anti-viruses are very accurate, but are limited in detecting new malicious code. Dozens of new malicious codes are created every day, and the rate is expected to increase in coming years. To extend the generalization to detect unknown malicious code, heuristic methods are used; however, these are not successful enough. Recently, classification algorithms were used successfully f...

To detect malicious executables, often spread as email attachments, two types of algorithms are usually applied under instance-based statistical learning paradigms: 1) Signature-based template matching, which finds unique tell-tale characteristics of a malicious executable and thus is capable of matching those with known signatures; 2) Two-class supervised learning, which determines a set of fe...