In this paper, we develop a decision-theoretic frameworkfor evaluating data mining systems, which employ classification methods, in terms of their utility in decision-making. The decision-theoretic model provides an economic perspective on the value of â extracted knowledge,â in terms of its...

Machine learning techniques are widely used in many fields. One of the applications of machine learning in the field of information security is classification of a computer behavior into malicious and benign. Antiviruses consisting of signature-based methods are helpless against new (unknown)...

Detection of malicious software (malware) using machine learning methods has been explored extensively to enable fast detection of new released malware. The performance of these classifiers depends on the induction algorithms being used. In order to benefit from multiple different classifiers,...

Purpose – The purpose of this paper is to prove the ability of PRivAte Web (PRAW) – a system for private web browsing – to stand possible attacks. Design/methodology/approach – Attacks on the systems were simulated, manipulating systems variables. A privacy measure was defined to...

Purpose – The purpose of this paper is to present an extension to a framework based on the information structure (IS) model for combining information filtering (IF) results. The main goal of the framework is to combine the results of the different IF systems so as to maximise the expected...