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In this paper, we introduce a new form of behavioral biometrics based on mouse dynamics, which can be used in different security applications. We develop a technique that can be used to model the behavioral characteristics from the captured data using artificial neural networks. In addition, we present an architecture and implementation for the detector,(More)
Botnets have become one of the major threats on the Internet for serving as a vector for carrying attacks against organizations and committing cybercrimes. They are used to generate spam, carry out DDOS attacks and click-fraud, and steal sensitive information. In this paper, we propose a new approach for characterizing and detecting botnets using network(More)
In this work we introduce the idea of using behavioral biometrics in intrusion detection applications. We propose a new approach to user profiling, which can be used to detect intrusion without the need for any special hardware implementation and without forcing the user to perform any special actions. The technique is based on using "keystroke dynamics"(More)
How to find and detect novel or unknown network attacks is one of the most important objectives in current intrusion detection systems. In this paper, a rule evolution approach based on Genetic Programming (GP) for detecting novel attacks on networks is presented and four genetic operators, namely reproduction, mutation, crossover, and dropping condition(More)
In this paper we introduce the idea of using behavioral biometrics in intrusion detection applications. We present a new biometrics-based technique, which can be used to detect intrusion without the need for any special hardware implementation and without forcing the user to perform any special actions. The technique is based on using " keystroke dynamics "(More)
Existing risk-based authentication systems rely on basic web communication information such as the source IP address or the velocity of transactions performed by a specific account, or originating from a certain IP address. Such information can easily be spoofed, and as such, put in question the robustness and reliability of the proposed systems. In this(More)
Digital fingerprinting is an important but still challenging aspect of network forensics. This paper introduces an effective way to identify an attacker based on a strong behavioral biometric. We introduce a new passive digital fingerprinting technique based on keystroke dynamics biometrics. The technique is based on free text detection and analysis of(More)
Botnets are becoming the predominant threat on the Internet today and is the primary vector for carrying out attacks against organizations and individuals. Botnets have been used in a variety of cybercrime, from click-fraud to DDOS attacks to the generation of spam. In this paper we propose an approach to detect botnet activity by classifying network(More)