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Full Version: Host-Based Intrusion Detection Using user signatures
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ABSTRACT
Network security has been an issue almost since computers have been networked toge ther. Since the evolution of the internet, there has been an increasing need for security systems. One important type of security software that has emerged since the evolution of the internet is intrusion detection systems. An intrusion occurs when an attacker gains unauthorized access to a valid userâ„¢s account and performs disruptive behavior while masquerading as that user. The attacker may harm the userâ„¢s account directly and can use it to launch attacks on other accounts or machines. Developing signatures of users of a computer system is a useful method for detecting when this scenario happens. Our approach concentrates on developing precise user signatures characterizing multiple aspects of user activity. Thus, anytime someone behaves in a manner inconsistent with their signature, our system will raise an alarm which strength corresponds to the unlikelihood of the current behavior to the signature.
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how to create a host based intrusion detection using java programming language
An intrusion detection system (IDS) is a device or software application that monitors a network or systems for malicious activity or policy violations. Any detected activity or violation is typically reported either to an administrator or collected centrally using a security information and event management (SIEM) system. A SIEM system combines outputs from multiple sources, and uses alarm filtering techniques to distinguish malicious activity from false alarms.

There is a wide spectrum of IDS, varying from antivirus software to hierarchical systems that monitor the traffic of an entire backbone network. The most common classifications are network intrusion detection systems (NIDS) and host-based intrusion detection systems (HIDS). A system that monitors important operating system files is an example of a HIDS, while a system that analyzes incoming network traffic is an example of a NIDS. It is also possible to classify IDS by detection approach: the most well-known variants are signature-based detection (recognizing bad patterns, such as malware) and anomaly-based detection (detecting deviations from a model of "good" traffic, which often relies on machine learning). Some IDS have the ability to respond to detected intrusions. Systems with response capabilities are typically referred to as an intrusion prevention system.