This study aimed to examine the pattern of alcohol use among those attending a General Hospital and to explore the perception of safe drinking. The Alcohol Use Disorders Identification Test (AUDIT) questionnaire was given for self-completion to all inpatients and outpatients on separate days and to all adults attending the Accident and Emergency Department (A&E) on both a midweek and a weekend ...

As networking and communication technology become more widespread, the quantity and impact of system attackers have been increased rapidly. The methodology of intrusion detection (IDS) is generally classified into two broad categories according to the detection approaches: misuse detection and anomaly detection. In misuse detection approach, abnormal system behavior is defined at first, and the...

The ability to detect intruders in computer systems increases in importance as computers are increasingly integrated into the systems that we rely on for the correct functioning of society. This paper reviews the history of research in intrusion detection as performed in software in the context of operating systems for a single computer, a distributed system, or a network of computers. There ar...

This paper describes design for intrusion detection that combines anomaly detection with misuse detection. The proposed method includes an ensemble feature selecting classifier and a data mining classifier. The former consists of four classifiers using different sets of features and each of them employs a machine learning algorithm named fuzzy belief k-NN classification algorithm. The latter ap...

Nowadays, many organizations use Process Aware Information Systems (PAISs) to automate their business process. As any other information systems, security plays a major role in PAIS to provide a secure state and maintain the system in it. In order to provide security in a PAIS, a Process Aware Host-based Intrusion Detection (PAHID) model is proposed in this paper. The model detects host-based in...

Anomaly detection techniques have been devised to address the limitations of misuse detection approach for intrusion detection. They can abstract information about the normal behaviors of a system and detect attacks regardless of whether or not the system has observed them before. However, they have an inherent difficulty to deal with large volume of audit data to model the normal behaviors. Ca...

The syntax of application layer protocols carries valuable information for network intrusion detection. Hence, the majority of modern IDS perform some form of protocol analysis to refine their signatures with application layer context. Protocol analysis, however, has been mainly used for misuse detection, which limits its application for the detection of unknown and novel attacks. In this contr...

Conventional Network intrusion detection system (NIDS) mostly uses individual classification techniques, such system fails to provide the best possible attack detection rate. In this paper, we propose a new two-stage hybrid classification method using Support Vector Machine (SVM) as anomaly detection in the first stage, and Artificial Neural Network (ANN) as misuse detection in the second. The ...

Problem statement: Wireless LAN IEEE 802.11 protocols are growing rapidly and security has always been a concern with the security of wired network. Wireless networks encountered threats from unauthorized access to network resources, installation of access points and illegal sniffing (refer as classical intrusion threats). In its current hybrid wired and wireless network attacks on the generall...