Mohammed A. Ambusaidi

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Redundant and irrelevant features in data have caused a long-term problem in network traffic classification. These features not only slow down the process of classification but also prevent a classifier from making accurate decisions, especially when coping with big data. In this paper, we propose a mutual information based algorithm that analytically(More)
Intrusion Detection Systems (IDSs) play a significant role in monitoring and analyzing daily activities occurring in computer systems to detect occurrences of security threats. However, the routinely produced analytical data from computer networks are usually of very huge in size. This creates a major challenge to IDSs, which need to examine all features in(More)
This paper considers the feature selection problem for data classification in the absence of data labels. Due to the lack of categorized information in many practical applications, unsupervised feature selection has been proven to be more practically important but at the same time more difficult. It is not an easy task to assess the relevance of a feature(More)
Cyber crimes and malicious network activities have posed serious threats to the entire internet and its users. This issue is becoming more critical, as network-based services, are more widespread and closely related to our daily life. Thus, it has raised a serious concern in individual internet users, industry and research community. A significant amount of(More)
Internet is playing major and key role in our daily life especially in business, from two decades. The domain name / internet website address is very important and plays major role in the current IT trend based life style. The business people, consumers prefer same domain name as their trade name, even the famous people like their names as the address of(More)
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