Mohammad Salim Ahmed

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Evaluation of network security is an essential step in securing any network. This evaluation can help security professionals in making optimal decisions about how to design security countermeasures, to choose between alternative security architectures, and to systematically modify security configurations in order to improve security. However, the security(More)
In order to create secure and dependable systems and information intelligence, it is a major challenge to determine the security level of the network. This security level depends on a number of dynamically changing factors including emerging of new vulnerabilities and threats, policy updates and network traffic. An effective means to address this is to(More)
Text classification poses some specific challenges. One such challenge is its high dimensionality where each document (data point) contains only a small subset of them. In this paper, we propose Semi-supervised Impurity based Subspace Clustering (SISC) in conjunction with k-Nearest Neighbor approach, based on semi-supervised subspace clustering that(More)
Network security depends on a number of factors. And a common characteristic of these factors is that they are dynamic in nature. Such factors include new vulnerabilities and threats, the network policy structure and traffic. These factors can be divided into two broad categories. Network risk and service risk. As the name implies, the former one(More)
Security of a network depends on a number of dynamically changing factors. These include emergence of new vulnerabilities and threats, policy structure and network traffic. Due to the dynamic nature of these factors, identifying security metrics that measure objectively the quality of security configuration pose a major challenge. Moreover, this evaluation(More)
There has been a lot of research targeting text classification. Many of them focus on a particular characteristic of text data multi-labelity. This arises due to the fact that a document may be associated with multiple classes at the same time. The consequence of such a characteristic is the low performance of traditional binary or multi-class(More)
With the boom of web and social networking, the amount of generated text data has increased enormously. Much of this data can be considered and modeled as a stream and the volume of such data necessitates the application of automated text classification strategies. Although streaming data classification is not new, considering text data streams for(More)
We propose a data intensive and distributed multichunk ensemble classifier based data mining technique to classify data streams. In our approach, we combine r most recent consecutive data chunks with data chunks in the current ensemble and generate a new ensemble using this data for training. By introducing this multi-chunk ensemble technique in a(More)
The factors on which security depends are of dynamic nature. These include emergence of new vulnerabilities and threats, policy structure and network traffic. Due to the dynamic nature of these factors, objectively identifying and measuring security metrics is a major challenge. However, such an evaluation can significantly help security professionals in(More)
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