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Computers and Smartphone's becomes vital part of everyday life and hence use of internet becomes more and more. Due to internet, computers are becomes vulnerable of different kinds of security threats. Therefore it is required that we need to have efficient security method in order to avoid leakage of important data or misuse of data. This security method is called as Intrusion Detection System (IDS)...
Modern Internet applications rely on rich multimedia contents making the quality of experience (QoE) of end users sensitive to network conditions. Several models were developed in the literature to express QoE as a function of measurements carried out on the traffic of the applications themselves. In this paper, we propose a new methodology based on machine learning able to link expected QoE to network...
With the increasing risk of data leakage, information guards have emerged as a novel concept in the field of security which bears similarity to spam filter that examine the content of the exchanged messages. A guard is defined as a high-assurance device used to control the information flow, typically from a domain with a "high" level of confidentiality, such as a corporate or military network,...
Wikipedia, a collaborative and user driven encyclopedia is considered to be the largest content thesaurus on the web, expanding into a massive database housing a huge amount of information. In this paper, we present the design and implementation of a MapReduce-based Wikipedia link analysis system that provides a hierarchical examination of document connectivity in Wikipedia and captures the semantic...
With the acceleration of the Internet speed and the vigorous emergence of new applications, the amount of Internet traffic has increased. In order to provide stable Internet service, efficient network management based on accurate traffic identification is critical. Although various methods for traffic identification have been proposed, not a single method identifies all types of Internet traffic....
After lung cancer, breast cancer is known to be the greatest cause for death among females [20]. The improving effectiveness of machine learning approaches is being given a lot of importance by medical practitioners for breast cancer diagnosis. The paper proposes an effective hybridized classifier for breast cancer diagnosis. The classifier is made by combining an unsupervised artificial neural network...
Conventional dimensionality reduction methods are not applicable for hybrid data as they require the data set to be pure numerical. In this study, the mutual information (MI)-based unsupervised feature transformation (UFT) method which can transform symbolic features into numerical features without information loss was integrated with principle component analysis (PCA) for dimensionality reduction...
To alleviate the loads of tracking web log file by human effort, machine learning methods are now commonly used to analyze log data and to identify the pattern of malicious activities. Traditional kernel based techniques, like the neural network and the support vector machine (SVM), typically can deliver higher prediction accuracy. However, the user of a kernel based techniques normally cannot get...
AS-level end-to-end paths are of great value for ISPs and a variety of network applications. Although tools like traceroute may reveal AS paths, they require the permission to access source hosts and introduce additional probing traffic, which is not feasible in many applications. In contrast, AS path inference based on BGP control plane data and AS relationship information is a more practical and...
Recently, data on the internet grows and it can be used as supporting information for human life. Wikipedia as an online encyclopedia provides many resources, data, and information on the internet. Main problem in our research is how to represent information from Indonesian Wikipedia article into some knowledge representation such as ontology. Ontology is a set of related concept and relation between...
Cross-language text similarity calculation is a critical and fundamental problem in natural language processing. It is widely used in cross-language research, such as cross-language information retrieval. In this paper, we used the LDA (Latent Dirichlet Allocation) model to calculate similarities of Tibetan and Chinese texts at the topic level. Through topic modelling and forecasting, the texts are...
The ever increasing traffic demands and the current trend of network and services virtualization calls for effective approaches for optimal use of network resources. In the future Internet multiple virtual networks will coexist on top of the same physical infrastructure, and these will compete for bandwidth resources. Link dimensioning can support fair share and allocation of bandwidth. Current approaches...
In this paper, we consider multi-sensor classification when there is a large number of unlabeled samples. The problem is formulated under the multi-view learning framework and a Consensus-based Multi-View Maximum Entropy Discrimination (CMV-MED) algorithm is proposed. By iteratively maximizing the stochastic agreement between multiple classifiers on the unlabeled dataset, the algorithm simultaneously...
Traffic matrix estimation in communication networks is challenging problem, whose solution provides a valuable management and planning tool. Given the range of technologies able to reconfigure the resource assignment, real-time knowledge of the traffic matrix enables smart adaptive traffic management functions. A new perspective is given to the traffic matrix estimation problem by the Software Defined...
Since extremely powerful technologies are now available to generate and process digital images, there is a concomitant need for developing techniques to distinguish the original images from the altered ones, the genuine ones from the doctored ones. In this paper we focus on this problem and propose a method based on the neighbor bit planes of the image. The basic idea is that, the correlation between...
Distributed Denial of Service (DDoS) attacks pose a serious threat to efficient and uninterrupted Internet services. During Distributed Denial of Service (DDoS), attackers make fool of innocent servers (i.e., Slave) into reddening packets to the victim. Most low-rate DDoS attack detection mechanisms are associated with specific protocols used by the attacks. Due to the use of slave, it has been found...
The online retail industry is one of the world's largest and fastest growing industries having huge amount of online sales data. This sales data includes information about customer buying history, goods or services offered for the customers. Hidden relationships in sales data can be discovered from the application of data mining techniques. Data mining is an inter disciplinary promising field that...
Content delivery services over the Internet are increasingly attractive to users and widely used. Internet users now can play many kinds of content and new content items are continually created. As users interest has changed to content delivery communication from inter-user communication, Content-Centric Networking (CCN) [1], which is designed for content delivery services, has attracted much attention.
The rising of the modern Internet brought with it heap opportunities for attackers to gain illegal benefit from spreading spam mail. Spam is irrelevant or inappropriate messages sent on the Internet to a large number of recipients. Many researchers use a large number of classification method in machine learning to filter spam messages. But, there is still limited research which evaluate the use of...
Changes in the network topology such as large-scale power outages or Internet worm attacks are events that may induce routing information updates. Border Gateway Protocol (BGP) is by Autonomous Systems (ASes) to address these changes. Network reachability information, contained in BGP update messages, is stored in the Routing Information Base (RIB). Recent BGP anomaly detection systems employ machine...
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