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Distributed Denial of Service (DDoS) attacks are a serious threat to network security. Servers of many companies and/or governments have been victims of such attacks. DDoS attacks jam the network service of the target using multiple bots hijacked by crackers and send numerous packets to the target server. In such an attack, detecting the crackers is extremely difficult, because they only send a command...
Distributed denial of service (DDoS) attacks is one of the major threats to the current Internet. After analyzing the characteristics of DDoS attacks and the existing approaches to detect DDoS attacks, a novel detection method based on conditional entropy is proposed in this paper. First, a group of statistical features based on conditional entropy is defined, which is named Traffic Feature Conditional...
Along with the rapid popularity of the Internet, crime information on the web is becoming increasingly rampant, and the majority of them are in the form of text. Because a lot of crime information in documents is described through events, event-based semantic technology can be used to study the patterns and trends of web-oriented crimes. In our research project on cyber crime mining, we construct...
Recently, DoS (Denial of Service) detection has become more and more important in web security. In this paper, we argue that DoS attack can be taken as continuous data streams, and thus can be detected by using stream data mining methods. More specifically, we propose a new Weighted Ensemble learning model to detect the DoS attacks. The Weighted Ensemble model first trains base classifiers using different...
Distributed denial-of-service (DDoS) attacks present serious threats to servers in the Internet. We argue that the difference of the goals, manners and results of the interaction behaviors of normal flows and attack flows, which show different characteristics on IP addresses and ports. IAI (IP Address Interaction Feature) algorithm is proposed based on the addresses interaction, abrupt traffic change,...
Phishing continue to be one of the most drastic attacks causing both financial institutions and customers huge monetary losses. Nowadays mobile devices are widely used to access the Internet and therefore access financial and confidential data. However, unlike PCs and wired devices, such devices lack basic defensive applications to protect against various types of attacks. In consequence, phishing...
As fake Website developers become more innovative, so too must the tools used to protect Internet users. A proposed system combines a support vector machine classifier and a rich feature set derived from Website text, linkage, and images to better detect fraudulent sites.
Research work related to plagiarism detection methods in dealing with monolingual texts (e.g. English texts) have been well established in recent years. However, little attention has been paid to facilitate plagiarism detection in cross-lingual text collections (e.g. English and Chinese texts). In this paper we present a system platform to evaluating text similarity and relatedness in multilingual...
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