![]() ![]() In this paper, we present several anti‐phishing methods with their pros and cons. In addition, we propose an intelligent anti‐phishing solution named Password‐Transaction Secure Window (PTSW) in order to secure users and their personal information. The PTSW is a cheap and efficient solution against password and transaction attacks. ![]() Traffic classification has a vital role in tasks as wide ranging as trend analyses, adaptive network‐based QoS marking of traffic, dynamic access control and lawful interception. The identification of network applications through observation of associated packet traffic flows is vital to the areas of network management and surveillance. An important role of this work is to show the need for thorough comparisons between the plethora of proposed solutions in traffic classification and packet detections. Certainly there are other learning algorithms, other features, other performance measures, different approaches to traffic classification and packet detection, in general more research have been done, and within the same lane, we propose a novel strategy called 'separator'. This paper is an attempt to create discussion and inspire future research in this direction. The method proposed is theoretically proved to have tight error bound and small space usage. We then show that it is useful to differentiate algorithms based on computational performance rather than classification accuracy alone, as although classification accuracy between the algorithms is similar, computational performance can differ significantly. Comprehensive experiments conducted also verify our mechanism accuracy and efficiency. Unauthorised accesses into computers are serious cyber warfare across the globe. Consequently, an intrusion detector is used for network forensics to maximally detect and report intrusions. ![]() The toolkit is generally designed to log tons of unauthorised activities with their respective attributes to assist in‐depth analyses of the events. Unfortunately, there are several ways to cluster intrusive alerts. ![]()
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