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With an enormous increase in number of mobile users, mobile threats are also growing rapidly. Mobile malwares can lead to several cybersecurity threats i.e. stealing sensitive information, installing backdoors, ransomware attacks and sending premium SMSs etc. Previous studies have shown that due to the sophistication of threats and tailored techniques to avoid detection, not every antivirus system...
In this study, we apply an anomaly-based approach to analyze traffic flows transferred over a network to detect the flows related to different types of attacks. Based on the information extracted from network flows a model of normal user behavior is discovered with the help of several clustering techniques. This model is then used to detect anomalies within recent time intervals. Since this approach...
The most traditional technique for Network Intrusion Detection Systems (NIDSs) is misuse detection which only detects well-known attacks by matching the current behavior of network with pre-defined attacks' signatures. Providing attacks' signatures is costly, time consuming and with the explosive growing number of zero day attacks, using misuse detection mechanism is not an efficient solution. Other...
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