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Web attacks that exploit vulnerabilities of web applications are still major problems. The number of attacks that maliciously manipulate parameters of web applications such as SQL injections and command injections is increasing nowadays. Anomaly detection is effective for detecting these attacks, particularly in the case of unknown attacks. However, existing anomaly detection methods often raise false...
During the last decade, various machine learning and data mining techniques have been applied to Intrusion Detection Systems (IDSs) which have played an important role in defending critical computer systems and networks from cyber attacks. Unsupervised anomaly detection techniques have received a particularly great amount of attention because they enable construction of intrusion detection models...
Intrusion Detection Systems (IDSs) play an important role detecting various kinds of attacks and defend our computer systems from them. There are basically two main types of detection techniques: signature-based and anomaly-based. A signature-based IDS cannot detect unknown attacks because a signature has not been written. To overcome this shortcoming, many researchers have been developing anomaly-based...
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