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Identifying instances of network attacks by comparing current activity against the expected actions of an intruder has become an important. Most current approaches to misuse detection involve the use of rule-based expert systems to identify indications of known attacks. Artificial neural networks provide the potential to identify and classify network activity based on limited, incomplete, and nonlinear data sources. Transmission of data over the internet keeps on increasing, which needs to protect connected systems also increasing. Intrusion Detection Systems (IDSs) are the latest technology used for this purpose.
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