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Internet has played a vital role in this modern world, the
possibilities and opportunities offered are limitless. Despite all
the hype, Internet services are liable to intrusion attack that
could tamper the confidentiality and integrity of important
information. An attack started with gathering the information
of the attack target, this gathering of information activity can
be done as either fast or slow attack. The defensive measure
network administrator can take to overcome this liability is by
introducing Intrusion Detection Systems (IDSs) in their
network. IDS have the capabilities to analyze the network
traffic and recognize incoming and on-going intrusion.
Unfortunately the combination of both modules in real time
network traffic slowed down the detection process. In real time
network, early detection of fast attack can prevent any further
attack and reduce the unauthorized access on the targeted
machine. The suitable set of feature selection and the correct
threshold value, add an extra advantage for IDS to detect
anomalies in the network. Therefore this paper discusses a new
technique for selecting static threshold value from a minimum
standard features in detecting fast attack from the victim
perspective. In order to increase the confidence of the
threshold value the result is verified using Statistical Process
Control (SPC). The implementation of this approach shows
that the threshold selected is suitable for identifying the fast
attack in real tim
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