Measuring the Histogram Feature Vector for Anomaly Network Traffic
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Recent works have shown that Internet traffics are self- similar over several time scales from microseconds to minutes. On the other hand, the dramatic expansion of Internet applications give rise to a fundamental challenge to the network security. This paper presents a statistical analysis of the Internet traffic Histogram Feature Vector, which can be applied to detect the traffic anomalies. Besides, the Variant Packet Sending-interval Link Padding based on heavy-tail distribution is proposed to defend the traffic analysis attacks in the low or medium speed anonymity system.
KeywordsPareto Distribution Link Group Constant Length Tail Index Heavy Tail Distribution
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