Pattern matching is a fundamental approach to detect malicious behaviors and information over Internet, which has been gradually used in high-speed network traffic analysis. However, there is a performance bottleneck ...Pattern matching is a fundamental approach to detect malicious behaviors and information over Internet, which has been gradually used in high-speed network traffic analysis. However, there is a performance bottleneck for multi-pattern matching on online compressed network traffic(CNT), this is because malicious and intrusion codes are often embedded into compressed network traffic. In this paper, we propose an online fast and multi-pattern matching algorithm on compressed network traffic(FMMCN). FMMCN employs two types of jumping, i.e. jumping during sliding window and a string jump scanning strategy to skip unnecessary compressed bytes. Moreover, FMMCN has the ability to efficiently process multiple large volume of networks such as HTTP traffic, vehicles traffic, and other Internet-based services. The experimental results show that FMMCN can ignore more than 89.5% of bytes, and its maximum speed reaches 176.470MB/s in a midrange switches device, which is faster than the current fastest algorithm ACCH by almost 73.15 MB/s.展开更多
In network environments,before meaningful interactions can begin,trust may need to be established between two interactive entities in which an entity may ask the other to provide some information involving privacy.Con...In network environments,before meaningful interactions can begin,trust may need to be established between two interactive entities in which an entity may ask the other to provide some information involving privacy.Consequently,privacy protection and trust establishment become important in network interactions.In order to protect privacy while facilitating effective interactions,we propose a trust-based privacy protection method.Our main contributions in this paper are as follows:(1)We introduce a novel concept of k-sensitive privacy as a measure to assess the potential threat of inferring privacy;(2)According to trust and k-sensitive privacy evaluation,our proposed method can choose appropriate interaction patterns with lower degree of inferring privacy threat;(3)By considering interaction patterns for privacy protection,our proposed method can overcome the shortcomings of some current privacy protection methods which may result in low interaction success rate.Simulation results show that our method can achieve effective interactions with less privacy loss.展开更多
基金supported by China MOST project (No.2012BAH46B04)
文摘Pattern matching is a fundamental approach to detect malicious behaviors and information over Internet, which has been gradually used in high-speed network traffic analysis. However, there is a performance bottleneck for multi-pattern matching on online compressed network traffic(CNT), this is because malicious and intrusion codes are often embedded into compressed network traffic. In this paper, we propose an online fast and multi-pattern matching algorithm on compressed network traffic(FMMCN). FMMCN employs two types of jumping, i.e. jumping during sliding window and a string jump scanning strategy to skip unnecessary compressed bytes. Moreover, FMMCN has the ability to efficiently process multiple large volume of networks such as HTTP traffic, vehicles traffic, and other Internet-based services. The experimental results show that FMMCN can ignore more than 89.5% of bytes, and its maximum speed reaches 176.470MB/s in a midrange switches device, which is faster than the current fastest algorithm ACCH by almost 73.15 MB/s.
基金research funding from the Beijing Education Commission under Grant No. KM201010005027National Natural Science Foundation of China under Grant No. 61074128National Social Science Foundation of China under Grant No. 07CTQ010
文摘In network environments,before meaningful interactions can begin,trust may need to be established between two interactive entities in which an entity may ask the other to provide some information involving privacy.Consequently,privacy protection and trust establishment become important in network interactions.In order to protect privacy while facilitating effective interactions,we propose a trust-based privacy protection method.Our main contributions in this paper are as follows:(1)We introduce a novel concept of k-sensitive privacy as a measure to assess the potential threat of inferring privacy;(2)According to trust and k-sensitive privacy evaluation,our proposed method can choose appropriate interaction patterns with lower degree of inferring privacy threat;(3)By considering interaction patterns for privacy protection,our proposed method can overcome the shortcomings of some current privacy protection methods which may result in low interaction success rate.Simulation results show that our method can achieve effective interactions with less privacy loss.
