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Journal of Computer Networks and Communications
Article . 2014 . Peer-reviewed
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Packet Payload Monitoring for Internet Worm Content Detection Using Deterministic Finite Automaton with Delayed Dictionary Compression

Authors: Divya Selvaraj; Ganapathi Padmavathi;

Packet Payload Monitoring for Internet Worm Content Detection Using Deterministic Finite Automaton with Delayed Dictionary Compression

Abstract

Packet content scanning is one of the crucial threats to network security and network monitoring applications. In monitoring applications, payload of packets in a network is matched against the set of patterns in order to detect attacks like worms, viruses, and protocol definitions. During network transfer, incoming and outgoing packets are monitored in depth to inspect the packet payload. In this paper, the regular expressions that are basically string patterns are analyzed for packet payloads in detecting worms. Then the grouping scheme for regular expression matching is rewritten using Deterministic Finite Automaton (DFA). DFA achieves better processing speed during regular expression matching. DFA requires more memory space for each state. In order to reduce memory utilization, decompression technique is used. Delayed Dictionary Compression (DDC) is applied for achieving better speeds in the communication links. DDC achieves decoding latency during compression of payload packets in the network. Experimental results show that the proposed approach provides better time consumption and memory utilization during detection of Internet worm attacks.

Keywords

Electronic computers. Computer science, QA75.5-76.95

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Average
Average
Average
gold