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Internet worm is a self-propagating and fast spreading attack which has affected the Internet dramatically in the last few years.
Finite state automata malware code#
Internet worm is a malicious code or program that exploits security holes and enters into the network without human interference. With rapid development, today the Internet has become more vulnerable to various threats and attacks such as intrusions, worms, viruses, spyware, and Trojans. Experimental results show that the proposed approach provides better time consumption and memory utilization during detection of Internet worm attacks. DDC achieves decoding latency during compression of payload packets in the network. Delayed Dictionary Compression (DDC) is applied for achieving better speeds in the communication links. In order to reduce memory utilization, decompression technique is used.
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DFA requires more memory space for each state. DFA achieves better processing speed during regular expression matching. Then the grouping scheme for regular expression matching is rewritten using Deterministic Finite Automaton (DFA). In this paper, the regular expressions that are basically string patterns are analyzed for packet payloads in detecting worms. During network transfer, incoming and outgoing packets are monitored in depth to inspect the packet payload. 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. Packet content scanning is one of the crucial threats to network security and network monitoring applications.