DEFECT: discover and eradicate fool around node in emergency network using combinatorial techniques
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ORIGINAL RESEARCH
DEFECT: discover and eradicate fool around node in emergency network using combinatorial techniques S. Arun1 · K. Sudharson2 Received: 2 March 2020 / Accepted: 9 October 2020 © Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract Mining the frequent pattern deals with the finding patterns in large set of data, subsequences and substructures that occur in a database frequently. Likewise, We can use Frequent pattern mining for MANET nodes in order to identify the paths which are participated in frequent data transaction among the various Mobile adhoc network nodes. The network data stream is a long and continuous sequence of data sets transmitted over the network. The OCA (Online Combinatorial Approximation) algorithm is used in the data stream for mining online data. The processing time of OCA was much less and accuracy of its approximate result was quite high like other traditional mining methods. The Data Path Combinatorial Approximation (DPCA) algorithm deals with a frequent pathset mining over the MANET data flow. The pathset is generation of path from the set of paths on any node which are provided paths to various other nodes participating in the data transmission. The mining algorithm is based on Approximate Inclusion–Exclusion technique. Without continual path scanning, approximate counts are calculated for the pathsets. Skip and complete technique and group count technique were combined together and integrated into the DPCA algorithm to improve the MANET performance in terms of identifying fool around (misbehaving) nodes. Keywords Data mining · Data path · Frequent nodesets · Combinatorial approximation
1 Introduction Ad hoc networks are essentially peer-to-peer mobile wireless networks where information packets are transmitted from source to arbitrary destination through intermediate nodes in a "store-and-forward" mechanism (Nivedita and Nandhagopal 2020). Ad hoc environments are secured via two ways. The primary way for securing an ad hoc network is by implementing a secure routing protocol which ensures the secure transmission by taking care of the mandatory security requirements. The other approach is to design and implement an intrusion detection system that detects and circumvents the nodes inducing malevolent behavior in the network. This paper focuses a viable solution to node packet forwarding misbehavior attack. It uses a non-cryptographic technique * S. Arun [email protected] K. Sudharson [email protected] 1
Prathyusha Engineering College, Chennai, India
Velammal Institute of Technology, Chennai, India
2
to secure MANETs against packet forwarding misbehavior attack by jointly employing both the data mining and clustering (Kukreja et al. 2018). A node that experienced any attack in mobile ad-hoc environments exhibits an anomalous or fraudulent activity. A mobile node is considered to be a fraudulent node, if and only if it has one or more of the following features: bandwidth consumption, message tampering, session recording, battery drained,
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