Title
Fine-Grained Analysis of Packet Loss in MANETs.
Abstract
Most existing trust-based security schemes for mobile ad-hoc networks (MANETs) consider packet loss an indicator of possible attacks by malicious nodes. There may be several reasons for packet losses, such as interference, queue overflow, and node mobility. Identifying the real underlying cause of a packet loss event is important for any security solution. To detect truly malicious nodes, it is necessary to carry out a fine-grained analysis (FGA) to determine the underlying cause of such loss. Without such analysis, the performance of any security solution may degrade, due to the punishment of innocent nodes while actual malicious nodes may remain undetected. Therefore, approaches are required that can correctly identify the reason for packet losses and can react accordingly. In this paper, we present a scheme that is able to correctly identify malicious nodes, using network parameters to determine whether packet losses are due to queue overflows or node mobility in MANETs. The contributions of this paper include the FGA scheme for packet loss and the development of a comprehensive trust model for malicious node identification and isolation. Our proposed FGA scheme is evaluated in terms of effectiveness and performance metrics under different network parameters and configurations. The experimental results show that our proposed trust model achieves a significant reduction in false positives rate and an increase in the rate of detection of truly malicious nodes compared with traditional non-FGA schemes.
Year
DOI
Venue
2017
10.1109/ACCESS.2017.2694467
IEEE ACCESS
Keywords
Field
DocType
Trust,MANETs,misbehaving,fine-grained analysis,mobility,queue overflow,congestion
Mobile computing,Computer science,Queue,Network packet,Computer network,Packet loss,Interference (wave propagation),Wireless ad hoc network,Routing protocol,Distributed computing,False positive paradox
Journal
Volume
ISSN
Citations 
5
2169-3536
2
PageRank 
References 
Authors
0.37
22
4
Name
Order
Citations
PageRank
Muhammad Saleem Khan184.20
Daniele Midi2799.79
Majid Iqbal Khan39511.44
Elisa Bertino4140252128.50