Modelling attacks and challenges to wireless networks

Due to the tremendous potential of MANETs (mobile ad hoc networks) for deployment in commercial and military services, a thorough understanding of network behaviour when exposed to challenges is essential for constructing a resilient and survivable MANET. Therefore, it is vital to have a comprehensive framework that can model it under various network attacks and challenges. The MANET environment has a dynamic and intermittent connectivity resulting from channel fading and mobility of the nodes, which makes it difficult to model the network as well as its challenges. We provide a model to simulate malicious and area-based challenges to wireless networks. In the modelling of malicious attacks, we treat MANETs as time-varying graphs (TVGs) represented as a weighted adjacency matrix, in which the weights refer to the link availability. We evaluate the relations between node significance and weighted centrality metrics. Area-based challenges representative of real-world scenarios are also modelled. Our ultimate goal is to provide a comprehensive network challenge model of MANETs and also heterogeneous networks.

[1]  John Skvoretz,et al.  Node centrality in weighted networks: Generalizing degree and shortest paths , 2010, Soc. Networks.

[2]  L. Freeman Centrality in social networks conceptual clarification , 1978 .

[3]  A. Lee Swindlehurst,et al.  Improving the topological resilience of mobile ad hoc networks , 2009, 2009 7th International Workshop on Design of Reliable Communication Networks.

[4]  Cory Beard,et al.  Evaluating geographic vulnerabilities in networks , 2011, 2011 IEEE International Workshop Technical Committee on Communications Quality and Reliability (CQR).

[5]  David A. Maltz,et al.  A performance comparison of multi-hop wireless ad hoc network routing protocols , 1998, MobiCom '98.

[6]  George F. Riley,et al.  The ns-3 Network Simulator , 2010, Modeling and Tools for Network Simulation.

[7]  Nicola Santoro,et al.  Time-varying graphs and dynamic networks , 2010, Int. J. Parallel Emergent Distributed Syst..

[8]  James P. G. Sterbenz,et al.  Modelling communication network challenges for Future Internet resilience, survivability, and disruption tolerance: a simulation-based approach , 2013, Telecommun. Syst..

[9]  David Levin,et al.  Survivable mobile wireless networks: issues, challenges, and research directions , 2002, WiSE '02.

[10]  James P. G. Sterbenz,et al.  Modelling wireless challenges , 2012, Mobicom '12.

[11]  Tracy Camp,et al.  MANET simulation studies: the incredibles , 2005, MOCO.

[12]  Piet Van Mieghem,et al.  Connectivity in Wireless Ad-hoc Networks with a Log-normal Radio Model , 2006, Mob. Networks Appl..

[13]  Christian Bettstetter,et al.  On the Connectivity of Ad Hoc Networks , 2004, Comput. J..

[14]  M. Newman,et al.  Scientific collaboration networks. II. Shortest paths, weighted networks, and centrality. , 2001, Physical review. E, Statistical, nonlinear, and soft matter physics.

[15]  David Hutchison,et al.  Resilience and survivability in communication networks: Strategies, principles, and survey of disciplines , 2010, Comput. Networks.

[16]  Afonso Ferreira,et al.  Building a reference combinatorial model for MANETs , 2004, IEEE Network.

[17]  Zygmunt J. Haas,et al.  Predictive distance-based mobility management for PCS networks , 1999, IEEE INFOCOM '99. Conference on Computer Communications. Proceedings. Eighteenth Annual Joint Conference of the IEEE Computer and Communications Societies. The Future is Now (Cat. No.99CH36320).

[18]  Mads Haahr,et al.  Social Network Analysis for Information Flow in Disconnected Delay-Tolerant MANETs , 2009, IEEE Transactions on Mobile Computing.

[19]  Victor S. Frost,et al.  Performance Comparison of Weather Disruption-Tolerant Cross-Layer Routing Algorithms , 2009, IEEE INFOCOM 2009.

[20]  M. Salazar-Palma,et al.  A survey of various propagation models for mobile communication , 2003 .

[21]  Ioannis Chatzigiannakis,et al.  Modeling and evaluation of the effect of obstacles on the performance of wireless sensor networks , 2006, 39th Annual Simulation Symposium (ANSS'06).

[22]  James P. G. Sterbenz,et al.  A comprehensive framework to simulate network attacks and challenges , 2010, International Congress on Ultra Modern Telecommunications and Control Systems.

[23]  Robert J Hermann,et al.  Report of the Commission to Assess the Threat to the United States from Electromagnetic Pulse (EMP) Attack: Critical National Infrastructures , 2008 .

[24]  Ioannis Stavrakakis,et al.  How much off-center are centrality metrics for routing in opportunistic networks , 2011, CHANTS '11.

[25]  Ioannis Chatzigiannakis,et al.  TRAILS, a Toolkit for Efficient, Realistic and Evolving Models of Mobility, Faults and Obstacles in Wireless Networks , 2008, 41st Annual Simulation Symposium (anss-41 2008).