Dynamic Adaptive Anti-Jamming via Mobility Control

In this work, the mobility of network nodes is explored as a ne w promising approach for jamming defense. To fulfill it, properly designed node motion that can intelligently adapt to the jammer’s action is crucial. In our study, anti-jammin g mobility control is investigated in the context of the single and mult iple commodity flow problems, in the presence of one intellig nt mobile jammer which can respond to the evasion of legitimate nodes as well. Based on spectral graph theory, two new spectr al quantities, singleand multi-weighted Cheeger constants d corresponding eigenvalue variants, are constructed to direct motions of the defender and the attacker in this dynamic adaptive com petition. Both analytical and simulation results are prese nted to justify the effectiveness of the proposed approach. I. I NTRODUCTION Due to the broadcast nature of radio propagation, wireless c ommunications are highly susceptible to jamming attacks. V arious types of anti-jamming strategies have been proposed in lite rature, ranging from stochastic matching (e.g., [1]), codi ng (e.g., [2]), directive antenna and beamforming (e.g., [3]), to spr ead spectrum (SS) techniques including frequency hopping ( FH) and direct-sequence (DS) [4]. More recent advances in this area include the uncoordinated spread spectrum techniques such as UFH [5, 6] and UDSSS [7] for insider jamming defense, the USDFH scheme [8] for jamming-resilient key establishment, the RD-DSSS scheme [9] and the DSD-DSSS scheme [10] for efficient k yless anti-jamming broadcast communications, and the techniques of creating covert and low data rate channels to d efen strong and reactive jammers [11, 12]. In wireless netw orks, multinode diversity has been exploited in [13] to develop CU FH, a collaborative anti-jamming technique, and spatial di versity has been exploited in [14] to design jamming-resilient geog raphic routing. 2 Recently, node mobility adds another new ingredient to the j amming/anti-jamming game. Spatial retreat was considered in [15, 16] for jamming avoidance. Based on some inspiring heur istics and a simulation study, node mobility is investigate d in [17] for both the adversarial network and the legitimate net work, which can reconfigure their geometries in response to t he opponent’s action so as to adaptively improve attack impact and protocol performance, respectively. Motivated by the p ioneering works in this direction, we intend to further explore anti-j amming techniques through mobility control, based on a more s lid theoretical foundation that can provide certain performan ce assurance. In this aspect, fruitful results and analytic l ools from spectral graph theory [18], which nicely relate network per formance metrics to the spectral properties of the network g raph, provide a promising design basis for mobility and topology c ontrol with global performance assurance. In our study, we consider an intelligent jammer that can resp ond to the evasion of legitimate nodes, and view the interact ion between the two parties as a dynamic adaptive game. In the fac e of such intelligent mobile jammers, the legitimate nodes continuously reconfigure their geographic locations to rec ov r the network performance, while presenting the adversa ry a dynamic and unpredictable attack surface. Our approach con forms to the newly advocated moving target defense (MTD) principle [19], which indicates that the ability of dynamic adaptation is crucial to the success in the security contest . This principle has already been exemplified in the cyber domain an d the spectrum domain. Cyber MTD approaches include softwar e transformation, server diversification, IP evolution and k ey maneuvering [19]. In the spectrum domain, legitimate tra nsceivers and the jammer can learn the opponent’s action pattern and ma ke their own channel hopping decisions adaptively [20–22]. In this sense, anti-jamming via controlled mobility provides a new avenue to instantiate the MTD principle. In this work, the single and multiple commodity flow problems in the presence of mobile relays and one intelligent mobile jammer is considered, which find wide applications in mobile ad hoc networks and robotic sensor networks. The dynamic adaptive competition between relays and the jammer evolves as follows: legitimate relay nodes masterly move based on th e jammer’s current position to protect the flows among all sour ce-destination (S-D) pairs, while the jammer strives in opp osition and adaptively moves to new advantageous positions so as to d egrade the achievable network flows. For these two problems, new spectral quantities, singleand multi-weighted Cheeg er constants and corresponding eigenvalue variants, are co nstructed. Relays and the jammer compete effectively by directing thei r motions according to these spectral quantities of the netw ork graph. Both analytical results and simulations are present d to demonstrate the effectiveness of our approaches. The rest of this paper is organized as follows. Section II des cribes the general problem setting and notations. The singl e and the multiple commodity flow problems under jamming are treat ed in Section III and IV, respectively. Numerical results ar e presented in Section V. Conclusions and future work are give n in Section VI. 3 II. PROBLEM FORMULATION AND NOTATIONS −1 0 1 2 3 4 0 0.2 0.4 0.6 0.8 1

[1]  Patrick Tague,et al.  Improving anti-jamming capability and increasing jamming impact with mobility control , 2010, The 7th IEEE International Conference on Mobile Ad-hoc and Sensor Systems (IEEE MASS 2010).

[2]  D. R. Fulkerson,et al.  Maximal Flow Through a Network , 1956 .

[3]  K. J. Ray Liu,et al.  An anti-jamming stochastic game for cognitive radio networks , 2011, IEEE Journal on Selected Areas in Communications.

[4]  Tamer Basar,et al.  Graph-theoretic approach for connectivity maintenance in mobile networks in the presence of a jammer , 2010, 49th IEEE Conference on Decision and Control (CDC).

[5]  Guosen Yue,et al.  Anti-jamming coding techniques with application to cognitive radio , 2009, IEEE Transactions on Wireless Communications.

[6]  Wenyuan Xu,et al.  Exploiting Jamming-Caused Neighbor Changes for Jammer Localization , 2012, IEEE Transactions on Parallel and Distributed Systems.

[7]  Sushil Jajodia,et al.  Moving Target Defense II , 2013, Advances in Information Security.

[8]  Srdjan Capkun,et al.  Jamming-resistant Broadcast Communication without Shared Keys , 2009, USENIX Security Symposium.

[9]  Wade Trappe,et al.  Managing the Mobility of a Mobile Sensor Network Using Network Dynamics , 2008, IEEE Transactions on Parallel and Distributed Systems.

[10]  Scott D. Coutts Passive localization of moving emitters using out-of-plane multipath , 2000, IEEE Trans. Aerosp. Electron. Syst..

[11]  Frank Thomson Leighton,et al.  Multicommodity max-flow min-cut theorems and their use in designing approximation algorithms , 1999, JACM.

[12]  Abbas Jamalipour,et al.  Wireless communications , 2005, GLOBECOM '05. IEEE Global Telecommunications Conference, 2005..

[13]  Franz S. Hover,et al.  Laplacians for flow networks , 2011, SIAM J. Discret. Math..

[14]  Srikanth V. Krishnamurthy,et al.  Lightweight Jammer Localization in Wireless Networks: System Design and Implementation , 2009, GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference.

[15]  U. Feige,et al.  Spectral Graph Theory , 2015 .

[16]  Peng Ning,et al.  BitTrickle: Defending against broadband and high-power reactive jamming attacks , 2012, 2012 Proceedings IEEE INFOCOM.

[17]  Jonah Sherman,et al.  Breaking the Multicommodity Flow Barrier for O(vlog n)-Approximations to Sparsest Cut , 2009, 2009 50th Annual IEEE Symposium on Foundations of Computer Science.

[18]  Xiang-Yang Li,et al.  Towards Optimal Adaptive UFH-Based Anti-Jamming Wireless Communication , 2012, IEEE Journal on Selected Areas in Communications.

[19]  Devavrat Shah,et al.  Product Multicommodity Flow in Wireless Networks , 2006, IEEE Transactions on Information Theory.

[20]  Srdjan Capkun,et al.  Anti-jamming broadcast communication using uncoordinated spread spectrum techniques , 2010, IEEE Journal on Selected Areas in Communications.

[21]  Srdjan Capkun,et al.  Jamming-resistant Key Establishment using Uncoordinated Frequency Hopping , 2008, 2008 IEEE Symposium on Security and Privacy (sp 2008).

[22]  David Kempe,et al.  A decentralized algorithm for spectral analysis , 2008, J. Comput. Syst. Sci..

[23]  J. A. Tomlin,et al.  Minimum-Cost Multicommodity Network Flows , 1966, Oper. Res..

[24]  Ruey-Wen Liu,et al.  Anti-jamming filtering in the autocorrelation domain , 2004, IEEE Signal Processing Letters.

[25]  Peng Ning,et al.  Defending DSSS-based broadcast communication against insider jammers via delayed seed-disclosure , 2010, ACSAC '10.

[26]  Wenyuan Xu,et al.  Channel surfing and spatial retreats: defenses against wireless denial of service , 2004, WiSe '04.

[27]  Peng Ning,et al.  Communication Efficiency of Anti-Jamming Broadcast in Large-Scale Multi-Channel Wireless Networks , 2012, IEEE Transactions on Signal Processing.

[28]  Zhu Han,et al.  Dogfight in Spectrum: Jamming and Anti-Jamming in Multichannel Cognitive Radio Systems , 2009, GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference.

[29]  Charalampos Konstantopoulos,et al.  A survey on jamming attacks and countermeasures in WSNs , 2009, IEEE Communications Surveys & Tutorials.

[30]  Rudra Dutta,et al.  A routing approach to jamming mitigation in wireless multihop networks , 2011, 2011 18th IEEE Workshop on Local & Metropolitan Area Networks (LANMAN).

[31]  Jochen Könemann,et al.  Faster and simpler algorithms for multicommodity flow and other fractional packing problems , 1998, Proceedings 39th Annual Symposium on Foundations of Computer Science (Cat. No.98CB36280).

[32]  Peng Ning,et al.  USD-FH: Jamming-resistant wireless communication using Frequency Hopping with Uncoordinated Seed Disclosure , 2010, The 7th IEEE International Conference on Mobile Ad-hoc and Sensor Systems (IEEE MASS 2010).

[33]  D. West Introduction to Graph Theory , 1995 .

[34]  Peng Ning,et al.  Randomized Differential DSSS: Jamming-Resistant Wireless Broadcast Communication , 2010, 2010 Proceedings IEEE INFOCOM.

[35]  Wenyuan Xu,et al.  Anti-jamming timing channels for wireless networks , 2008, WiSec '08.