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DAWA: Defending against wormhole attack in MANETs by using fuzzy logic and artificial immune system

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Abstract

Mobile ad hoc networks (MANETs) are mobile networks, which are automatically outspread on a geographically limited region, without requiring any preexisting infrastructure. Mostly, nodes are both self-governed and self-organized without requiring a central monitoring. Because of their distributed characteristic, MANETs are vulnerable to a particular routing misbehavior, called wormhole attack. In wormhole attack, one attacker node tunnels packet from its position to the other attacker nodes. Such wormhole attack results in a fake route with fewer hop count. If source node selects this fictitious route, attacker nodes have the options of delivering the packets or dropping them. For this reason, this paper proposes an improvement over AODV routing protocol to design a wormhole-immune routing protocol. The proposed protocol called defending against wormhole attack (DAWA) employs fuzzy logic system and artificial immune system to defend against wormhole attacks. DAWA is evaluated through extensive simulations in the NS-2 environment. The results show that DAWA outperforms other existing solutions in terms of false negative ratio, false positive ratio, detection ratio, packet delivery ratio, packets loss ratio and packets drop ratio.

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References

  1. Van G, Greeven MJ (2016) Mobile telecommunication standardization in Japan, China, the United States, and Europe: a comparison of regulatory and industrial regimes. Telecommunication Systems, p 1–12. doi:10.1007/s11235-016-0214-y

  2. Bricha N, Nourelfath M (2014) Extra-capacity versus protection for supply networks under attack. Reliab Eng Syst Saf 131:185–196

    Article  Google Scholar 

  3. Fotohi R, Ebazadeh Y, Geshlag MS (2016) A new approach for improvement security against DoS attacks in vehicular ad-hoc network. Int J Adv Comput Sci Appl 7:10–16

    Google Scholar 

  4. Fotohi R, Jamali SHA (2014) comprehensive study on defence against wormhole attack methods in mobile Ad hoc Networks. Int J Comput Sci Netw Solut 2:37–56

    Google Scholar 

  5. Adewole KS, Anuar NB, Kamsin A, Varathan KD, Razak SA (2016) Malicious accounts: dark of the social networks. J Netw Comput Appl 79:41–67

    Article  Google Scholar 

  6. Rana AI, Jennings B (2016) Semantic aware processing of user defined inference rules to manage home networks. J Netw Comput Appl 79:68–87

  7. Vatn J, Aven T (2010) An approach to maintenance optimization where safety issues are important. Reliab Eng Syst Saf 95(1):58–63

    Article  Google Scholar 

  8. Fotohi R, Heydari R, Jamali SH (2016) A Hybrid routing method for mobile ad-hoc networks. J Adv Comput Res 7(3):93–103

    Google Scholar 

  9. Fotohi Reza et al (2013b) An Improvement over AODV routing protocol by limiting visited hop count. Int J Inf Technol Comput Sci (IJITCS) 5(9):87

    Google Scholar 

  10. Jamali SH, Fotohi R (2016) Defending against wormhole attack in MANET using an artificial immune system. New Rev Inf Netw 21(2):1–22. doi:10.1080/13614576.2016.1247741

    Google Scholar 

  11. Jamali SH, Shaker V (2014) Defense against SYN flooding attacks: a particle swarm optimization approach. Comput Electr Eng 40(6):2013–2025

    Article  Google Scholar 

  12. Maulik R, Chaki N, A comprehensive review on wormhole attacks in MANET. In: 2010 International Conference on Computer Information Systems and Industrial Management Applications (CISIM), IEEE, 1010, pp 233–238

  13. Fotohi R, Jamali SH, Sarkohaki F (2013a) Performance evaluation of AODV, LHC-AODV, OLSR, UL-OLSR, DSDV routing protocols. Int J Inf Technol Comput Sci (IJITCS) 5(10):21

    Google Scholar 

  14. Drozda M, Schaust S, Szczerbicka H (2007) AIS for misbehavior detection in wireless sensor networks: performance and design principles. In: 2007 IEEE Congress on Evolutionary Computation, IEEE, pp 3719–3726

  15. Farmer JD, Packard NH, Perelson AS (1986) The immune system, adaptation, and machine learning. Phys D: Nonlinear Phenom 22(1):187–204

    Article  MathSciNet  Google Scholar 

  16. Perelson AS (1989) Immune network theory. Immunol Rev 110(1):5–36. doi:10.1111/j.1600-065X.1989.tb00025.x

    Article  Google Scholar 

  17. Varela F, Coutinho A, Dupire B, Nelson N (1988) Cognitive networks: immune, neural and otherwise. In: Perelson AS (ed) Theoretical immunology, part two. SFI studies in the sciences of complexity, vol 3. Addison-Wesley, MA, pp 377–401

  18. Shen J, Wang J, Ai H (2012) An improved artificial immune system-based network intrusion detection by using rough set. Commun Netw 4(1):41–47. doi:10.4236/cn.2012.41006

    Article  Google Scholar 

  19. Zadeh LA (1965) Fuzzy sets. Inf Control 8(3):338–353

    Article  MATH  Google Scholar 

  20. Teotia V, Dhurandher SK, Woungang I, Obaidat MS (2015) Wormhole prevention using COTA mechanism in position based environment over MANETs. In: 2015 IEEE International Conference on Communications (ICC), IEEE, pp 7036–7040

  21. Lu X, Dong D, Liao X (2013) WormPlanar: Topological planarization based wormhole detection in wireless networks. In: 2013 42nd International Conference on Parallel Processing, IEEE, pp 498–503

  22. Amish P, Vaghela VB (2016) Detection and prevention of wormhole attack in wireless sensor network using AOMDV protocol. 7th International Conference on Communication, Elsevier, pp 700–707

  23. Raju VK, Kumar KV (2012) A simple and efficient mechanism to detect and avoid wormhole attacks in mobile ad hoc networks. In: 2012 International Conference on Computing Sciences (ICCS), IEEE, pp 271–275

  24. Patel A, Patel N, Patel R (2015). Defending against wormhole attack in MANET. In: 2015 Fifth International Conference on Communication Systems and Network Technologies (CSNT), IEEE, pp 674–678

  25. Ji S, Chen T, Zhong S, Kak S (2014) Dawn: defending against wormhole attacks in wireless network coding systems. In: 2014 IEEE Conference on Computer Communications, IEEE INFOCOM, IEEE, pp 664–672

  26. Patidar K, Dubey V (2014) Modification in routing mechanism of AODV for defending black hole and wormhole attacks. In: 2014 Conference on IT in Business, Industry and Government (CSIBIG), IEEE, pp 1–6

  27. Tan Z (2012) An efficient identity-based tripartite authenticated key agreement protocol. Electron Commer Res 12(4):505–518. doi:10.1007/s10660-012-9103-y

    Article  Google Scholar 

  28. Petrova K, Wang B (2011) Location-based services deployment, and demand: a roadmap model. Electron Commer Res 11(1):5–29. doi:10.1007/s10660-010-9068-7

    Article  Google Scholar 

  29. Aloudat A, Michael K (2011) Toward the regulation of ubiquitous mobile government: a case study on location-based emergency services in Australia. Electron Commer Res 11(1):31–74. doi:10.1007/s10660-010-9070-0

    Article  Google Scholar 

  30. Zhou T (2013) An empirical examination of user adoption of location-based services. Electron Commer Res 13(1):25–39. doi:10.1007/s10660-013-9106-3

    Article  Google Scholar 

  31. Chiu HS, Lui KS (2006) Delphi: wormhole detection mechanism for ad hoc wireless networks. In: 2006 1st International Symposium on Wireless Pervasive Computing, IEEE, p 6

  32. Qian L, Song N, Li X (2005) Detecting and locating wormhole attacks in wireless ad hoc networks through statistical analysis of multi-path. In: IEEE Wireless Communications and Networking Conference, IEEE, vol 4. pp 2106–2111

  33. Su MY (2010) WARP: a wormhole-avoidance routing protocol by anomaly detection in mobile ad hoc networks. Comput Secur 29(2):208–224. doi:10.1016/j.cose.2009.09.005

    Article  Google Scholar 

  34. Su X, Boppana RV (2007) On mitigating in-band wormhole attacks in mobile ad hoc networks. In: 2007 IEEE International Conference on Communications, IEEE, pp 1136–1141

  35. Hu YC, Johnson DB, Perrig A (2003) SEAD: Secure efficient distance vector routing for mobile wireless ad hoc networks. Ad hoc Netw 1(1):175–192. doi:10.1016/S1570-8705(03)00019-2

    Article  Google Scholar 

  36. Maulik R, Chaki N, A comprehensive review on wormhole attacks in MANET. In: 2010 International Conference on Computer Information Systems and Industrial Management Applications (CISIM), IEEE, 1010, pp 233–238

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Authors and Affiliations

  1. Computer Engineering Department, University of Mohaghegh Ardabili, Ardabil, Iran

    Shahram Jamali

  2. Department of Computer Engineering Germi Branch, Islamic Azad University, Germi, Iran

    Reza Fotohi

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  1. Shahram Jamali
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  2. Reza Fotohi
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Correspondence to Shahram Jamali or Reza Fotohi.

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Shahram Jamali and Reza Fotohi declare that they have no conflict of interest.

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This paper does not contain any studies with human participants by any of the authors.

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Jamali, S., Fotohi, R. DAWA: Defending against wormhole attack in MANETs by using fuzzy logic and artificial immune system. J Supercomput 73, 5173–5196 (2017). https://doi.org/10.1007/s11227-017-2075-x

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  • DOI: https://doi.org/10.1007/s11227-017-2075-x

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