EAODV: detection and removal of multiple black hole attacks through sending forged packets in MANETs

Original Research
  • 20 Downloads

Abstract

Detecting and removing black hole attacks are considered to be one major routing security issue in mobile ad hoc networks (MANETs). Malicious nodes existing on the delivery route of packets change a secure route into an insecure route in these networks. Hence, rather than delivering them to the next node, the malicious nodes discard data packets. In this paper, a routing algorithm is proposed based on sending forged packets so as to enhance the accuracy of detecting and removing malicious nodes. According to the proposed method, malicious nodes in a network are detected through sending forged route request (RREQ) and route reply (RREP) routing packets which include the address of unreal destination node. Then, they are removed from routing tables of nodes via sending an RREP message. The method proposed in this paper was able to improve traffic load in the network, identify a short and secure route, detect a number of malicious nodes and optimize the criteria of packet deliver rate, throughput and routing overhead. Simulations results indicated that the percentage of the delivered data packets by the proposed algorithm is higher than that of Intrusion Detection System (IDS) algorithm. Furthermore, thanks to the accuracy improvement in detecting black hole, lack of many conditions for RREQ and RREP and quick routing detection process, the delay in the proposed method was lower than other methods. The above-mentioned factors led to the optimization of throughput.

Keywords

Mobile ad-hoc networks Black hole attack Detecting black hole attack Malicious nodes Routing protocol security AODV protocol 

References

  1. Abraham A, Grosan C, Martin-vide C (2007) “Evolutionary design of intrusion detection programs”. Network Security 4(3):328–339Google Scholar
  2. Ardakani S, Pourroostaei J, Padget, Marina De Vos (2016) “US CR” Ad Hoc Networks. Elsevier, Amsterdam.  https://doi.org/10.1016/j.adhoc.2016.05.009 Google Scholar
  3. Baadache A, Belmehdi A (2014) “Struggling against simple and cooperative black hole attacks in multi-hop wireless ad hoc networks.” Comput Netw 73:173–184.  https://doi.org/10.1016/j.comnet.2014.07.016 (Elsevier)CrossRefGoogle Scholar
  4. Bansal JC, Sharma H, Jadon SS (2013) Artificial bee colony algorithm: a survey.” Int J Adv Intell Paradig 5(1/2):123.  https://doi.org/10.1504/IJAIP.2013.054681 CrossRefGoogle Scholar
  5. Bica I, Naccache D, Simion E (2015) “Innovative security solutions for information technology and communications: 8th International Conference, SECITC 2015 Bucharest, Romania, June 11–12, 2015 Revised Selected Papers.” Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 9522:III.  https://doi.org/10.1007/978-3-319-27179-8
  6. Brajevic I (2015) “Crossover-based artificial bee colony algorithm for constrained optimization problems.” Neural Comput Appl 26 (7):1587–1601.  https://doi.org/10.1007/s00521-015-1826-y (Springer, London)CrossRefGoogle Scholar
  7. Chatterjee S, Swagatam Das (2014) “Ant colony optimization based enhanced dynamic source routing algorithm for mobile ad-hoc network.” Inf Sci.  https://doi.org/10.1016/j.ins.2014.09.039 (Elsevier)
  8. Cherkaoui B, Beni-hssane A (2017) “A clustering algorithm for detecting and handling black hole attack in vehicular ad hoc networks”. Springer, Cham, pp 481–490.  https://doi.org/10.1007/978-3-319-46568-5 Google Scholar
  9. Computing Personal Engineering Management, Kuang-fu Road, Information Technology, and Sungai Besi Camp (2012) “A novel anomaly-network intrusion detection system”. Int J Innov Comput Inf Control 8 (12):8231–8248Google Scholar
  10. Gao H, Wu R, Cao M, Zhang C (2014) “Detection and defense technology of blackhole attacks in wireless sensor network.” Lecture notes in computer science (including subseries lecture notes in artificial intelligence and lecture notes in bioinformatics) 8631 LNCS (PART 2):601–610.  https://doi.org/10.1007/978-3-319-11194-0_53
  11. Glabbeek R van, Höfner P, Portmann M, Wee Lum Tan. 2016. “Modelling and verifying the AODV routing protocol.” Distrib Comput 29 (4):279–315.  https://doi.org/10.1007/s00446-015-0262-7 (Springer, Berlin)MathSciNetCrossRefMATHGoogle Scholar
  12. Gurung S, Chauhan S (2017) “Performance analysis of black-hole attack mitigation protocols under gray-hole attacks in MANET.” Wireless Networks. Springer, Berlin.  https://doi.org/10.1007/s11276-017-1639-2 Google Scholar
  13. Hoc Ad Sensor Wireless Networks May (2016) “A novel proactive routing protocol in mobile ad hoc networks”Google Scholar
  14. Krishnamurthi M, Mohanapriya I (2014) “Trust based DSR routing protocol for mitigating cooperative black hole attacks in ad hoc networks”. Arab J Sci Eng 39: 1825–1833.  https://doi.org/10.1007/s13369-013-0764-1 CrossRefGoogle Scholar
  15. Mafra PM, Fraga JS, Santin AO (2014) Algorithms for a distributed IDS in MANETs.” J Comput Syst Sci 80(3):554–570.  https://doi.org/10.1016/j.jcss.2013.06.011 (Elsevier)CrossRefMATHGoogle Scholar
  16. Magazine Ieee Communications, Hongmei Deng, and Intelligent Automation (2002) “Routing security in wireless ad hoc networks”.  https://doi.org/10.1109/MCOM.2002.1039859
  17. Marti S, Giuli TJ, Lai K, Baker M (2000) “Mitigating routing misbehavior in mobile ad hoc networks.” In: Proceedings of the 6th annual international conference on mobile computing and networking mobicom 1(18):255–65.  https://doi.org/10.1145/345910.345955
  18. Mohanapriya M, Krishnamurthi I (2014) “Modified DSR protocol for detection and removal of selective black hole attack in MANET.” Comput Electr Eng 40(2):530–538.  https://doi.org/10.1016/j.compeleceng.2013.06.001 (Elsevier)CrossRefGoogle Scholar
  19. Nadeem A, Howarth M (2013) “Protection of MANETs from a range of attacks using an intrusion detection and prevention system.” Telecommun Syst 2047–2058.  https://doi.org/10.1007/s11235-011-9484-6
  20. Nadeem A, Howarth MP (2014) “Ad hoc networks an intrusion detection and adaptive response mechanism for MANETs.” Ad Hoc Netw 13:368–380.  https://doi.org/10.1016/j.adhoc.2013.08.017 (Elsevier)CrossRefGoogle Scholar
  21. Patwardhan A, Parker J, Iorga M, Joshi A, Karygiannis T, Yesha Y (2008) “Threshold-based intrusion detection in ad hoc networks and secure AODV”. Ad Hoc Netw 6 (4):578–599.  https://doi.org/10.1016/j.adhoc.2007.05.001.CrossRefGoogle Scholar
  22. Pietro R, Di S, Guarino NV, Verde, Domingo-ferrer J (2014) “Security in wireless ad-hoc networks—a survey.” Comput Commun 51:1–20.  https://doi.org/10.1016/j.comcom.2014.06.003 (Elsevier)CrossRefGoogle Scholar
  23. Rahman FHMA, Au TW, Black Hole Á, Ipsec, Olsr Á, Tora Á (2017) “Performance analysis of MANET under black hole attack using AODV, OLSR and TORA.”  https://doi.org/10.1007/978-3-319-48517-1
  24. Ravi G, Kashwan KR (2015) “A new routing protocol for energy efficient mobile applications for ad hoc networks Q.” Comput Electr Eng 48:77–85.  https://doi.org/10.1016/j.compeleceng.2015.03.023(Elsevier)CrossRefGoogle Scholar
  25. Salih YK, See OH, Ibrahim RW, Yussof S, Iqbal A (2014) “An overview of intelligent selection and prediction method in heterogeneous wireless networks.”  https://doi.org/10.1007/s11771-014-2286-8
  26. Sánchez-casado L, Gabriel Maciá F, Pedro García T, Roberto Magán C (2015) “A model of data forwarding in MANETs for lightweight detection of malicious packet dropping”. Comput Netw 87:44–58.  https://doi.org/10.1016/j.comnet.2015.05.012 Google Scholar
  27. Satapathy SC, Udgata SK, Biswal BN (2014) “Proceedings of the International Conference on Frontiers of Intelligent Computing: Theory and Applications (FICTA) 2013.” Adv Intell Syst Comput 247:345–352.  https://doi.org/10.1007/978-3-319-02931-3 Google Scholar
  28. Sathish M, Arumugam K, Neelavathy Pari S (2016) “Detection of single and collaborative black hole attack in MANET,”pp 2040–2044Google Scholar
  29. Sdshu, Jlyhq EO, Ydulrxv, Ghwhfwlrq E. 2016. “’ HWHFWLRQ DQG 3UHYHQWLRQ RI % ODFN + ROH $ WWDFNV LQ & OXVWHU % DVHG: LUHOHVV VHQVRU 1HWZRUNV.”pp 3399–3403Google Scholar
  30. Shahabi S, Ghazvini M, Bakhtiarian M (2016) “A modified algorithm to improve security and performance of AODV protocol against black hole attack.” Wireless Netw 22 (5):1505–1511.  https://doi.org/10.1007/s11276-015-1032-y (Springer)CrossRefGoogle Scholar
  31. Shen H, Guangwei B (2016) “A survey and challenges ahead.” J Netw Comput Appl.  https://doi.org/10.1016/j.jnca.2016.05.013 (Elsevier)Google Scholar
  32. Singh B (2016b) “Mitigating effects of black hole attack in mobile ad-hoc networks: military perspective”Google Scholar
  33. Singh B, Rahul H (2016a) “Emerging research in computing, information, communication and applications,” pp 151–161.  https://doi.org/10.1007/978-981-10-0287-8
  34. Sodiya AS (2007) Multi-level and secured agent-based intrusion detection system.” J Comput Inf Technol 14(3):217–223.  https://doi.org/10.2498/cit.2006.03.05 CrossRefGoogle Scholar
  35. Su M-Y (2011) “Prevention of selective black hole attacks on mobile ad hoc networks through intrusion detection systems.” Comput Commun 34 (1):107–117.  https://doi.org/10.1016/j.comcom.2010.08.007 (Elsevier )CrossRefGoogle Scholar
  36. Tamilselvan L, Sankaranarayanan V (2008) Prevention of co-operative black hole attack in MANET.” J Netw 3(5):13–20.  https://doi.org/10.4304/jnw.3.5.13-20 Google Scholar
  37. Thuat K, Laurent M, Nouha O (2015) “Ad hoc networks survey on secure communication protocols for the internet of things.” Ad Hoc Netw 32:17–31.  https://doi.org/10.1016/j.adhoc.2015.01.006 (Elsevier )CrossRefGoogle Scholar
  38. Tseng F-H, Chou L-D, Chao HC (2011) “A survey of black hole attacks in wireless mobile ad hoc networks.” Hum-Centric Comput Inf Sci 1 (1):4.  https://doi.org/10.1186/2192-1962-1-4 (Springer)CrossRefGoogle Scholar
  39. Von Mulert J, Welch I, Seah WKG (2012) “Security threats and solutions in MANETs: a case study using AODV and SAODV.” J Netw Comput Appl 35(4):1249–1259.  https://doi.org/10.1016/j.jnca.2012.01.019 (Elsevier)CrossRefGoogle Scholar
  40. Yu FR, Liu J, Lung CH, Helen T (2009) “Optimal combined intrusion detection and biometric-based continuous authentication in high security mobile ad hoc networks”.  https://doi.org/10.1109/TWC.2009.071036

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Computer Engineering, Shabestar BranchIslamic Azad UniversityShabestarIran

Personalised recommendations