nach oben

Cluster Computing

Erschienen in:

01.01.2020

The limitations in the state-of-the-art counter-measures against the security threats in H-IoT

verfasst von: Yazdan Ahmad Qadri, Rashid Ali, Arslan Musaddiq, Fadi Al-Turjman, Dae Wan Kim, Sung Won Kim

Erschienen in: Cluster Computing | Ausgabe 3/2020

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config

KI-gestützte Suche

Aus

Abstract

Internet of Things (IoT) technology is anticipated to pave the way for groundbreaking applications in a number of areas of current healthcare systems. Given the significant number of connected medical devices, the vital data generated by the patient is under several security threats. Selective Forwarding (SF) and Wormhole (WH) attacks are two critical threats that cause information deficit in the network. The SF attack drops critical data packets at compromised nodes while the WH attack creates fallacious routing tables due to the introduction of malicious routes in the network. In this paper, we focus on the security aspects of Healthcare-IoT and review the proposed counter-measures against the SF and WH attacks. We weigh the recently postulated counter-measures based on their significance and identify their limitations. Additionally, we propose a blockchain-based cryptographic framework for mitigating SF and WH attacks in H-IoT. We explore future research directions in mitigating these threats.

Vorheriger Artikel A game theoretic analysis of resource mining in blockchain

Nächster Artikel A decentralized lightweight blockchain-based authentication mechanism for IoT systems

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Alagar, V., Alsaig, A., Ormandjiva, O., Wan, K.: Context-based security and privacy for healthcare IoT. In: 2018 IEEE International Conference on Smart Internet of Things (SmartIoT), Xi’an, pp. 122–128 (2018). https://doi.org/10.1109/SmartIoT.2018.00-14

Ramli, S.N., Ahmad, R.: Surveying the wireless body area network in the realm of wireless communication. In: 2011 7th International Conference Information Assurance and Security (IAS), Melaka, pp. 58–61 (2011). https://doi.org/10.1109/ISIAS.2011.6122845

Suresh, P., Daniel, J.V., Parthasarathy, V., Aswathy, R.H.: A state of the art review on the Internet of Things (IoT) History, Technology and fields of deployment. In: 2014 International Conference on Science Engineering and Management (ICSEMR), Chennai, India, pp. 1–8 (2014). https://doi.org/10.1109/ICSEMR.2014.7043637

Qadri, Y.A., Musaddiq, A., Kim, D.W., Kim, S.W.: An overview of selective forwarding and wormhole attacks in healthcare IoT. In: Asia Pacific Conference on Information Communication Technology (APCICT-2018), Daegu, Korea (2018)

Naik, M.R.K., Samundiswary, P.: Wireless body area network security issues-survey. In: 2016 International Conference on Control, Instrumentation, Communication and Computational Technologies (ICCICCT), Kumaracoil, India, pp. 190–194 (2016). https://doi.org/10.1109/ICCICCT.2016.7987943

He, D., Zeadally, S., Kumar, N., Lee, J.H.: Anonymous authentication for wireless body area networks with provable security. IEEE Syst. J. 11(4), 1–12 (2017). https://doi.org/10.1109/JSYST.2016.2544805CrossRef

Lin, Y.-J., Chen, H.-S., Su, M.-J.: A cloud based bluetooth low energy tracking system for dementia patients. In: 2015 Eighth International Conference on Mobile Computing and Ubiquitous Networking (ICMU), Hakodate, pp. 88–89 (2015). https://doi.org/10.1109/ICMU.2015.7061043

IEEE Standard for Low-Rate Wireless Networks. IEEE Std 802.15.4-2015 (Revision of IEEE Std 802.15.4-2011), pp. 1–709, (2016). https://doi.org/10.1109/IEEESTD.2016.7460875

Ali, R., Kim, S.W., Kim, B., Park, Y.: Design of MAC layer resource allocation schemes for IEEE 802.11ax: future directions. IETE Tech. Rev. 35(1), 28–52 (2018). https://doi.org/10.1080/02564602.2016.1242387CrossRef

10.

He, S., Cheng, B., Wang, H., Huang, Y., Chen, J.: Proactive personalized services through fog-cloud computing in large-scale iot-based healthcare application. China Commun. 14(11), 1–16 (2017). https://doi.org/10.1109/CC.2017.8233646CrossRef

11.

Ridhawi, I.A., Aloqaily, M., Kotb, Y., Jararweh, Y.: A profitable and energy-efficient cooperative fog solution for IoT services. In: IEEE Transactions on Industrial Informatics (Early Access) (2019). https://doi.org/10.1109/TII.2019.2922699

12.

Buyukakkaslar, M.T., Erturk, M.A., Aydin, M.A., Vollero, L.: LoRaWAN as an e-health communication technology. In: 2017 IEEE 41st Annual Computer Software and Applications Conference (COMPSAC), Turin, pp. 310–313 (2017). https://doi.org/10.1109/COMPSAC.2017.162

13.

Lavric, A., Petrariu, A.I., Popa, V.: Long range sigfox communication protocol scalability analysis under large-scale, high-density conditions. IEEE Access 7, 35816–35825 (2019). https://doi.org/10.1109/ACCESS.2019.2903157CrossRef

14.

Anand, S, Routray, S.K.: Issues and challenges in healthcare narrowband IoT. In: 2017 international conference on inventive communication and computational technologies (ICICCT), Coimbatore, pp. 486–489 (2017). https://doi.org/10.1109/ICICCT.2017.7975247

15.

Baker, S.B., Xiang, W., Atkinson, I.: Internet of things for smart healthcare: technologies, challenges, and opportunities. IEEE Access 5, 26521–26543 (2017). https://doi.org/10.1109/ACCESS.2017.2775180CrossRef

16.

Zafar, S., Jangsher, S., Bouachir, O., Aloqaily, M., Othman, J.B.: QoS enhancement with deep learning-based interference prediction in mobile IoT. Comput. Commun. 148, 86–97 (2019). https://doi.org/10.1016/j.comcom.2019.09.010CrossRef

17.

Firouzi, F., Farahani, B., Ibrahim, M., Chakrabarty, K.: From EDA to IoT eHealth: promise, challenges, and solutions. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 37(12), 1–16 (2018). https://doi.org/10.1109/TCAD.2018.2801227CrossRef

18.

Faheem, M., Gungor, V.C.: Capacity and spectrum-aware communication framework for wireless sensor network-based smart grid applications. Comput. Stand. Interfaces 53, 48–58 (2017). https://doi.org/10.1016/j.csi.2017.03.003CrossRef

19.

Faheem, M., Butt, R.A, Raza, B, Ashraf, M.W, Begum, S, Ngadi, M.A, Gungor, V.C: Bio-inspired routing protocol for WSN-based smart grid applications in the context of Industry 4.0. In: Transactions on Emerging Telecommunications Technologies (2018). https://doi.org/10.1002/ett.3503

20.

Faheem, M., Gungor, V.C.: Energy efficient and QoS-aware routing protocol for wireless sensor network-based smart grid applications in the context of industry 4.0. Appl. Soft Comput. 68, 910–922 (2018). https://doi.org/10.1016/j.asoc.2017.07.045CrossRef

21.

Faheem, M., Abbas, M.Z., Tuna, G., Gungor, V.C.: EDHRP: Energy efficient event driven hybrid routing protocol for densely deployed wireless sensor networks. J. Netw. Comput. Appl. 58, 309–326 (2015). https://doi.org/10.1016/j.jnca.2015.08.002CrossRef

22.

Al-Turjman, F., Ever, E., Zahmatkesh, H.: Internet of nano-things (IoNT) & WBAN. In: Al-Turjman, F. (ed.) Internet of Nano-Things and Wireless Body Area Networks (WBAN). CRC Press, Baco Raton (2019)CrossRef

23.

Topel, S.D., Al-Turjman, F.: Nanosensors for the internet of nano-things (IoNT): an overview. In: Al-Turjman, F. (ed.) Internet of Nano-Things and Wireless Body Area Networks (WBAN). CRC Press, Boca Raton (2019)

24.

Balasubramanian, V., Zaman, F., Aloqaily, M., Ridhawi, I.A., Jararweh, Y., Salameh, H.B.: A mobility management architecture for seamless delivery of 5G-IoT services. In: 2019 IEEE International Conference on Communications (ICC 2019), Shanghai, China, pp. 1–7 (2019). https://doi.org/10.1109/ICC.2019.8761658

25.

Tomić, I., McCann, J.A.: A survey of potential security issues in existing wireless sensor network protocols. IEEE Internet Things J. 4(6), 1910–1923 (2017). https://doi.org/10.1109/JIOT.2017.2749883CrossRef

26.

Zheng, Z., Xie, S., Dai, H.-N., Wang, H.: Blockchain challenges and opportunities: a survey. Int. J. Web Grid Serv. 14, 352–375 (2016). https://doi.org/10.1504/ijwgs.2018.10016848CrossRef

27.

Dwivedi, A.D., Srivastava, G., Dhar, S., Singh, R.: A decentralized privacy-preserving healthcare blockchain for IoT. Sensors 19(2), 326 (2019). https://doi.org/10.3390/s19020326CrossRef

28.

Salah, K., Rehman, M.H.U., Nizamuddin, N., Al-Fuqaha, A.: Blockchain for AI: review and open research challenges. IEEE Access 7, 10127–10149 (2019). https://doi.org/10.1109/ACCESS.2018.2890507CrossRef

29.

Salleh, A., Mamat, K., Darus, M.Y.: Integration of wireless sensor network and web of things: security perspective. In: 2017 IEEE 8th Control and System Graduate Research Colloquium (ICSGRC), Shah Alam, Malaysia, pp. 138–143 (2017). https://doi.org/10.1109/ICSGRC.2017.8070583

30.

Goyal, S., Bhatia, T., Verma, A.K.: Wormhole and Sybil attack in WSN: a review. In: 2015 2nd International Conference on Computing for Sustainable Global Development (INDIACom), New Delhi, India, pp. 1463–1468 (2015)

31.

Prabhakar, A., Anjali, T.: Mitigating selective Gray Hole Attack in wireless multi-hop network. In: 2017 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET), Chennai, India, pp. 1223–1227 (2017). https://doi.org/10.1109/WiSPNET.2017.8299958

32.

Khabbazian, M., Mercier, H., Bhargava, V.K.: Severity analysis and countermeasure for the wormhole attack in wireless ad hoc networks. IEEE Trans. Wireless Commun. 8(2), 736–745 (2009). https://doi.org/10.1109/TWC.2009.070536CrossRef

33.

Yu, B., Xiao, B.: Detecting selective forwarding attacks in wireless sensor networks. In: 20th International Parallel and Distributed Processing Symposium (IPDPS), Rhodes Island, Greece (2006). https://doi.org/10.1109/IPDPS.2006.1639675

34.

Liu, A., Dong, M., Ota, K., Long, J.: PHACK: an efficient scheme for selective forwarding attack detection in WSNs. Sensors 15(12), 30942–30963 (2015). https://doi.org/10.3390/s151229835CrossRef

35.

Mathur, A., Newe, T., Rao, M.: Healthcare WSN: cluster elections and selective forwarding defense. In: NGMAST 9th International Conference on Next Generation Mobile Applications, Services and Technologies, Cambridge, UK, pp. 341–346 (2015). https://doi.org/10.1109/NGMAST.2015.14

36.

Ren, J., Zhang, Y., Zhang, K., Shen, X.: Adaptive and channel-aware detection of selective forwarding attacks in wireless sensor networks. IEEE Trans. Wireless Commun. 15(5), 3718–3731 (2016). https://doi.org/10.1109/TWC.2016.2526601CrossRef

37.

Gara, F., Saad, L.B., Ayed, R.B.: An intrusion detection system for selective forwarding attack in IPv6-based mobile WSNs. In: 2017 13th International Wireless Communications and Mobile Computing Conference (IWCMC), Valencia, Spain, pp. 276–281 (2017). https://doi.org/10.1109/IWCMC.2017.7986299

38.

Ioannou, C., Vassiliou, V., Sergiou, C.: An intrusion detection system for wireless sensor networks. In: 2017 24th International Conference on Telecommunications (ICT), Limassol, Cyprus, pp. 1–5 (2017). https://doi.org/10.1109/ICT.2017.7998271

39.

Dorri, A.: An EDRI-based approach for detecting and eliminating cooperative black hole nodes in MANET. Springer Wirel. Netw. 23(6), 1767–1778 (2017). https://doi.org/10.1007/s11276-016-1251-xCrossRef

40.

Pu, C., Lim, S.: A light-weight countermeasure to forwarding misbehavior in wireless sensor networks: design, analysis, and evaluation. IEEE Syst. J. 12(1), 1–9 (2018). https://doi.org/10.1109/JSYST.2016.2535730CrossRef

41.

Mehetre, D.C., Roslin, S.E., Wagh, S.J.: Detection and prevention of black hole and selective forwarding attack in clustered wsn with active trust. Clust. Comput. 22, 1313–1328 (2018). https://doi.org/10.1007/s10586-017-1622-9CrossRef

42.

Modirkhazeni, A., Aghamahamoodi, S., Modirkhazeni, A., Niknejad, N.: Distributed approach to mitigate wormhole attack in wireless sensor network. In: 7th International Conference on Networked Computing, Gyeongsanbuk-do, Korea, pp. 122–128 v

43.

Qazi, S., Raad, R., Mu, Y., Susilo, W.: Securing DSR against wormhole attacks in multi-rate ad hoc networks. J. Netw. Comput. Appl. 36(2), 582–592 (2013). https://doi.org/10.1016/j.jnca.2012.12.019CrossRef

44.

Bendjima, M., Feham, M.: Wormhole attack detection in wireless sensor networks. In: 2016 SAI Computing Conference (SAI), London, UK, pp. 1319–1326 (2016). https://doi.org/10.1109/SAI.2016.7556151

45.

Sharma, M.K., Joshi, B.K.: A mitigation technique for high transmission power based wormhole attack in wireless sensor networks. In: 2016 International Conference on ICT in Business Industry & Government (ICTBIG), Indore, India, pp. 1–6 (2016). https://doi.org/10.1109/ICTBIG.2016.7892698

46.

Singh, R., Singh, J., Singh, R.: WRHT: a hybrid technique for detection of wormhole attack in wireless sensor networks. J. Mob. Inf. Syst. 2016, 1–13 (2016). https://doi.org/10.1155/2016/8354930CrossRef

47.

Parmar, A., Vaghelab, V.B.: Detection and prevention of wormhole attack in wireless sensor network using AOMDV protocol. Procedia Comput. Sci. 79, 700–707 (2016). https://doi.org/10.1016/j.procs.2016.03.092CrossRef

48.

Shukla, P.: ML-IDS: A machine learning approach to detect Wormhole attacks in Internet of Things. In: 2017 Intelligent Systems Conference (IntelliSys), London, pp. 234–240 (2017). https://doi.org/10.1109/IntelliSys.2017.8324298

49.

Ahsan, M.S., Bhutta, M.N.M., Maqsood, M.: Wormhole attack detection in routing protocol for low power lossy networks. In: 2017 International Conference on Information and Communication Technologies (ICICT), Karachi, pp. 58–67 (2017). https://doi.org/10.1109/ICICT.2017.8320165

50.

Rmayti, M., Begriche, Y., Khatoun, R., Khoukhi, L., Mammeri, A.: Graph-based wormhole attack detection in mobile ad hoc networks (MANETs). In: 2018 Fourth International Conference on Mobile and Secure Services (MobiSecServ), Florida, USA, pp. 1–6 (2018). https://doi.org/10.1109/MOBISECSERV.2018.8311439

51.

Zikria, Y.B., Kim, S.W., Hahm, O., Afzal, M.K., Aalsalem, M.Y.: Internet of Things (IoT) operating systems management: opportunities, challenges, and solution. Sensors 19(8), 1–10 (2019). https://doi.org/10.3390/s19081793CrossRef

52.

Reyna, A., Martín, C., Chen, J., Soler, E., Díaz, M.: On blockchain and its integration with IoT: challenges and opportunities. Future Gener. Comput. Syst. 88, 173–190 (2018). https://doi.org/10.1016/j.future.2018.05.046CrossRef

53.

Huh, S., Cho, S., Kim, S.: Managing IoT devices using blockchain platform. In: 2017 19th International Conference on Advanced Communication Technology (ICACT), Bongpyeong, pp. 464–467 (2017). https://doi.org/10.23919/ICACT.2017.7890132

54.

Feng, Q., He, D., Zeadally, S., Khan, M.K., Kumar, N.: A survey on privacy protection in blockchain system. J. Netw. Comput. Appl. 126, 45–58 (2019). https://doi.org/10.1016/j.jnca.2018.10.020CrossRef

55.

Antonopoulos, A.M.: Mastering Bitcoin: Unlocking Digital Cryptocurrencies, 1st edn. O’Reilly Media, Inc., Newton (2014). ISBN:1449374042 9781449374044

56.

Virmani, C., Gupta, D.J., Choudhary, T.: Blockchain 2.0: an edge over technologies. In: Architectures and Frameworks for Developing and Applying Blockchain Technology. IGI Global, Pennsylvania (2019). https://doi.org/10.4018/978-1-5225-9257-0.ch009

57.

Monrat, A.A., Schelén, O., Andersson, K.: A survey of blockchain from the perspectives of applications, challenges, and opportunities. IEEE Access 7, 117134–117151 (2019). https://doi.org/10.1109/ACCESS.2019.2936094CrossRef

58.

Otte, P., Vos, N.D., Pouwelse, J: TrustChain: A Sybil-resistant scalable blockchain. Future Gener. Comput. Syst. (2017). https://doi.org/10.1016/j.future.2017.08.048

59.

Douceur, J.R.: The sybil attack. In: 1st International Workshop on Peer-To-Peer Systems (IPTPS), Berlin, pp. 251–260 (2002)

60.

Sayeed, S., Marco-Gisbert, H.: Assessing blockchain consensus and security mechanisms against the 51% attack. Appl. Sci. 9(9), 1788 (2019). https://doi.org/10.3390/app9091788CrossRef

61.

Aloqaily, M., Otoum, S., Al Ridhawi, I., Jararweh, Y.: An intrusion detection system for connected vehicles in smart cities. Ad Hoc Netw. 90, 101842 (2019). https://doi.org/10.1016/j.adhoc.2019.02.001CrossRef

62.

Al-Turjman, F., Din, S., Paul, A.: Energy monitoring in IoT-based ad hoc networks: an overview. Comput. Electr. Eng. 76, 133–142 (2019). https://doi.org/10.1016/j.compeleceng.2019.03.013CrossRef

63.

Demir, S.M., Al-Turjman, F., Muhtaroglu, A.: Energy-harvesting methods for WBAN applications. In: Al-Turjman, F. (ed.) Internet of Nano-Things and Wireless Body Area Networks (WBAN). CRC Press, Boca Raton (2019)

64.

Balasubramanian, V., Zaman, F., Aloqaily, M., Alrabaee, S., Gorlatova, M., Reisslein, M.: Reinforcing the edge: autonomous energy management for mobile device clouds. In: IEEE International Conference on Computer Communications, Paris, France (2019)

65.

Al-Turjman, F., Zahmatkesh, H., Mostarda, L.: Quantifying uncertainty in internet of medical things and big-data services using intelligence and deep learning. In: IEEE Access (Early Access). https://doi.org/10.1109/ACCESS.2019.2931637

66.

Balasubramaniam, V., Aloqaily, M., Zaman, F., Jararweh, Y.: Exploring computing at the edge: a multi-interface system architecture enabled mobile device cloud. In: 2018 IEEE 7th International Conference on Cloud Networking (CloudNet),Tokyo, Japan (2018). https://doi.org/10.1109/CloudNet.2018.8549296

67.

Dai, Y., Xu, D., Maharjan, S., Chen, Z., He, Q., Zhang, Y.: Blockchain and deep reinforcement learning empowered intelligent 5G beyond. IEEE Netw. 33, 10–17 (2019). https://doi.org/10.1109/MNET.2019.1800376CrossRef

68.

Rathee, G., Sharma, A., Iqbal, R., Aloqaily, M., Jaglan, N., Kumar, R.: A blockchain framework for securing connected and autonomous vehicles. Sensors 19, 3165 (2019). https://doi.org/10.3390/s19143165CrossRef

Titel: The limitations in the state-of-the-art counter-measures against the security threats in H-IoT
verfasst von: Yazdan Ahmad Qadri
Rashid Ali
Arslan Musaddiq
Fadi Al-Turjman
Dae Wan Kim
Sung Won Kim
Publikationsdatum: 01.01.2020
Verlag: Springer US
Erschienen in: Cluster Computing / Ausgabe 3/2020
Print ISSN: 1386-7857
Elektronische ISSN: 1573-7543
DOI: https://doi.org/10.1007/s10586-019-03036-7

Springer Professional

Abstract

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Technik"

Springer Professional "Wirtschaft"

Weitere Artikel der Ausgabe 3/2020

Apache Spark Implementation of Whale Optimization Algorithm

Comprehensive techniques of multi-GPU memory optimization for deep learning acceleration

Blockchain structures to guarantee logging integrity of a digital platform to support community-dwelling older adults

Enhancement of fraternal K-median algorithm with CNN for high dropout probabilities to evolve optimal time-complexity

An efficient data transmission approach using IAES-BE

IoTBlockSIEM for information security incident management in the internet of things ecosystem

Premium Partner