Skip to main content

A context-aware encryption protocol suite for edge computing-based IoT devices


Heterogeneous devices are connected with each other through wireless links within a cyber physical system. These devices undergo resource constraints such as battery, bandwidth, memory and computing power. Moreover, the massive interconnections of these devices result in network latency and reduced speed. Edge computing offers a solution to this problem in which devices transmit the preprocessed actionable data in a formal way, resulting in reduced data traffic and improved speed. However, to provide the same level of security to each piece of information is not feasible due to limited resources. In addition, not all the data generated by Internet of things devices require a high level of security. Context-awareness principles can be employed to select an optimal algorithm based on device specifications and required information confidentiality level. For context-awareness, it is essential to consider the dynamic requirements of data confidentiality as well as device available resources. This paper presents a context-aware encryption protocol suite that selects optimal encryption algorithm according to device specifications and the level of data confidentiality. The results presented herein clearly exhibit that the devices were able to save 79% memory consumption, 56% battery consumption and 68% execution time by employing the proposed context-aware encryption protocol suite.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2
Fig. 3
Fig. 4






  1. Ashton K (2009) That ‘Internet of things’ thing. RFID J 22(7):97–114

    Google Scholar 

  2. Gubbi J, Buyya R, Marusic S, Palaniswami M (2013) Internet of things (IoT): a vision, architectural elements, and future directions. Future Gener Comput Syst 29(7):1645–1660

    Article  Google Scholar 

  3. Hou L, Zhao S, Xiong X, Zheng K, Chatzimisios P, Hossain MS, Xiang W (2016) Internet of things cloud: architecture and implementation. IEEE Commun Mag 54(12):32–39

    Article  Google Scholar 

  4. Khan R, Khan SU, Zaheer R, Khan S (2012) Future internet: the internet of things architecture, possible applications and key challenges. In: 2012 10th International Conference on Frontiers of Information Technology (FIT). IEEE, pp 257–260

  5. Hennebert C, Dos SJ (2014) Security protocols and privacy issues into 6LoWPAN stack: a synthesis. IEEE Internet Things J 1(5):384–398

    Article  Google Scholar 

  6. Liu CH, Sheng Z, Leung VC, Moreno W, Leung KK, Yürür Ö (2016) Context-awareness for mobile sensing: a survey and future directions. IEEE Commun Surv Tutor 18(1):68–93

    Article  Google Scholar 

  7. Roselin AG, Nanda P, Nepal S (2017) Lightweight authentication protocol (LAUP) for 6LoWPAN wireless sensor networks. In: 2017 IEEE Trustcom/BigDataSE/ICESS. IEEE, pp 371–378

  8. Kolias C, Stavrou A, Voas J, Bojanova I, Kuhn R (2016) “Learning internet-of-things security” hands-on. IEEE Secur Priv 14(1):37–46

    Article  Google Scholar 

  9. Su X, Li P, Li Y, Flores H, Riekki J, Prehofer C (2016) Towards semantic reasoning on the edge of IoT systems. In: Proceedings of the 6th International Conference on the Internet of Things, pp 171–172

  10. Gu B, Zhou Z, Mumtaz S, Frascolla V, Bashir AK (2018) Context-aware task offloading for multi-access edge computing: matching with externalities. In: IEEE Globecom

  11. Yaqoob I, Ahmed E, ur Rehman MH, Ahmed AIA, Al-garadi MA, Imran M, Guizani M (2017) The rise of ransomware and emerging security challenges in the Internet of Things. Comput Netw 129:444–458

    Article  Google Scholar 

  12. Marjani M, Nasaruddin F, Gani A, Karim A, Hashem IAT, Siddiqa A, Yaqoob I (2017) Big IoT data analytics: architecture, opportunities, and open research challenges. IEEE Access 5:5247–5261

    Article  Google Scholar 

  13. Bansod G, Patil A, Sutar S, Pisharoty N (2016) ANU: an ultra-lightweight cipher design for security in IoT. Secur Commun Netw 9(18):5238–5251

    Article  Google Scholar 

  14. Siddiqui IF, Qureshi NMF, Shaikh MA, Chowdhry BS, Abbas A, Bashir AK, Lee SUJ (2018) Stuck-at fault analytics of IoT devices using knowledge-based data processing strategy in smart grid. Wireless personal communications. Springer, Berlin

    Google Scholar 

  15. Riker A, Curado M, Monteiro E (2017) Neutral operation of the minimum energy node in energy-harvesting environments. In 2017 IEEE Symposium on Computers and Communication (ISCC), pp 1–6

  16. Adrianto D, Lin FJ (2015) Analysis of security protocols and corresponding cipher suites in ETSI M2M standards. In: 2015 IEEE 2nd World Forum on Internet of Things (WF-IoT). IEEE, pp 777–782

  17. Mohammadian M, Hatzinakos D (2009) Data classification process for security and privacy based on a fuzzy logic classifier. Int J Electron Finance 3(4):374–386

    Article  Google Scholar 

  18. Perera C, Vasilakos AV (2016) A knowledge-based resource discovery for Internet of things. Knowl-Based Syst 109:122–136

    Article  Google Scholar 

  19. Perera C, Zaslavsky A, Christen P, Georgakopoulos D (2014) Context aware computing for the internet of things: a survey. IEEE Commun Surv Tutor 16:414–454

    Article  Google Scholar 

  20. Kao Y-W, Yuan S-M (2012) User-configurable semantic home automation. Comput Stand Interfaces 34(1):171–188

    MathSciNet  Article  Google Scholar 

  21. Zhou Q, Natarajan S, Simmhan Y, Prasanna V (2012) Semantic information modeling for emerging applications in smart grid. In: 2012 Ninth International Conference on Information Technology: New Generations (ITNG). IEEE, pp 775–782

  22. Taylor K, Griffith C, Lefort L, Gaire R, Compton M, Wark T, Lamb D, Falzon G, Trotter M (2013) Farming the web of things. IEEE Intell Syst 28(6):12–19

    Article  Google Scholar 

  23. Hristoskova A, Sakkalis V, Zacharioudakis G, Tsiknakis M, De Turck F (2014) Ontology-driven monitoring of patient’s vital signs enabling personalized medical detection and alert. Sensors 14(1):1598–1628

    Article  Google Scholar 

  24. Preist C, Esplugas-Cuadrado J, Battle SA, Grimm S, Williams SK (2005) Automated business-to-business integration of a logistics supply chain using semantic web services technology. In: International Semantic Web Conference. Springer, pp 987–1001

  25. Medaglia CM, Serbanati A (2010) An overview of privacy and security issues in the Internet of things. In: The Internet of things. Springer, pp 389–395

  26. Messer A, Greenberg I, Bernadat P, Milojicic D, Chen D, Giuli TJ, Gu X (2002) Towards a distributed platform for resource-constrained devices. In: 2002 Proceedings of 22nd International Conference on Distributed Computing Systems. IEEE, pp 43–51

  27. Hofer T, Schwinger W, Pichler M, Leonhartsberger G, Altmann J, Retschitzegger W (2003) Context-awareness on mobile devices-the hydrogen approach. In: 2003 Proceedings of the 36th Annual Hawaii International Conference on System Sciences. IEEE, p 10

  28. Lum WY, Lau FC (2002) A context-aware decision engine for content adaptation. IEEE Pervasive Comput 1(3):41–49

    Article  Google Scholar 

  29. Taneja M, Davy A (2017) Resource aware placement of IoT application modules in Fog-Cloud Computing Paradigm. In: 2017 IFIP/IEEE Symposium on Integrated Network and Service Management (IM). IEEE, pp 1222–1228

  30. Sathyamoorthy P, Ngai EC-H, Hu X, Leung V (2017) Profiling energy efficiency and data communications for mobile Internet of things. Wirel Commun Mobile Comput 2017:1–15 (Article ID 6562915)

  31. Suo H, Wan J, Zou C, Liu J (2012) Security in the Internet of things: a review. In: 2012 International Conference on Computer Science and Electronics Engineering (ICCSEE), vol 3. IEEE, pp 648–651

  32. Musaddiq A, Zikriya YB, Hahm O, Yu HJ, Bashir AK, Kim SW (2018) A survey on resource management in IoT operating systems. IEEE Access 6:8459–8482

    Article  Google Scholar 

  33. Zardari MA, Jung LT (2016) Data security rules/regulations based classification of file data using TsF-kNN algorithm. Clust Comput 19(1):349–368

    Article  Google Scholar 

  34. Zardari MA, Jung LT, Zakaria MNB (2014) Data classification based on confidentiality in virtual Cloud environment. Res J Appl Sci Eng Technol 8(13):1498–1509

    Article  Google Scholar 

  35. Safi A (2017) Improving the security of Internet of things using encryption algorithms. World Acad Sci Eng Technol Int J Comput Electr Autom Control Inf Eng 11(5):546–549

    MathSciNet  Google Scholar 

  36. Wu X-W, Yang E-H, Wang J (2017) Lightweight security protocols for the Internet of things. In 2017 IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC). IEEE, pp 1–7

  37. Hamad F, Smalov L, James A (2009) Energy-aware Security in M-Commerce and the Internet of things. IETE Tech Rev 26(5):357–362

    Article  Google Scholar 

  38. Glissa G, Meddeb A (2017) IEEE 802.15. 4 security sublayer for OMNET++. IEEE, pp 1891–1896

  39. Toldinas J, Damasevicius R, Venckauskas A, Blazauskas T, Ceponis J (2014) Energy consumption of cryptographic algorithms in mobile devices. Elektron Elektrotech 20(5):158–161

    Google Scholar 

  40. Khan SU, Pastrone C, Lavagno L, Spirito MA (2012) An authentication and key establishment scheme for the IP-based wireless sensor networks. Procedia Comput Sci 10:1039–1045

    Article  Google Scholar 

  41. Liu A, Ning P (2008) TinyECC: a configurable library for elliptic curve cryptography in wireless sensor networks. In: Proceedings of the 7th International Conference on Information Processing in Sensor Networks. IEEE Computer Society, pp 245–256

  42. Szczechowiak P, Oliveira LB, Scott M, Collier M, Dahab R (2008) NanoECC: testing the limits of elliptic curve cryptography in sensor networks. In: Wireless Sensor Networks. Springer, pp 305–320

  43. Matthias C, Kris S, An B, Ruben S, Nele M, Kris A (2015) Study on impact of adding security in a 6LoWPAN based network. In: 2015 IEEE Conference on Communications and Network Security (CNS). IEEE, pp 577–584

  44. Raza S, Duquennoy S, Höglund J, Roedig U, Voigt T (2014) Secure communication for the Internet of things—a comparison of link-layer security and IPsec for 6LoWPAN. Secur Commun Netw 7:2654–2668

    Article  Google Scholar 

  45. Jung W, Hong S, Ha M, Kim Y-J, Kim D (2009) SSL-based lightweight security of IP-based wireless sensor networks. In: WAINA’09. International Conference on Advanced Information Networking and Applications Workshops, 2009. IEEE, pp 1112–1117

  46. Mathur M, Kesarwani A (2013) Comparison between Des, 3des, Rc2, Rc6, Blowfish And Aes. In: Proceedings of National Conference on New Horizons in IT-NCNHIT, pp 143–148

  47. Ebrahim M, Khan S, Khalid UB (2013) Symmetric algorithm survey: a comparative analysis. Int J Comput Appl 61(20):0975–8887

    Google Scholar 

  48. Tripathi R, Agrawal S (2014) Comparative study of symmetric and asymmetric cryptography techniques. Int J Adv Found Res Comput: IJAFRC 1(6):68–76

    Google Scholar 

  49. Nie T, Song C, Zhi X (2014) Performance evaluation of DES and Blowfish algorithms. In: 2010 International Conference on Biomedical Engineering and Computer Science (ICBECS). IEEE, pp 1–4

  50. Verma HK, Singh RK (2012) Performance analysis of RC5, Blowfish and DES block cipher algorithms. Int J Comput Appl 42(16):8–14

    Google Scholar 

  51. Agrawal M, Mishra P (2012) A comparative survey on symmetric key encryption techniques. Int J Comput Sci Eng 4(5):877

    Google Scholar 

  52. Kumar A, Gopal K, Aggarwal A (2014) Simulation and analysis of authentication protocols for mobile Internet of things (MIoT). In: 2014 International Conference on PDGC. IEEE, pp 423–428

  53. Brambilla G, Picone M, Cirani S, Amoretti M, Zanichelli F (2014) A simulation platform for large-scale Internet of things scenarios in urban environments. In: Proceedings of the First International Conference on IoT in Urban Space. ICST, pp 50–55

  54. Prasad SR, Vivek R, Mungara J (2016) NS3 simulation studies for optimized neighbour discovery in 6LoWPAN networks. IEEE, pp 15–18

  55. D’Angelo G, Ferretti S, Ghini V (2016) Simulation of the Internet of things. In: 2016 International Conference on High Performance Computing & Simulation (HPCS). IEEE, pp 1–8

  56. Talpur MSH, Bhuiyan MZA, Wang G (2014) Shared–node IoT network architecture with ubiquitous homomorphic encryption for healthcare monitoring. Int J Embedded Syst 7(1):43–54

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations


Corresponding author

Correspondence to Hafiz Husnain Raza Sherazi.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Dar, Z., Ahmad, A., Khan, F.A. et al. A context-aware encryption protocol suite for edge computing-based IoT devices. J Supercomput 76, 2548–2567 (2020).

Download citation

  • Published:

  • Issue Date:

  • DOI:


  • Edge computing
  • Cyber physical systems
  • 6LoWPAN
  • Context-awareness
  • Device specification
  • Information profiling
  • IoT