SpringerLink
Log in

Enhanced-AES encryption mechanism with S-box splitting for wireless sensor networks

  • Original Research
  • Published:
International Journal of Information Technology Aims and scope Submit manuscript

Abstract

The sensor networks have revolutionized wireless technology with next-generation internetworking and scalable infrastructure. Since, the autonomous sensor operates in vulnerable and unattended environmental conditions, hence, securing the sensed data becomes a critical issue. Advanced Encryption Standard popularly known as AES is one of the most common and extensively used algorithms for private key encryption in sensor networks. However, the substitution box lookup table is a time-consuming process in AES. Therefore, our research targets to improve the running time and throughput of AES by proposing a novel technique of splitting AES S-box followed with parallel substituting of two bytes at a time using multithreading. The proposed Enhanced-AES has the feasibility of implementation in the heterogeneous and hierarchical multicore sensor network. Energy consumption and execution time are the parameters used to evaluate the functioning of the Enhanced-AES. Our proposed model outperformed the existing security mechanisms; thereby increasing the lifetime of the sensor network and maintaining the data freshness.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or Ebook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11

Similar content being viewed by others

References

  1. Akyildiz IF, Su W, Sankarasubramaniam Y, Cayirci E (2002) Wireless sensor networks: a survey. Comput Netw 38(4):393–422

    Article  Google Scholar 

  2. Yick J, Mukherjee B, Ghosal D (2008) Wireless sensor network survey. Comput Netw 52(12):2292–2330

    Article  Google Scholar 

  3. Zheng J, Jamalipour A (2009) Wireless sensor networks: a networking perspective. Wiley, New York

    Book  Google Scholar 

  4. Sohraby K, Minoli D, Znati T (2007) Wireless sensor networks: technology, protocols, and applications. Wiley, New York

    Book  Google Scholar 

  5. Matin MA, Islam MM (2012) Overview of wireless sensor network. Wirel Sens Netw Technol Protoc. https://doi.org/10.5772/49376

    Article  Google Scholar 

  6. Rajagopalan R, Varshney PK (2006) Data aggregation techniques in sensor networks: a survey. IEEE Commun Surv Tutor 8(4):48–63

    Article  Google Scholar 

  7. Vodel M, Hardt W (2012) Data aggregation and data fusion techniques in WSN/SANET topologies—a critical discussion. In: TENCON 2012 IEEE Region 10 conference. IEEE, pp 1–6

  8. Sirsikar S, Anavatti S (2015) Issues of data aggregation methods in wireless sensor network: a survey. Proc Comput Sci 49:194–201

    Article  Google Scholar 

  9. Patil NS, Patil PR (2010) Data aggregation in wireless sensor network. In: IEEE int. conf. computational intelligence and computing research

  10. Anastasia G, Contib M, Francescoa M, Passarellab A (2009) Energy conservation in wireless sensor networks: a survey. Ad Hoc Netw 7(3):537–568

    Article  Google Scholar 

  11. Abbasi AA, Younis M (2007) A survey on clustering algorithms for wireless sensor networks. Comput Commun 30(14–15):2826–2841

    Article  Google Scholar 

  12. Perrig A, Stankovic J, Wagner D (2004) Security in wireless sensor networks. Commun ACM 47(6):53–57

    Article  Google Scholar 

  13. Burgner DE, Wahsheh LA (2011) Security of wireless sensor networks. In: 2011 eighth international conference on information technology: new generations. IEEE, pp 315–320

  14. Wang Y, Attebury G, Ramamurthy B (2006) A survey of security issues in wireless sensor networks. IEEE Commun Surv Tutor 8:2–23

    Article  Google Scholar 

  15. Minaam DSA, Abdual-Kader HM, Hadhoud MM (2010) Evaluating the effects of symmetric cryptography algorithms on power consumption for different data types. IJ Netw Secur 11(2):78–87

    Google Scholar 

  16. Kumar MA, Karthikeyan S (2012) Investigating the efficiency of Blowfish and Re**dael (AES) algorithms. Int J Comput Netw Inf Secur 4(2):22

    Google Scholar 

  17. Abd Elminaam DS, Abdual-Kader HM, Hadhoud MM (2010) Evaluating the performance of symmetric encryption algorithms. IJ Netw Secur 10(3):216–222

    Google Scholar 

  18. Krishnamurthy GN, Ramaswamy V (2008) Making AES stronger: AES with key dependent S-box. IJCSNS Int J Comput Sci Netw Secur 8(9):388–398

    Google Scholar 

  19. Yan J, Chen F (2016) An improved AES key expansion algorithm. In: 2016 international conference on electrical, mechanical and industrial engineering. Atlantis Press

  20. Wang J, Xu H, Yao M (2012) Improvement of the round key generation of AES. Int J Commun Netw Syst Sci 5(12):850–853

    Google Scholar 

  21. Elkabbany GF, Aslan HK, Rasslan MN (2015). A design of a fast parallel-pipelined implementation of AES: Advanced Encryption Standard. ar**v preprint ar**v: 1501.01427

  22. Liu B, Baas BM (2011) Parallel AES encryption engines for many-core processor arrays. IEEE Trans Comput 62(3):536–547

    Article  MathSciNet  Google Scholar 

  23. Munir A, Gordon-Ross A, Ranka S (2013) Multi-core embedded wireless sensor networks: architecture and applications. IEEE Trans Parallel Distrib Syst 25(6):1553–1562

    Article  Google Scholar 

  24. Duan CH, Jiang J, Wang XM, Xu WY (2009) Fast S-box substitution instructions and their hardware implementation for accelerating symmetric cryptographic processing. In: 2009 international conference on E-business and information system security. IEEE, pp 1–4

  25. Le D, Chang J, Gou X, Zhang A, Lu C (2010) Parallel AES algorithm for fast data encryption on GPU. In: 2010 2nd international conference on computer engineering and technology, vol 6. IEEE, p V6-1

  26. Barnes A, Fernando R, Mettananda K, Ragel R (2012) Improving the throughput of the AES algorithm with multicore processors. In: 2012 IEEE 7th international conference on industrial and information systems (ICIIS). IEEE, pp 1–6

  27. Kim JM, Lee HS, Yi J, Park M (2016) Power adaptive data encryption for energy-efficient and secure communication in solar-powered wireless sensor networks. J Sens 2016:1–9

    Google Scholar 

  28. Perrig A, Szewczyk R, Tygar JD, Wen V, Culler DE (2002) SPINS: Security protocols for sensor networks. Wirel Netw 8(5):521–534

    Article  Google Scholar 

  29. Chu CK, Liu JK, Zhou J, Bao F, Deng RH (2010) Practical ID-based encryption for wireless sensor network. In: Proceedings of the 5th ACM symposium on information, computer and communications security, pp 337–340

  30. Mullai A, Mani K (2020) Enhancing the security in RSA and elliptic curve cryptography based on addition chain using simplified Swarm Optimization and Particle Swarm Optimization for mobile devices. Int J Inf Technol. https://doi.org/10.1007/s41870-019-00413-8

    Article  Google Scholar 

  31. Saravanan P, Kalpana P (2018) Novel reversible design of advanced encryption standard cryptographic algorithm for wireless sensor networks. Wirel Pers Commun 100(4):1427–1458

    Article  Google Scholar 

  32. Li J (2017) A symmetric cryptography algorithm in wireless sensor network security. Int J Online Biomed Eng (iJOE) 13(11):102–110

    Article  Google Scholar 

  33. Farooq S, Prashar D, Jyoti K (2018) Hybrid encryption algorithm in wireless body area networks (WBAN). Intelligent communication, control and devices. Springer, Singapore, pp 401–410

    Chapter  Google Scholar 

  34. Ahmad A, Javaid N, Imran M, Guizani M, Alhamed AA (2016) An advanced energy consumption model for terrestrial wireless sensor networks. In: 2016 international wireless communications and mobile computing conference (IWCMC). IEEE, pp 790–793

  35. Savita, Lobiyal DK (2019) Multicopy energy aware distance and inter-contact delay routing (EDICDR) approach for delay tolerant networks. Int J Comput Netw Inf Secur 11(5). https://doi.org/10.5815/ijcnis.2019.05.05

  36. Genta A, Lobiyal DK, Abawajy JH (2019) Energy efficient multipath routing algorithm for wireless multimedia sensor network. Sensors 19(17):3642

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Computer Science & Engineering and Information Technology, Jaypee Institute of Information Technology, Noida, 62, Uttar Pradesh, India

    Meeta Gupta & Adwitiya Sinha

Authors
  1. Meeta Gupta
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Adwitiya Sinha
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Adwitiya Sinha.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Gupta, M., Sinha, A. Enhanced-AES encryption mechanism with S-box splitting for wireless sensor networks. Int. j. inf. tecnol. 13, 933–941 (2021). https://doi.org/10.1007/s41870-021-00626-w

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s41870-021-00626-w

Keywords

Search

Navigation