Handling Information Security Wisely Utilising the Aggressive Cuckoo Search Algorithm in Lock Systems

Authors

  • Adusumalli Balaji Computer Science and Engineering, Chalapathi institute of engineering and technology, Guntur, India
  • Ch. Indira Priyadarsini Deapartment of Mechanical Engineering, Chaitanya Bharati Institute of Technology, Hyderabad, India.
  • Eluri Nageswara Rao Computer Science and Engineering(IOT), RVR & JC College of Engineering, Guntur, India.
  • Gowru Bharath Kumar Computer Science and Engineering, Chalapathi institute of engineering and technology, Guntur,India
  • Arumalla Nagaraju Computer Science and Engineering, koneru lakshmaiah education foundation, vaddeswaram,Vijayawada,India
  • Narne Srikanth Computer Science and Engineering(AI&ML), RVR & JC College of Engineering, Guntur, India
  • Popuri Srinivasarao Computer Science and Engineering(DS), RVR & JC College of Engineering, Guntur, India.

Keywords:

Information security, IoT, cryptography, Aggressive Cuckoo Search Algorithms

Abstract

Concerns relating to safety and privacy have been brought to light as a result of the growing adoption of Internet of Things (IoT) devices, such as smart home appliances, mobile phones, and smart watches. Security has emerged as an essential component in the development of Internet of Things (IoT) systems in light of the growing number of assaults that originate from both malicious and non-malicious sources. The increasing volume of data that is stored in IoT systems presents a number of unique challenges, one of the most crucial being data security. Hackers may be able to remotely take control of Internet of Things devices if inadequate security measures are in place, which may result in substantial harm. This research suggests utilizing the Aggressive Cuckoo Search Algorithm method (ACS), the SHA-256 method, and the Elliptic Curve Cryptography (ECC) in order to solve these issues while enhancing the safety of internet of things (I smart door lock systems. ACS stands for Aggressive Cuckoo Search, SHA-256 stands for Secure Hash Algorithm, and ECC stands for Elliptic Curve Cryptography. In order to produce the ECC private key, the suggested architecture makes use of ACS, which has the potential to improve the data storage security of IoT systems. In the study, both the encoding and decoding times of the suggested design are analyzed, and it is compared to other encoding methods like (ECC-GA-SHA-256) and (ECC-FA-SHA-256). The findings indicate that the proposed design is capable of producing superior outcomes with 125 iterations for the encoding process and 175 iterations for the decoding process. In addition, the proposed design features encoding and decoding times that are over 16.17 percentage points faster than those of previous encoding methods. Based on these data, it appears that the design that was proposed has the potential to considerably improve the functionality and safety of IoT-based smart door lock systems. The employment of ACS, SHA-256, and ECC can serve as potential solutions to overcome the security concerns connected with IoT-based intelligent locking systems. These are all cryptographic standard algorithms.

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References

L. Kong and B. Ma, “Intelligent manufacturing model of construction industry based on Internet of Things technology,” The International Journal of Advanced Manufacturing Technology, vol. 107, pp. 1025–1037, 2020.

Jha, A. Athanerey and A. Kumar, “Role and challenges of internet of things and informatics in healthcare

research,” Health and Technology, vol. 12, no. 4, pp. 701–712, 2022.

Kamilaris and A. Pitsillides, “Mobile phone computing and the internet of things: A survey,” IEEE Internet of Things Journal, vol. 3, no. 6, pp. 885–898, 2016.

P. M. Chanal and M. S. Kakkasageri, “Security and privacy in IoT: A survey,” Wireless Personal Communications, vol. 115, pp. 1667–1693, 2020.

K. R. Sarkar, “Assessing insider threats to information security using technical, behavioural and organisa- tional measures,” Information Security Technical Report, vol. 15, no. 3, pp. 112–133, 2010.

Makhdoom, M. Abolhasan, H. Abbas and W. Ni, “Blockchain’s adoption in IoT: The challenges, and a way forward,” Journal of Network and Computer Applications, vol. 125, pp. 251–279, 2019.

Ghani, K. Mansoor, S. Mehmood, S. A. Chaudhry, A. U. Rahman et al., “Security and key management in IoT-based wireless sensor networks: An authentication protocol using symmetric key,” International Journal of Communication Systems, vol. 32, no. 16, pp. e4139, 2019.

R. Aldawira, H. W. Putra, N. Hanafiah, S. Surjarwo and A. Wibisurya, “Door security system for home monitoring based on ESP32,” Procedia Computer Science, vol. 157, pp. 673–682, 2019.

Ha, “Security and usability improvement on a digital door lock system based on internet of things,”

International Journal of Security and its Applications, vol. 9, no. 8, pp. 45–54, 2015.

Jacobsson, M. Boldt and B. Carlsson, “A risk analysis of a smart home automation system,” Future Generation Computer Systems, vol. 56, pp. 719–733, 2016.

M. Ahtsham, H. Y. Yan and U. Ali, “IoT based door lock surveillance system using cryptographic algorithms,” in 2019 IEEE 16th Int. Conf. Networking, Sensing and Control (ICNSC), Banff, AB, Canada, pp. 448–453, 2019.

X. S. Yang and S. Deb, “Cuckoo search via Lévy flights,” in 2009 World Congress on Nature & Biologically Inspired Computing (NaBIC), Coimbatore, India, pp. 210–214, 2009.

V. S. Miller, “Use of elliptic curves in cryptography,” in 12th Int. Workshop, Canada, SAC, pp. 417–426, 2005.

H. Yoshida and A. Biryukov, “Analysis of a SHA-256 variant,” in 12th Int. Workshop, Canada, SAC, pp. 245–260, 2006.

S. R. Prasanna and B. S. Premananda, “Performance analysis of MD5 and SHA-256 algorithms to maintain data integrity,” in 2021 Int. Conf. on Recent Trends on Electronics, Information, Communication & Technology (RTEICT), Bangalore, India, pp. 246–250, 2021.

N. K. Sreelaja and G. V. Pai, “Stream cipher for binary image encryption using ant colony optimization based key generation,” Applied Soft Computing, vol. 12, no. 9, pp. 2879–2895, 2012.

Shankar and P. Eswaran, “A secure visual secret share (VSS) creation scheme in visual cryptography using elliptic curve cryptography with optimization technique,” Australian Journal of Basic & Applied Science, vol. 9, no. 36, pp. 150–163, 2015.

Shankar and P. Eswaran, “An efficient image encryption technique based on optimized key generation in ECC using genetic algorithm,” in Artificial Intelligence and Evolutionary Computations in Engineering Systems: Proc. of ICAIECES 2015, India, Springer, pp. 705–714, 2016.

Dworak, J. Nalepa, U. Boryczka and M. Kawulok, “Cryptanalysis of SDES using genetic and memetic algorithms,” in Recent Developments in Intelligent Information and Database Systems, Springer, Cham, pp. 3–14, 2016.

Kalaiselvi and A. Kumar, “An empirical study on effect of variations in the population size and generations of genetic algorithms in cryptography,” in 2017 IEEE Int. Conf. on Current Trends in Advanced Computing (ICCTAC), Bangalore, India, pp. 1–5, 2017.

Ahmad, M. Z. Alam, Z. Umayya, S. Khan and F. Ahmad, “An image encryption approach using particle swarm optimization and chaotic map,” International Journal of Information Technology, vol. 10, pp. 247–255, 2018.

S. Kota, V. N. R. Padmanabhuni and K. Budda, “Authentication and encryption using modified elliptic curve cryptography with particle swarm optimization and cuckoo search algorithm,” Journal of the Institution of Engineers (India): Series B, vol. 99, no. 4, pp. 343–351, 2018.

R. Kiruba and T. Sree Sharmila, “Secure data hiding by fruit fly optimization improved hybridized seeker algorithm,” Multidimensional Systems and Signal Processing, vol. 33, no. 3, pp. 1423–1443, 2020.

T. Avudaiappan, R. Balasubramanian, S. S. Pandiyan, M. Saravanan, S. K. Lakshmanaprabu et al., “Medical image security using dual encryption with oppositional based optimization algorithm,” Journal of Medical Systems, vol. 42, pp. 1–11, 2018.

S. Mitra, G. Mahapatra, V. E. Balas and R. Chattaraj, “Public key cryptography using harmony search algorithm,” in Innovations in Infrastructure, Singapore, Springer, pp. 1–11, 2019.

Shankar, M. Elhoseny, E. Perumal, M. Ilayaraja and K. Sathesh Kumar, “An efficient image encryption scheme based on signcryption technique with adaptive elephant herding optimization,” in Cybersecurity and Secure Information Systems: Challenges and Solutions in Smart Environments. Springer, Cham, pp. 31–42, 2019.

Din, S. K. Pal and S. K. Muttoo, “Applying PSO based technique for analysis of geffe generator cryptosystem,” in Harmony Search and Nature Inspired Optimization Algorithms: Theory and Applications, ICHSA 2018. Singapore: Springer, pp. 741–749, 2019.

S. Vimal, M. Khari, R. G. Crespo, L. Kalaivani, N. Dey et al., “Energy enhancement using multiobjective ant colony optimization with double Q learning algorithm for IoT based cognitive radio networks,” Computer Communications, vol. 154, pp. 481–490, 2020.

Z. Wang, D. Liu and A. Jolfaei, “Resource allocation solution for sensor networks using improved chaotic firefly algorithm in IoT environment,” Computer Communications, vol. 156, pp. 91–100, 2020.

P. Siddavaatam and R. Sedaghat, “A novel multi-objective optimizer framework for TDMA-based medium access control in IoT,” CSI Transactions on ICT, vol. 8, pp. 319–330, 2020.

K. Tamilarasi and A. Jawahar, “Medical data security for healthcare applications using hybrid lightweight encryption and swarm optimization algorithm,” Wireless Personal Communications, vol. 114, pp. 1865– 1886, 2020.

S. Yousefi, F. Derakhshan, H. S. Aghdasi and H. Karimipour, “An energy-efficient artificial bee colony- based clustering in the internet of things,” Computers & Electrical Engineering, vol. 86, pp. 106733, 2020.

P. Verma, N. Jain and S. K. Pal, “Design and analysis of an optimal ECC algorithm with effective access control mechanism for big data,” Multimedia Tools and Applications, vol. 79, pp. 9757–9783, 2020.

S. Nandan, S. Singh and L. K. Awasthi, “An efficient cluster head election based on optimized genetic algorithm for movable sinks in IoT enabled HWSNs,” Applied Soft Computing, vol. 107, pp. 107318, 2021.

Mullai and K. Mani, “Enhancing the security in RSA and elliptic curve cryptography based on addition chain using simplified swarm optimization and particle swarm optimization for mobile devices,” International Journal of Information Technology, vol. 13, pp. 551–564, 2021.

S. K. Mousavi and A. Ghaffari, “Data cryptography in the internet of things using the artificial bee colony algorithm in a smart irrigation system,” Journal of Information Security and Applications, vol. 61, pp. 102945, 2021.

D. W. Sims, D. Righton and J. W. Pitchford, “Minimizing errors in identifying Lévy flight behaviour of organisms,” Journal of Animal Ecology, vol. 76, no. 2, pp. 222–229, 2007.

Lévy, “Théorie de l’addition des variables aléatoires,” Bulletin de la Société Mathématique de France, vol. 67, pp. 1–41, 1939.

X. S. Yang and S. Deb, “Engineering optimisation by cuckoo search,” International Journal of Mathematical Modelling and Numerical Optimisation, vol. 1, no. 4, pp. 330–343, 2010.

Conti, N. Dragoni and V. Lesyk, “A survey of man in the middle attacks,” IEEE Communications Surveys & Tutorials, vol. 18, no. 3, pp. 2027–2051, 2016.

L. Zou, M. Ni, Y. Huang, W. Shi and X. Li, “Hybrid encryption algorithm based on AES and RSA in file encryption,” in Frontier Computing: Theory, Technologies and Applications (FC 2019), vol. 8. Singapore: Springer, pp. 541–551, 2020.

Bafandehkar, S. M. Yasin, R. Mahmod and Z. M. Hanapi, “Comparison of ECC and RSA algorithm in resource constrained devices,” in 2013 Int. Conf. on IT Convergence and Security (ICITCS), Macao, China, pp. 1–3, 2013.

X. S. Yang, “Firefly algorithms for multimodal optimization,” in Int. Symp. on Stochastic Algorithms, Sapporo, Japan, pp. 169–178, 2009.

J. H. Holland, “Genetic algorithms,” Scientific American, vol. 267, no. 1, pp. 66–73, 1992.

Lemma, M. Tolentino and G. Mehari, “Performance analysis on the implementation of data encryption algorithms used in network security,” International Journal of Computer and Information Technology, vol. 4, no. 4, pp. 711–717, 2015.

Mwitia, Shawn Muthomi, and Davies Rene Segera. "An Aggressive Cuckoo Search Algorithm for Optimum Power Allocation in a CDMA-Based Cellular Network." The Scientific World Journal 2022 (2022).

Sabonchi, Arkan Kh Shakr, and Zainab Hasim Obaid. "Ensuring Information Security in Smart Door Lock Systems Using the Cuckoo Search Algorithm."

Srinivasarao, Popuri, and Aravapalli Rama Satish. "A Novel Hybrid Optimization Algorithm for Materialized View Selection from Data Warehouse Environments." Computer Systems Science & Engineering 47.2 (2023).

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Published

23.02.2024

How to Cite

Balaji, A. ., Priyadarsini, C. I. ., Rao, E. N. ., Kumar, G. B. ., Nagaraju, A. ., Srikanth, N. ., & Srinivasarao, P. . (2024). Handling Information Security Wisely Utilising the Aggressive Cuckoo Search Algorithm in Lock Systems. International Journal of Intelligent Systems and Applications in Engineering, 12(16s), 633–645. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/4901

Issue

Vol. 12 No. 16s (2024)

Section

Research Article

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