Data cryptography in the Internet of Things using the artificial bee colony algorithm in a smart irrigation system
01 Sep 2021-Vol. 61, pp 102945
TL;DR: In this article, the authors proposed a security design based on Elliptic-Curve Cryptography (ECC), the SHA-256 (Secure Hash Algorithm 256) algorithm, and the Artificial Bee Colony (ABC) algorithm to boost the security of IoT-based smart irrigation systems.
Abstract: The Internet of Things (IoT) includes various technologies, including sensing devices, Radio-Frequency Identification (RFID), and Microelectromechanical Systems (MEMS). Despite numerous advantages of IoT, security and privacy are important challenges. IoT infrastructures are frequently attacked by different invaders, including white hat hackers whose mission is to test the system's penetrability. Other attacks are orchestrated by adversaries that misuse system vulnerabilities to seize information for personal benefits. Hence, security is a key factor and fundamental requirement of IoT design. Thus, increased cyberattacks call for an appropriate strategic plan to ensure IoT security. Enhancing data security in IoT has proved to be a major concern, and one solution to mitigate this is to apply suitable encryption techniques when storing data in the IoT. An intruder will be able to control IoT devices without physical access if the network is not secure enough. To overcome this challenge, this paper proposes a security design based on Elliptic-Curve Cryptography (ECC), the SHA-256 (Secure Hash Algorithm 256) algorithm, and the Artificial Bee Colony (ABC) algorithm to boost the security of IoT-based smart irrigation systems. The proposed model applies the ABC algorithm to generate the private key for ECC. The results show that the optimal encoding and decoding times were 100 and 150 iterations, respectively. Moreover, compared to 3DES&ECC&SHA-256 and RC4&ECC&SHA-256, the total throughput of the proposed model was about 50.04% and 55.29% higher in encryption and 51.36% and 58.41% higher in decryption. The evaluation indicates a significant improvement (>50%) in the throughput rate. The performance results obtained indicate the efficiency and effectiveness of the proposed scheme in terms of performance and security.
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TL;DR: A novel oscillator with chaotic dynamics is presented and its dynamical properties are investigated, and a method to construct pseudo-random numbers (PRNGs) is proposed, then utilizing the generated PRNG sequence for designing secure substitution boxes (S-boxes) using the proposed PRNG mechanism and the suggested S-box approach.
Abstract: Data security represents an essential task in the present day, in which chaotic models have an excellent role in designing modern cryptosystems. Here, a novel oscillator with chaotic dynamics is presented and its dynamical properties are investigated. Various properties of the oscillator, like equilibria, bifurcations, and Lyapunov exponents (LEs), are discussed. The designed system has a center point equilibrium and an interesting chaotic attractor. The existence of chaotic dynamics is proved by calculating Lyapunov exponents. The region of attraction for the chaotic attractor is investigated by plotting the basin of attraction. The oscillator has a chaotic attractor in which its basin is entangled with the center point. The complexity of the chaotic dynamic and its entangled basin of attraction make it a proper choice for image encryption. Using the effective properties of the chaotic oscillator, a method to construct pseudo-random numbers (PRNGs) is proposed, then utilizing the generated PRNG sequence for designing secure substitution boxes (S-boxes). Finally, a new image cryptosystem is presented using the proposed PRNG mechanism and the suggested S-box approach. The effectiveness of the suggested mechanisms is evaluated using several assessments, in which the outcomes show the characteristics of the presented mechanisms for reliable cryptographic applications.
7 citations
TL;DR: The findings show that the Genetic Algorithm outperforms other algorithms in both the logic and training phases of Weighted Random k Satisfiability, and the quality of the retrieved final neuron states achieved acceptable results.
6 citations
01 Jan 2022
TL;DR: In this paper , a fuzzy neural network-controlled irrigation controller system was developed using the research presented here, which comprises a feedback Fuzzy Neural Network (FNN) controller that keeps track of important system measurements using sensors.
Abstract: Bangladesh is heavily dependent on agriculture for its crop production, food supply, and crop rotation. About 50% of the population in Bangladesh is working in the agriculture sector; agriculture occupies 70% of the country’s territory. To ensure a bountiful harvest, a soil condition suitable for cultivation and the judicious use of irrigation is essential. A fuzzy neural network-controlled irrigation controller system was developed using the research presented here. The system comprises a feedback Fuzzy Neural Network (FNN) controller that keeps track of important system measurements using sensors. The controller bases its findings on crop production, which guides it in determining when it is appropriate to irrigate. MATLAB may assign triangular and trapezoidal membership functions to every input variable. This inference engine uses Max-Min methods, which serve to derive the optimum answer for every case. Also, water consumption is lessened, and freshwater supplies are thereby protected. the system is created and tested for plant growth that reduces water usage by about 50–60% and reduces energy generating costs by the same amount. Improved irrigation management can be achieved when FNN is combined with data logging. By implementing this strategy, the overall energy use, water demand, total energy use, battery, and power control unit expenses can be reduced.
1 citations
01 Jan 2023
TL;DR: In this paper , a hybrid approach using Gray Wolf Optimizer (GWO) and Moth-Flame Optimization (MFO) algorithms was developed and applied to widely used data sets such as NSL-KDD, UNSW-NB15, and CIC IDS 2017, as well as various benchmark functions.
Abstract: This paper addresses the urgent need to detect network security attacks, which have increased significantly in recent years, with high accuracy and avoid the adverse effects of these attacks. The intrusion detection system should respond seamlessly to attack patterns and approaches. The use of metaheuristic algorithms in attack detection can produce near-optimal solutions with low computational costs. To achieve better performance of these algorithms and further improve the results, hybridization of algorithms can be used, which leads to more successful results. Nowadays, many studies are conducted on this topic. In this study, a new hybrid approach using Gray Wolf Optimizer (GWO) and Moth-Flame Optimization (MFO) algorithms was developed and applied to widely used data sets such as NSL-KDD, UNSW-NB15, and CIC IDS 2017, as well as various benchmark functions. The ease of hybridization of the GWO algorithm, its simplicity, its ability to perform global optimal search, and the success of the MFO algorithm in obtaining the best solution suggested that an effective solution would be obtained by combining these two algorithms. For these reasons, the developed hybrid algorithm aims to achieve better results by using the good aspects of both the GWO algorithm and the MFO algorithm. In reviewing the results, it was found that a high level of success was achieved in the benchmark functions. It achieved better results in 12 of the 13 benchmark functions compared. In addition, the success rates obtained according to the evaluation criteria in the different data sets are also remarkable. Comparing the 97.4%, 98.3%, and 99.2% classification accuracy results obtained in the NSL-KDD, UNSW-NB15, and CIC IDS 2017 data sets with the studies in the literature, they seem to be quite successful.
References
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TL;DR: Initially applying his concepts to simply defined artificial systems with limited numbers of parameters, Holland goes on to explore their use in the study of a wide range of complex, naturally occuring processes, concentrating on systems having multiple factors that interact in nonlinear ways.
Abstract: From the Publisher:
Genetic algorithms are playing an increasingly important role in studies of complex adaptive systems, ranging from adaptive agents in economic theory to the use of machine learning techniques in the design of complex devices such as aircraft turbines and integrated circuits. Adaptation in Natural and Artificial Systems is the book that initiated this field of study, presenting the theoretical foundations and exploring applications.
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Initially applying his concepts to simply defined artificial systems with limited numbers of parameters, Holland goes on to explore their use in the study of a wide range of complex, naturally occuring processes, concentrating on systems having multiple factors that interact in nonlinear ways. Along the way he accounts for major effects of coadaptation and coevolution: the emergence of building blocks, or schemata, that are recombined and passed on to succeeding generations to provide, innovations and improvements.
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TL;DR: A state-of-art of lightweight cryptographic primitives which include lightweight block cipher, hash function, stream ciphers, high performance system, and low resources device for IoT environment are discussed in details.
Abstract: There are many emerging areas in which highly constrained devices are interconnected and communicated to accomplish some tasks Nowadays, Internet of Things (IoT) enables many low resources and constrained devices to communicate, compute process and make decision in the communication network In the heterogeneous environments for IoT, there are many challenges and issues like power consumption of devices, limited battery, memory space, performance cost, and security in the Information Communication Technology (ICT) network In this paper, we discuss a state-of-art of lightweight cryptographic primitives which include lightweight block ciphers, hash function, stream ciphers, high performance system, and low resources device for IoT environment in details We analyze many lightweight cryptographic algorithms based on their key size, block size, number of rounds, and structures In addition, we discuss the security architecture in IoT for constrained device environment, and focus on research challenges, issues and solutions Finally, a proposed security scheme with a service scenario for an improvement of resource constrained IoT environment and open issues are discussed
252 citations