Public Key Cryptography Using Harmony Search Algorithm
TL;DR: The adaptation of the HSA tries to provide a fast key generation mechanism with a feasible implementation to provide privacy requirement for viability of modern information sharing through cyberspace.
Abstract: Privacy is a very important requirement for viability of modern information sharing through cyberspace and the modern cryptology is ensuring success. Harmony Search Algorithm (HSA) is a new meta-heuristic computation technique inspired from musical improvisation techniques, where searching for a perfect harmony is the objective of this technique. Public Key Cryptography heavily relies on key pairs which are large prime numbers. Our adaptation of the HSA tries to provide a fast key generation mechanism with a feasible implementation. The keys are ranked based on their harmony and the best harmony is selected as the result of the search which in turn is used to generate the key pair of RSA, a Public Key Cryptography technique as a test of effectiveness and success.
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01 Jan 2020
TL;DR: The main contribution of this article is the proposed use of the theory of interval type-2 fuzzy logic to the dynamic adjustment of parameters for the harmony search algorithm and then its application to the optimal design of interval types of fuzzy logic controller.
Abstract: At the present time there are several types of metaheuristics which have been used to solve various types of problems in the real world. These metaheuristics contain parameters that are usually fixed throughout the iterations. However, various techniques exist to adjust the parameters of an algorithm such as probabilistic, fuzzy logic, among others. This work describes the methodology and equations for building Triangular and Gaussian interval type-2 membership functions, and this methodology was applied to the optimization of a benchmark control problem with an interval type-2 fuzzy logic controller. To validate in the best way the effect of uncertainty we perform experiments using noise (Pulse generator) and without noise. Also, a statistical z-test is presented to verify the effectiveness of the proposed method. The main contribution of this article is the proposed use of the theory of interval type-2 fuzzy logic to the dynamic adjustment of parameters for the harmony search algorithm and then its application to the optimal design of interval type-2 fuzzy logic controller.
13 citations
01 Sep 2021
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.
6 citations
References
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TL;DR: Artificial Bee Colony (ABC) Algorithm is an optimization algorithm based on the intelligent behaviour of honey bee swarm that is used for optimizing multivariable functions and the results showed that ABC outperforms the other algorithms.
Abstract: Swarm intelligence is a research branch that models the population of interacting agents or swarms that are able to self-organize. An ant colony, a flock of birds or an immune system is a typical example of a swarm system. Bees' swarming around their hive is another example of swarm intelligence. Artificial Bee Colony (ABC) Algorithm is an optimization algorithm based on the intelligent behaviour of honey bee swarm. In this work, ABC algorithm is used for optimizing multivariable functions and the results produced by ABC, Genetic Algorithm (GA), Particle Swarm Algorithm (PSO) and Particle Swarm Inspired Evolutionary Algorithm (PS-EA) have been compared. The results showed that ABC outperforms the other algorithms.
6,377 citations
01 Dec 2009
TL;DR: A new meta-heuristic algorithm, called Cuckoo Search (CS), is formulated, based on the obligate brood parasitic behaviour of some cuckoo species in combination with the Lévy flight behaviour ofSome birds and fruit flies, for solving optimization problems.
Abstract: In this paper, we intend to formulate a new meta-heuristic algorithm, called Cuckoo Search (CS), for solving optimization problems. This algorithm is based on the obligate brood parasitic behaviour of some cuckoo species in combination with the Levy flight behaviour of some birds and fruit flies. We validate the proposed algorithm against test functions and then compare its performance with those of genetic algorithms and particle swarm optimization. Finally, we discuss the implication of the results and suggestion for further research.
5,521 citations
01 Feb 2001
TL;DR: A new heuristic algorithm, mimicking the improvisation of music players, has been developed and named Harmony Search (HS), which is illustrated with a traveling salesman problem (TSP), a specific academic optimization problem, and a least-cost pipe network design problem.
Abstract: Many optimization problems in various fields have been solved using diverse optimization al gorithms. Traditional optimization techniques such as linear programming (LP), non-linear programming (NL...
5,136 citations
TL;DR: A new method of estimating the entropy and redundancy of a language is described, which exploits the knowledge of the language statistics possessed by those who speak the language, and depends on experimental results in prediction of the next letter when the preceding text is known.
Abstract: A new method of estimating the entropy and redundancy of a language is described. This method exploits the knowledge of the language statistics possessed by those who speak the language, and depends on experimental results in prediction of the next letter when the preceding text is known. Results of experiments in prediction are given, and some properties of an ideal predictor are developed.
2,556 citations
06 Jul 1999
TL;DR: This work defines the Ant Colony Optimization (ACO) meta-heuristic by defining these algorithms in a common framework by defining the foraging behavior of ant colonies as a meta- heuristic.
Abstract: Recently, a number of algorithms inspired by the foraging behavior of ant colonies have been applied to the solution of difficult discrete optimization problems. We put these algorithms in a common framework by defining the Ant Colony Optimization (ACO) meta-heuristic. A couple of paradigmatic examples of applications of these novel meta-heuristic are given, as well as a brief overview of existing applications.
1,764 citations