Malay Kule

Bio: Malay Kule is an academic researcher from Indian Institute of Engineering Science and Technology, Shibpur. The author has contributed to research in topics: Crossbar switch & Very-large-scale integration. The author has an hindex of 5, co-authored 23 publications receiving 130 citations. Previous affiliations of Malay Kule include St. Thomas' College of Engineering and Technology.

A cryptanalytic attack on the knapsack cryptosystem using binary Firefly algorithm

Abstract: This paper presents a binary Firefly Algorithm (FA), for cryptanalysis of knapsack cipher algorithm so as to deduce the meaning of an encrypted message (i.e. to determine a plaintext from the cipher text). The implemented algorithm has been characterized, in this paper, by a number of properties and operations that build up and evolve the fireflies' positions. These include light intensity, distances, attractiveness, and position updating, fitness evaluation. The results of the Firefly algorithm are compared with the results shown by Genetic Algorithm (GA), to discover the plaintext from the cipher text. Experimental results show that binary firefly algorithm is capable of finding correct results more efficiently than GA.

A cryptanalytic attack on Knapsack cipher using Differential Evolution algorithm

Abstract: The paper presents a cryptanalytic attack on Merkle-Hellman Knapsack cipher using Differential Evolution. The Differential Evolution is a stochastic, population based optimization search strategy and uses three typical operators, mutation, crossover and selection, to search the solution space. An initial population is created and a new generation is generated by applying the operators until the solution is obtained. The results of Differential Evolution are compared with the results of Genetic Algorithm (GA) for cryptanalysis of the knapsack cipher. Experimental results show that cryptanalysis of Merkle Hellman Knapsack cipher using Differential Evolution is a better technique than using Genetic Algorithm for this purpose.

High-speed decoder design using memristor-based nano-crossbar architecture

Abstract: Recent advances in physical implementation of the fourth circuit element, memristor, have opened up many promising applications of this device in versatile areas such as neuromorphic systems, memory, and logic design. One way to build logic circuits is to use a regular array of memristor-crossbar that can be configured to implement the required Boolean functions. In this work, the design for a decoder circuit is described using memristor-based nanoscale crossbar architecture. The delay of the proposed circuit is observed to grow linearly with the number of inputs compared to the exponential delay experienced in earlier designs. The proposed design is validated using NgSpice simulation.

A multilevel encryption technique in cloud security

Abstract: Today ensuring security is one of the major concern in cloud environment. Cloud privacy is a one of the tentative issue in cloud computing. As the entire cloud user do not have same demands regarding cloud privacy. Some of the clients are satisfied with current policy where as others are quite concerned about the corresponding privacy. As per the fundamental cloud architecture it is generally deployed via three core service models, namely software as a service, platform as service and infrastructure as a service. But unfortunately these entire delivery services model are vulnerable to a range of security attacks by intelligent intruder. Although government as well as major of the organizations are moving fast towards a secure cloud cryptography offers a wide range of algorithms for cloud security but all these algorithms provide single level encryption. To enhance the security level we have proposed a multilevel security scheme which is more secure than any type of single level encryption. Particularly our technique shows that only authorized user can able to access the cloud data. Our algorithm is fast and safe in both direction such as upload and download of a file. As decryption technique is multilevel so if some data is lost then it is very difficult to decrypt the data.

A comprehensive review of firefly algorithms

Abstract: The firefly algorithm has become an increasingly important tool of Swarm Intelligence that has been applied in almost all areas of optimization, as well as engineering practice. Many problems from various areas have been successfully solved using the firefly algorithm and its variants. In order to use the algorithm to solve diverse problems, the original firefly algorithm needs to be modified or hybridized. This paper carries out a comprehensive review of this living and evolving discipline of Swarm Intelligence, in order to show that the firefly algorithm could be applied to every problem arising in practice. On the other hand, it encourages new researchers and algorithm developers to use this simple and yet very efficient algorithm for problem solving. It often guarantees that the obtained results will meet the expectations.

Nature-Inspired Optimization Algorithms

Abstract: Nature-Inspired Optimization Algorithms provides a systematic introduction to all major nature-inspired algorithms for optimization. The book's unified approach, balancing algorithm introduction, theoretical background and practical implementation, complements extensive literature with well-chosen case studies to illustrate how these algorithms work. Topics include particle swarm optimization, ant and bee algorithms, simulated annealing, cuckoo search, firefly algorithm, bat algorithm, flower algorithm, harmony search, algorithm analysis, constraint handling, hybrid methods, parameter tuning and control, as well as multi-objective optimization. This book can serve as an introductory book for graduates, doctoral students and lecturers in computer science, engineering and natural sciences. It can also serve a source of inspiration for new applications. Researchers and engineers as well as experienced experts will also find it a handy reference.Discusses and summarizes the latest developments in nature-inspired algorithms with comprehensive, timely literatureProvides a theoretical understanding as well as practical implementation hintsProvides a step-by-step introduction to each algorithm

Firefly algorithm: recent advances and applications

Abstract: Nature-inspired metaheuristic algorithms, especially those based on swarm intelligence, have attracted much attention in the last ten years. Firefly algorithm appeared in about five years ago, its literature has expanded dramatically with diverse applications. In this paper, we will briefly review the fundamentals of firefly algorithm together with a selection of recent publications. Then, we discuss the optimality associated with balancing exploration and exploitation, which is essential for all metaheuristic algorithms. By comparing with intermittent search strategy, we conclude that metaheuristics such as firefly algorithm are better than the optimal intermittent search strategy. We also analyse algorithms and their implications for higherdimensional optimisation problems.

The Fourth Element.

Abstract: This tutorial clarifies the axiomatic definition of (v(α); i(β)) circuit elements via a lookup table dubbed an A-pad, of admissible (v; i) signals measured via Gedanken probing circuits. The (v(α); i(β)) elements are ordered via a complexity metric. Under this metric, the memristor emerges naturally as the fourth element, characterized by a state-dependent Ohm's law. A logical generalization to memristive devices reveals a common fingerprint consisting of a dense continuum of pinched hysteresis loops whose area decreases with the frequency ω and tends to a straight line as ω ~ ∞, for all bipolar periodic signals and for all initial conditions. This common fingerprint suggests that the term memristor be used hence-forth as a moniker for memristive devices.

Swarm intelligence based algorithms: a critical analysis

Abstract: Many optimization algorithms have been developed by drawing inspiration from swarm intelligence (SI). These SI-based algorithms can have some advantages over traditional algorithms. In this paper, we carry out a critical analysis of these SI-based algorithms by analyzing their ways to mimic evolutionary operators. We also analyze the ways of achieving exploration and exploitation in algorithms by using mutation, crossover and selection. In addition, we also look at algorithms using dynamic systems, self-organization and Markov chain framework. Finally, we provide some discussions and topics for further research.