Saibal K. Pal

A hybrid Firefly Algorithm using genetic operators for the cryptanalysis of a monoalphabetic substitution cipher

The monoalphabetic substitution cipher encrypts a given text by replacing every letter in the text with a different letter according to some predefined scheme. The cryptanalysis of this cipher involves the identification of this scheme using known language statistical data. The firefly algorithm (FA) is a metaheuristic algorithm, inspired by the flashing behavior of fireflies. This paper discusses the integration of the operators of mutation and crossover commonly used in Genetic Algorithms with the Firefly Algorithm for cryptanalysis of the monoalphabetic substitution cipher.

Design of a New Block Cipher Based on Conditional Encryption

In today’s digital world, encryption has become a prerequisite for many applications requiring data transfer over open and insecure networks. In addition, the advent and fast evolution of mobile technologies has facilitated the need for lightweight encryption schemes which prove to be strong as well as computationally less expensive than the present day standard ciphers. With this as the source of motivation, the paper proposes a new 128-bit block cipher using 128-bit key and performs 8 rounds of operations. Flexibility in the design paves way for extending the block size as well as the key size. The basic strength of the scheme is the conditional processing and the use of non-linear operations during key expansion to generate round keys and the encryption process. Use of simple negation, shift, XOR and substitution operations makes the scheme computationally efficient and less expensive for high bandwidth applications. Results obtained for different types of inputs show almost equal distribution of 0’s and 1’s in the cipher. Also, change in the cipher with one bit change in the key or plain text is also drastic and depicts strict avalanche effect. Results indicate the strength of the scheme which is also computationally cheaper than many other standard block ciphers.

A New Cryptographic Hash Function based on Latin Squares and Non-linear Transformations

In this paper, we propose a new and efficient cryptographic hash function based on random Latin squares and non-linear transformations. The developed scheme satisfies basic as well as desirable properties of an ideal hash function. Use of repeated lookup on Latin squares, non-linear transformations and complex shift operations further increase the strength of our cryptographic hash function at a low computational overhead. It also ensures pre-image resistance and collision resistance as required for the present day lightweight cryptographic applications.

Intelligent Energy Conservation: Indoor Temperature Forecasting with Extreme Learning Machine

At present, most of the buildings are using process of heating, ventilation and air conditioning (HVAC)-systems. HVAC systems are also responsible for consumption of huge amount of energy. Home automation techniques are being used to reduce the waste of resources especially energy that is available to us in the form of temperature, electricity, water, sunlight, etc. Forecasting and predicting the future demand of the energy can help us to maintain and to reduce the cost of energy in the buildings. In this paper, we use the experiments the small medium large system (SML system) which is the house built at the university of CEU cardinal Herrera (CEU-UCH) for competition named Solar Decathlon 2013. With the data available from this experiments, we try to predict and forecast the future temperature condition intelligently for energy conservation with the model based on Extreme Learning Machine (ELM). This will help in determining the energy needs of the buildings and further will help in efficient utilization and conservation of energy.

Empirically developed integrated ICT framework for PDS in developing countries

Public distribution system is backbone for delivering benefits and other resources to needy population sections. However in developing countries, PDS system is presently not in good state as it is suffering from problems like resources wastage, corruption, leakage, ghost beneficiary, non-accountability, non-transparency, inefficiency, ineffectiveness and delay in resources and services distribution. Governments in developing countries are spending resources in large amount but benefits are not being distributed properly due to severe problems in public distribution systems. Social innovation is required to understand the problem on the basis of facts collections then providing solution with newly available technologies. Existing PDS mechanism is basically sequential or linear transmission systems of benefits delivery. Functioning of PDS mainly works from top to down process which struggles in quickly adapting to changes in social environment, market dynamics and globalization. Information and communication technology can provides social innovational solutions which could be out of intersection of existing PDS, top down to bottom up approach of services and goods delivery of the systems. Most of the fastest growing developing countries are passing through phase of demographic changes where population demands good governance and more of resources from government systems and organizations. In this paper we did empirical study on the basis of prototype of integration ICT framework with existing PDS (IICTF) developed to improve existing PDS system and collected some results which surely can be useful in solving certainly problems of PDS. We are proposing an integrated ICT framework (IICTF) with the existing PDS that can help in solving above mentioned problems. Paper is discussing ways with the help of developed integrated ICT platforms for very effective and efficient, transparent, accounted way of benefit transfer with bidirectional feedback recording.

Design of strong cryptographic schemes based on Latin Squares

Abstract A Latin Square (LS) of order n is an arrangement of n symbols in an n × n matrix form so that each symbol occurs in each row and each column exactly once. The total number of Latin Squares LS(n) of order n increases rapidly with n. This helps to design cryptosystems using Latin Squares with a very large key-space. We define encryption and decryption using simple operations on Latin Squares. Different schemes are designed to make the system secure and easy to implement. Use of keyed permutations and construction of large quasigroups ensure that the system is resistant to different practical cryptographic attacks. Computer implementations show the simplicity and power of these schemes for future cryptographic applications in resource-constrained networks or in mobile devices.

Development of Efficient Algorithms for Quasigroup Generation & Encryption

This paper proposes a lightweight quasigroup based encryption scheme for providing message confidentiality. A fast and efficient method of generating a practically unlimited number of quasigroups of an arbitrary order is presented. The scheme first generates a random quasigroup of order 256 out of the extremely large number of available options. A new method using shift and lookup operations on the quasigroup is then used for encryption/decryption of the data. Experiments conducted on text and visual data prove that enhanced security may be provided using computationally efficient schemes involving simple operations on quasigroups.

Steganography and watermarking of digital images using singular value decomposition

Abstract Singular Value decomposition (SVD), a scheme for matrix diagonalization, has shown promising results in the area of digital image compression. An image matrix is approximated with a rank lower than that of the original image without affecting its perceptual quality. This paper addresses two important aspects of information hiding using SVD namely steganography and watermarking. The lesser significant singular values are used to encode secret messages and carry out hidden communication. Watermarking schemes are designed by slightly modifying the most significant singular values for encoding vital data in the media. By manipulating singular values in different ways, we show the possibility of high-capacity steganography as well as robust watermarking schemes with the ability to resist attacks by active wardens monitoring the communication channels.

Image steganography for wireless networks using the Hadamard transform

The discrete Hadamard transform (DHT) is a simple orthogonal transformation with a set of unique properties. Its 2D version has a separable kernel and can be implemented using fast algorithms. This paper exploits the power of DHT for carrying out steganography using images as containers of hidden information. Computational simplicity and scope for efficient and compact hardware realization makes the scheme suitable for mobile applications. By manipulating different sets of coefficients in the Hadamard transform-domain it is possible to practice steganography satisfying different criteria like transparency, capacity and survivability. It is also shown that this transform has an edge over many other popular transforms for data embedding in real-time over resource constrained wireless networks.

Fuzzy C-Means Clustering and Particle Swarm Optimization based scheme for Common Service Center location allocation

Common Service Centers (CSCs), which are also known as Tele-centers and Rural Kiosks, are important infrastructural options for any country aiming to provide E-Governance services in rural regions. Their main objective is to provide adequate information and services to a country’s rural areas, thereby increasing government-citizen connectivity. Within developing nations, such as India, many CSC allocations are being planned. This study proposes a solution for allocating a CSC for villages in a country according to their E-Governance plan. The Fuzzy C-Means (FCM) algorithm was used for clustering the village dataset and finding a cluster center for CSC allocation, and the Particle Swarm Optimization (PSO) algorithm was used for further optimizing the results obtained from the FCM algorithm based on population. In the context of other studies addressing similar issues, this study highlights the practical implementation of location modeling and analysis. An extensive analysis of the results obtained using a village dataset from India including four prominent states shows that the proposed solution reduces the average traveling costs of villagers by an average of 33 % compared with those of allocating these CSCs randomly in a sorted order and by an average of 11 % relative to centroid allocation using the FCM-based approach only. As compared to traditional approaches like P-Center and P-Median, the proposed scheme is better by 31 % and 14 %, respectively. Therefore, the proposed algorithm yields better results than classical FCM and other types of computing techniques, such as random search & linear programming. This scheme could be useful for government departments managing the allocation of CSCs in various regions. This work should also be useful for researchers optimizing the location allocation schemes used for various applications worldwide.