National University of Computer and Emerging Sciences

About: National University of Computer and Emerging Sciences is a education organization based out in Islamabad, Pakistan. It is known for research contribution in the topics: Computer science & The Internet. The organization has 1506 authors who have published 2438 publications receiving 26786 citations.

A novel technique for the construction of strong S-boxes based on chaotic Lorenz systems

Abstract: In cryptographic systems, the encryption process relies on the nonlinear mapping of original data or plaintext to the secure data. The mapping of data is facilitated by the application of the substitution process embedded in the cipher. It is desirable to have resistance against differential cryptanalysis, which assists in providing clues about the composition of keys, and linear secret system, where a simple approximation is created to emulate the original cipher characteristics. In this work, we propose the use of nonlinear functional chaos-based substitution process which employs a continuous time Lorenz system. The proposed substitution system eliminates the need of independent round keys in a substitution-permutation network. The performance of the new substitution box is evaluated by nonlinearity analysis, strict avalanche criterion, bit independence criterion, linear approximation probability, and differential approximation probability.

Construction of S-box based on chaotic Boolean functions and its application in image encryption

Abstract: In numerous encryption frameworks, the first information is changed into encoded form by applying nonlinear substitutions and affecting diffusion. The goal of the nonlinear change is to accomplish high level of randomness in the image content. The choice of the source of randomness is critical because the success in cryptanalysis is demarked by the characteristics identified in the encrypted data. The chaotic frameworks show random conduct that is suitable for encryption applications where nonlinear transformations are needed in the middle of plaintext and the scrambled information. The application of nonlinear functional chaos-based system with embedded chaotic systems and binary chaotic sequences can prompt randomness and diffusion in the information. In addition to the high state of randomness, the requirement for various round keys is needed in a run of the mill substitution---permutation process. The proposed strategy kills the requirement for different round keys, which is suitable for high-speed communication frameworks. The measurable analyses performed on the proposed nonlinear algorithm which show improvement in encryption quality and safety against numerous brute-force and statistical attacks. Also, the proposed framework demonstrates high safety against differential and linear cryptanalysis.

Keystroke-Based User Identification on Smart Phones

Abstract: Smart phones are now being used to store users' identities and sensitive information/data. Therefore, it is important to authenticate legitimate users of a smart phone and to block imposters. In this paper, we demonstrate that keystroke dynamics of a smart phone user can be translated into a viable features' set for accurate user identification. To this end, we collect and analyze keystroke data of 25 diverse smart phone users. Based on this analysis, we select six distinguishing keystroke features that can be used for user identification. We show that these keystroke features for different users are diffused and therefore a fuzzy classifier is well-suited to cluster and classify them. We then optimize the front-end fuzzy classifier using Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) as back-end dynamic optimizers to adapt to variations in usage patterns. Finally, we provide a novel keystroke dynamics based PIN (Personal Identification Number) verification mode to ensure information security on smart phones. The results of our experiments show that the proposed user identification system has an average error rate of 2% after the detection mode and the error rate of rejecting legitimate users drops to zero in the PIN verification mode. We also compare error rates (in terms of detecting both legitimate users and imposters) of our proposed classifier with 5 existing state-of-the-art techniques for user identification on desktop computers. Our results show that the proposed technique consistently and considerably outperforms existing schemes.

Image segmentation using fuzzy clustering: A survey

Abstract: This paper presents a survey of latest image segmentation techniques using fuzzy clustering. Fuzzy C-Means (FCM) Clustering is the most wide spread clustering approach for image segmentation because of its robust characteristics for data classification. In this paper, four image segmentation algorithms using clustering, taken from the literature are reviewed. To address the drawbacks of conventional FCM, all these approaches have modified the objective function of conventional FCM and have incorporated spatial information in the objective function of the standard FCM. The techniques that have been reviewed in this survey are Segmentation for noisy medical images with spatial probability, Novel Fuzzy C-Means Clustering (NFCM), Fuzzy Local Information C-Means (FLICM) Clustering Algorithm and Improved Spatial Fuzzy C-Means Clustering (ISFCM) algorithm.

Emerging Smart Logistics and Transportation Using IoT and Blockchain

Abstract: Transportation and logistics management play a vital role in the development of a country With the advancement of the Internet of Things (IoT) devices, smart transportation is becoming a reality However, these abundant connected IoT devices are vulnerable to security attacks Recently, Blockchain has emerged as one of the most widely accepted technologies for trusted, secure and decentralized intelligent transportation systems This research study aims to contribute to the field of logistics and transportation by exploring the potential of IoT and Blockchain technology in smart logistics and transportation We propose a layered framework, namely BCTLF, for smart logistics and transportation that integrates IoT and Blockchain to provide an intelligent logistics and transportation system Finally, we present two real-life IoT and Blockchain-based case studies to highlight the contribution of IoT and Blockchain in logistics and transportation