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Cogent and Energy Efficient Authentication Protocol for WSN in IoT

Computers, Materials & Continua 2021年第8期68卷 1877-1898页

作者： Tariq Mahmood Butt rabia riaz Chinmay Chakraborty Sanam Shahla Rizvi Anand Paul Department of CS&IT University of Azad Jammu and KashmirMuzaffarabad13100Pakistan Birla Institute of Technology MesraJharkhand814142India Raptor Interactive(Pty)Ltd. Eco BoulevardWitch Hazel AveCenturion0157South Africa The School of Computer Science and Engineering Kyungpook National UniversityDaegu41566Korea

Given the accelerating development of Internet of things(IoT),a secure and robust authentication mechanism is urgently required as a critical architectural *** IoT has improved the quality of everyday life for numerous people in many *** to the predominantly wireless nature of the IoT,connected devices are more vulnerable to security threats compared to wired *** authentication is thus of utmost importance in terms of security on the *** authentication protocols have been proposed in recent years,but most prior schemes do not provide sufficient security for these wireless *** overcome the limitations of previous schemes,we propose an efficient and lightweight authentication scheme called the Cogent Biometric-Based Authentication Scheme(COBBAS).The proposed scheme is based on biometric data,and uses lightweight operations to enhance the efficiency of the network in terms of time,storage,and battery consumption.A formal security analysis of COBBAS using Burrows–Abadi–Needham logic proves that the proposed protocol provides secure mutual *** security verification using the Automated Validation of Internet Security Protocols and Applications tool shows that the proposed protocol is safe against man-in-the-middle and replay *** security analysis further shows that COBBAS protects wireless sensor networks against several security attacks such as password guessing,impersonation,stolen verifier attacks,denial-of-service attacks,and errors in biometric *** protocol also provides user anonymity,confidentiality,integrity,and biometric recovery in acceptable time with reasonable computational cost.

关键词： Internet of things wireless sensor networks authentication Burrows-Abadi-Needham logic fuzzy extractor elliptic curve cryptography

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SwCS: Section-Wise Content Similarity Approach to Exploit Scientific Big Data

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Computers, Materials & Continua 2021年第4期67卷 877-894页

作者： Kashif Irshad Muhammad Tanvir Afzal Sanam Shahla Rizvi Abdul Shahid rabia riaz Tae-Sun Chung Department of Computer Science Capital University of Science and TechnologyIslamabadPakistan Department of Computer Science NAMAL InstituteMianwali42250Pakistan Raptor Interactive(Pty)Ltd. Eco BoulevardWitch Hazel AveCenturion0157South Africa Institute of Computing Kohat University of Science and TechnologyPakistan Department of CS&IT University of Azad Jammu and KashmirMuzaffarabad13100Pakistan Department of Artificial Intelligence Ajou UniversityKorea

The growing collection of scientific data in various web repositories is referred to as Scientific Big Data,as it fulfills the four“V’s”of Big Data—volume,variety,velocity,and *** phenomenon has created new opportunities for startups;for instance,the extraction of pertinent research papers from enormous knowledge repositories using certain innovative methods has become an important task for researchers and ***,the content of the papers are compared to list the relevant papers from a *** conventional method results in a long list of papers that is often impossible to interpret ***,the need for a novel approach that intelligently utilizes the available data is ***,the primary element of the scientific knowledge base is a research article,which consists of various logical sections such as the Abstract,Introduction,Related Work,Methodology,Results,and ***,this study utilizes these logical sections of research articles,because they hold significant potential in finding relevant *** this study,comprehensive experiments were performed to determine the role of the logical sections-based terms indexing method in improving the quality of results(i.e.,retrieving relevant papers).Therefore,we proposed,implemented,and evaluated the logical sections-based content comparisons method to address the research objective with a standard method of indexing *** section-based approach outperformed the standard content-based approach in identifying relevant documents from all classified topics of computer ***,the proposed approach extracted 14%more relevant results from the entire *** the experimental results suggested that employing a finer content similarity technique improved the quality of results,the proposed approach has led the foundation of knowledge-based startups.

关键词： Scientific big data ACM classification term indexing content similarity cosine similarity

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