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Lightweight Key Management Scheme Using Fuzzy Extractor for Wireless Mobile Sensor Network

Computers, Materials & Continua 2022年第4期71卷 1695-1712页

作者： Eid Rehman Ibrahima Kalil Toure Kashif Sultan Muhammad Asif Muhammad Habib Najam Ul Hasan Oh-Young Song Aaqif Afzaal Abbasi Department of Software Engineering Foundation UniversityIslamabad44000Pakistan Centre Informatique Universite Gamal Abdel Nasser deConakryGuinea Department of Software Engineering Bahria University Islamabad CampusIslamabadPakistan gdc ahmad karak Higher Education DepartmentKhyber PakhtunkhwaPakistan Department of Electrical and Computer Engineering Dhofar UniversitySalalahOman Department of Software Sejong UniversitySeoul05006Korea

The mature design of wireless mobile sensor network makes it to be used in vast verities of applications including from home used to the security *** such types of applications based on wireless mobile sensor network are generally using real time data,most of them are interested in real time communication directly from cluster head of cluster instead of a base station in cluster *** would be possible if an external user allows to directly access real time data from the cluster head in cluster wireless mobile sensor network instead of accessing data from base *** this leads to a serious security breach and degrades the performance of any security protocol available in this *** existing schemes for authentication and cluster key management for external users,exchange a number of messages between cluster head and base station to allow external to access real time data from the base station instead of cluster *** increase communication cost and delay in such real time access *** handle this critical issue in cluster wireless mobile sensor network,we propose a lightweight authentication and key management scheme using a fuzzy *** this scheme,any external user can access data directly from the cluster head of any cluster without the involvement of the base *** proposed scheme only uses the one-way hash functions and bitwise XOR operations,apart from the fuzzy extractor method for the user biometric verification at the login *** presented scheme supports scalability for an increasing number of nodes using *** proposed scheme increases the life-time of the network by decreasing the key pool size.

关键词： Fuzzy extractor user authentication key management cluster session key wireless mobile sensor network

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Translation of English Language into Urdu Language Using LSTM Model

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Computers, Materials & Continua 2023年第2期74卷 3899-3912页

作者： Sajadul Hassan Kumhar Syed Immamul Ansarullah Akber Abid Gardezi Shafiq ahmad Abdelaty Edrees Sayed Muhammad Shafiq SSSUTMS Sehore466001India Department of Computer Science GDC SumbalJ&K193502India Department of Computer Science COMSATS University IslamabadIslamabad45550Pakistan Industrial Engineering Department College of EngineeringKing Saud UniversityP.O.Box 800Riyadh11421Saudi Arabia Department of Information and Communication Engineering Yeungnam UniversityGyeongsan38541Korea

English to Urdu machine translation is still in its beginning and lacks simple translation methods to provide motivating and adequate English to Urdu *** order tomake knowledge available to the masses,there should be mechanisms and tools in place to make things understandable by translating from source language to target language in an automated *** translation has achieved this goal with encouraging *** decoding the source text into the target language,the translator checks all the characteristics of the *** achieve machine translation,rule-based,computational,hybrid and neural machine translation approaches have been proposed to automate the *** this research work,a neural machine translation approach is employed to translate English text into *** Short Term Short Model(LSTM)Encoder Decoder is used to translate English to *** various steps required to perform translation tasks include preprocessing,tokenization,grammar and sentence structure analysis,word embeddings,training data preparation,encoder-decoder models,and output text *** results show that the model used in the research work shows better performance in *** results were evaluated using bilingual research metrics and showed that the test and training data yielded the highest score sequences with an effective length of ten(10).

关键词： Machine translation Urdu language word embedding

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