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Ether-IoT:A Realtime Lightweight and Scalable Blockchain-Enabled Cache Algorithm for IoT Access Control

Computers, Materials & Continua 2023年第5期75卷 3797-3815页

作者： Hafiz Adnan Hussain Zulkefli Mansor zarina shukur Uzma Jafar Universiti Kebangsaan Malaysia Bangi43000Malaysia

Several unique characteristics of Internet of Things(IoT)devices,such as distributed deployment and limited storage,make it challenging for standard centralized access control systems to enable access control in today’s large-scale IoT *** solve these challenges,this study presents an IoT access control system called Ether-IoT based on the Ethereum Blockchain(BC)infrastructure with Attribute-Based Access Control(ABAC).Access Contract(AC),Cache Contract(CC),Device Contract(DC),and Policy Contract(PC)are the four central smart contracts(SCs)that are included in the proposed *** offers a way to save user characteristics in a local cache system to avoid delays during transactions between BC and IoT *** is the fundamental program users typically need to run to build an access control *** offers a means for storing the resource data created by devices and a method for querying that *** offers administrative settings to handle ABAC policies on users’***-IoT,combined with ABAC and the BC,enables IoT access control management that is decentralized,fine-grained and dynamically *** research gives a real-world case study to illustrate the suggested framework’s *** the end,a simulation experiment is performed to evaluate the system’s *** ensure data integrity in dispersed systems,the results show that Ether-IoT can sustain high throughput in contexts with a large number of requests.

关键词： Blockchain Internet of Things IoT access control ABAC Ethereum distributed system

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High-Secured Image LSB Steganography Using AVL-Tree with Random RGB Channel Substitution

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Computers, Materials & Continua 2024年第10期81卷 183-211页

作者： Murad Njoum Rossilawati Sulaiman zarina shukur Faizan Qamar Center of Cyber Security Faculty of Information Science and TechnologyUniversiti Kebangsaan MalaysiaBangiSelangor43600Malaysia Computer Science and Cyber Security Faculty of Engineering and Information TechnologyBirZeit UniversityBirZeitRamallahP.O.Box 14Palestine

Random pixel selection is one of the image steganography methods that has achieved significant success in enhancing the robustness of hidden *** property makes it difficult for steganalysts’powerful data extraction tools to detect the hidden data and ensures high-quality stego image ***,using a seed key to generate non-repeated sequential numbers takes a long time because it requires specific mathematical *** addition,these numbers may cluster in certain *** hidden data in these clustered pixels will reduce the image quality,which steganalysis tools can ***,this paper proposes a data structure that safeguards the steganographic model data and maintains the quality of the stego *** paper employs the AdelsonVelsky and Landis(AVL)tree data structure algorithm to implement the randomization pixel selection technique for data *** AVL tree algorithm provides several advantages for image ***,it ensures balanced tree structures,which leads to efficient data retrieval and insertion ***,the self-balancing nature of AVL trees minimizes clustering by maintaining an even distribution of pixels,thereby preserving the stego image *** data structure employs the pixel indicator technique for Red,Green,and Blue(RGB)channel *** green channel serves as the foundation for building a balanced binary ***,the sender identifies the colored cover image and secret *** sender will use the two least significant bits(2-LSB)of RGB channels to conceal the data’s size and associated *** next step is to create a balanced binary tree based on the green *** the channel pixel indicator on the LSB of the green channel,we can conceal bits in the 2-LSB of the red or blue *** first four levels of the data structure tree will mask the data size,while subsequent levels will conceal the remaining digits of secret *** embedding the bits i

关键词： Image steganography pixel random selection(PRS) AVL tree peak signal-to-noise ratio(PSNR) imperceptibility capacity

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Process Mining Discovery Techniques for Software Architecture Lightweight Evaluation Framework

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Computers, Materials & Continua 2023年第3期74卷 5777-5797页

作者： Mahdi Sahlabadi Ravie Chandren Muniyandi zarina shukur Faizan Qamar Syed Hussain Ali Kazmi Centre for Cyber Security Faculty of Information Science and Technology(FTSM)Universiti Kebangsaan Malaysia(UKM)Bangi43600SelangorMalaysia

This research recognizes the limitation and challenges of adaptingand applying Process Mining as a powerful tool and technique in theHypothetical Software Architecture (SA) Evaluation Framework with thefeatures and factors of lightweightness. Process mining deals with the largescalecomplexity of security and performance analysis, which are the goalsof SA evaluation frameworks. As a result of these conjectures, all ProcessMining researches in the realm of SA are thoroughly reviewed, and ninechallenges for Process Mining Adaption are recognized. Process mining isembedded in the framework and to boost the quality of the SA model forfurther analysis, the framework nominates architectural discovery algorithmsFlower, Alpha, Integer Linear Programming (ILP), Heuristic, and Inductiveand compares them vs. twelve quality criteria. Finally, the framework’s testingon three case studies approves the feasibility of applying process mining toarchitectural evaluation. The extraction of the SA model is also done by thebest model discovery algorithm, which is selected by intensive benchmarkingin this research. This research presents case studies of SA in service-oriented,Pipe and Filter, and component-based styles, modeled and simulated byHierarchical Colored Petri Net techniques based on the cases’ *** this framework dealswith the system’s log files obtainedfrom SA simulation. Applying process mining is challenging, especially for aSA evaluation framework, as it has not been done yet. The research recognizesthe problems of process mining adaption to a hypothetical lightweightSA evaluation framework and addresses these problems during the solutiondevelopment.

关键词： Software architecture process mining hierarchical colored petri Net architectural discovery algorithms model discovery algorithm

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