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A Review on the security of the Ethereum-Based DeFi Ecosystem

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Computer Modeling in Engineering & Sciences 2024年第4期139卷 69-101页

作者： Yue Xue Dunqiu Fan Shen Su Jialu Fu Ning Hu Wenmao Liu Zhihong Tian Cyberspace Institute of Advanced Technology Guangzhou UniversityGuanzhou510000China Innovation Center NSFOCUS Inc.Beijing100089China Engineering Research Center of Integration and Application of Digital Learning Technology Ministry of EducationBeijing100816China

Decentralized finance(DeFi)is a general term for a series of financial products and *** is based on blockchain technology and has attracted people’s attention because of its open,transparent,and intermediary *** them,the DeFi ecosystem based on Ethereum-based blockchains attracts the most ***,the current decentralized financial system built on the Ethereum architecture has been exposed to many smart contract vulnerabilities during the last few ***,we believe it is time to improve the understanding of the prevailing Ethereum-based DeFi ecosystem security *** that end,we investigate the Ethereum-based DeFi security issues:1)inherited from the real-world financial system,which can be solved by macro-control;2)induced by the problems of blockchain architecture,which require a better blockchain platform;3)caused by DeFi invented applications,which should be focused on during the project *** on that,we further discuss the current solutions and potential directions ofDeFi *** to our research,we could provide a comprehensive vision to the research community for the improvement of Ethereum-basedDeFi ecosystem security.

关键词： Blockchain smart contract decentralized finance DeFi security

security Analysis in Smart Agriculture: Insights from a Cyber-Physical System Application

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Computers, Materials & Continua 2024年第6期79卷 4781-4803页

作者： Ahmed Redha Mahlous College of Computer and Information Sciences Prince Sultan UniversityRiyadh11586Saudia Arabia

Smart agriculture modifies traditional farming practices,and offers innovative approaches to boost production and sustainability by leveraging contemporary *** today’s world where technology is everything,these technologies are utilized to streamline regular tasks and procedures in agriculture,one of the largest and most significant industries in every *** research paper stands out from existing literature on smart agriculture security by providing a comprehensive analysis and examination of security issues within smart agriculture *** into three main sections-security analysis,system architecture and design and risk assessment of Cyber-Physical Systems(CPS)applications-the study delves into various elements crucial for smart farming,such as data sources,infrastructure components,communication protocols,and the roles of different stakeholders such as farmers,agricultural scientists and researchers,technology providers,government agencies,consumers and many *** contrast to earlier research,this work analyzes the resilience of smart agriculture systems using approaches such as threat modeling,penetration testing,and vulnerability *** discoveries highlight the concerns connected to unsecured communication protocols,possible threats from malevolent actors,and vulnerabilities in IoT ***,the study suggests enhancements for CPS applications,such as strong access controls,intrusion detection systems,and encryption *** addition,risk assessment techniques are applied to prioritize mitigation tactics and detect potential hazards,addressing issues like data breaches,system outages,and automated farming process *** research sets itself apart even more by presenting a prototype CPS application that makes use of a digital temperature *** application was first created using a Tinkercad simulator and then using actual hardware with Arduino *** CPS application’s defenses against p

关键词： Smart agriculture cyber-physical system IoT security temperature sensor threats vulnerabilities

Systematic security Guideline Framework through Intelligently Automated Vulnerability Analysis

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Computers, Materials & Continua 2024年第3期78卷 3867-3889页

作者： Dahyeon Kim Namgi Kim Junho Ahn Computer Information Technology Korea National University of TransportationChungju27469Korea Department of AI Computer Science and Engineering Kyonggi UniversitySuwon16227Korea

This research aims to propose a practical framework designed for the automatic analysis of a product’s comprehensive functionality and security vulnerabilities,generating applicable guidelines based on real-world *** existing analysis of software security vulnerabilities often focuses on specific features or *** partial and arbitrary analysis of the security vulnerabilities makes it challenging to comprehend the overall security vulnerabilities of the *** key novelty lies in overcoming the constraints of partial *** proposed framework utilizes data from various sources to create a comprehensive functionality profile,facilitating the derivation of real-world security *** guidelines are dynamically generated by associating functional security vulnerabilities with the latest Common Vulnerabilities and Exposure(CVE)and Common Vulnerability Scoring System(CVSS)scores,resulting in automated guidelines tailored to each *** guidelines are not only practical but also applicable in real-world software,allowing for prioritized security *** proposed framework is applied to virtual private network(VPN)software,wherein a validated Level 2 data flow diagram is generated using the Spoofing,Tampering,Repudiation,Information Disclosure,Denial of Service,and Elevation of privilege(STRIDE)technique with references to various papers and examples from related *** analysis resulted in the identification of a total of 121 *** successful implementation and validation demonstrate the framework’s efficacy in generating customized guidelines for entire systems,subsystems,and selected modules.

关键词： Framework automation vulnerability analysis security guidelines

A Holistic Secure Communication Mechanism Using a Multilayered Cryptographic Protocol to Enhanced security

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Computers, Materials & Continua 2024年第3期78卷 4417-4452页

作者： Fauziyah Zhaoshun Wang Mujahid Tabassum School of Computer and Communication Engineering University of Science and TechnologyBeijing100000China Noroff School of Technology and Digital Media(Noroff Accelerate) Noroff University CollegeKristiansand4612Norway

In an era characterized by digital pervasiveness and rapidly expanding datasets,ensuring the integrity and reliability of information is *** cyber threats evolve in complexity,traditional cryptographic methods face increasingly sophisticated *** article initiates an exploration into these challenges,focusing on key exchanges(encompassing their variety and subtleties),scalability,and the time metrics associated with various cryptographic *** propose a novel cryptographic approach underpinned by theoretical frameworks and practical *** to this approach is a thorough analysis of the interplay between Confidentiality and Integrity,foundational pillars of information *** method employs a phased strategy,beginning with a detailed examination of traditional cryptographic processes,including Elliptic Curve Diffie-Hellman(ECDH)key *** also delve into encrypt/decrypt paradigms,signature generation modes,and the hashes used for Message Authentication Codes(MACs).Each process is rigorously evaluated for performance and *** gain a comprehensive understanding,a meticulously designed simulation was conducted,revealing the strengths and potential improvement areas of various ***,our cryptographic protocol achieved a confidentiality metric of 9.13 in comprehensive simulation runs,marking a significant advancement over existing ***,with integrity metrics at 9.35,the protocol’s resilience is further *** metrics,derived from stringent testing,underscore the protocol’s efficacy in enhancing data security.

关键词： Cryptographic security privacy preservation decryption integrity

Network security Enhanced with Deep Neural Network-Based Intrusion Detection System

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Computers, Materials & Continua 2024年第7期80卷 1457-1490页

作者： Fatma S.Alrayes Mohammed Zakariah Syed Umar Amin Zafar Iqbal Khan Jehad Saad Alqurni Information Systems Department College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia College of Computer and Information Sciences King Saud UniversityRiyadh11362Saudi Arabia College of Computer and Information Sciences Prince Sultan UniversityRiyadh11586Saudi Arabia Department of Educational Technologies College of EducationImam Abdulrahman Bin Faisal UniversityP.O.Box 1982Dammam31441Saudi Arabia

This study describes improving network security by implementing and assessing an intrusion detection system(IDS)based on deep neural networks(DNNs).The paper investigates contemporary technical ways for enhancing intrusion detection performance,given the vital relevance of safeguarding computer networks against harmful *** DNN-based IDS is trained and validated by the model using the NSL-KDD dataset,a popular benchmark for IDS *** model performs well in both the training and validation stages,with 91.30%training accuracy and 94.38%validation ***,the model shows good learning and generalization capabilities with minor losses of 0.22 in training and 0.1553 in ***,for both macro and micro averages across class 0(normal)and class 1(anomalous)data,the study evaluates the model using a variety of assessment measures,such as accuracy scores,precision,recall,and F1 *** macro-average recall is 0.9422,the macro-average precision is 0.9482,and the accuracy scores are ***,macro-averaged F1 scores of 0.9245 for class 1 and 0.9434 for class 0 demonstrate the model’s ability to precisely identify anomalies *** research also highlights how real-time threat monitoring and enhanced resistance against new online attacks may be achieved byDNN-based intrusion detection systems,which can significantly improve network *** study underscores the critical function ofDNN-based IDS in contemporary cybersecurity procedures by setting the foundation for further developments in this *** research aims to enhance intrusion detection systems by examining cooperative learning techniques and integrating up-to-date threat knowledge.

关键词： Machine-Learning Deep-Learning intrusion detection system security privacy deep neural network NSL-KDD Dataset

Adaptive Marine Predator Optimization Algorithm(AOMA)-Deep Supervised Learning Classification(DSLC)based IDS framework for MANET security

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Intelligent and Converged Networks 2024年第1期5卷 1-18页

作者： M.Sahaya Sheela A.Gnana Soundari Aditya Mudigonda C.Kalpana K.Suresh K.Somasundaram Yousef Farhaoui Department of Electronics and Communication Engineering Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and TechnologyChennai 600069India Department of Computer Science and Engineering Saveetha School of EngineeringSIMATSChennai 602105India JNIAS School of Planning and Architecture Hyderabad 500034India Department of Computer Science and Engineering NPR College of Engineering and TechnologyNatham Dindigul 624401India Department of Computer Science and Engineering PSNA College of Engineering and TechnologyPoolangulathupatti 620009India Department of Computer Science and Engineering Sri Muthukumaran Institute of TechnologyChennai 600069India Department of Computer Science Moulay Ismail UniversityMeknes 5003Morocco

Due to the dynamic nature and node mobility,assuring the security of Mobile Ad-hoc Networks(MANET)is one of the difficult and challenging tasks *** MANET,the Intrusion Detection System(IDS)is crucial because it aids in the identification and detection of malicious attacks that impair the network’s regular *** machine learning and deep learning methodologies are used for this purpose in the conventional works to ensure increased security of ***,it still has significant flaws,including increased algorithmic complexity,lower system performance,and a higher rate of ***,the goal of this paper is to create an intelligent IDS framework for significantly enhancing MANET security through the use of deep learning ***,the min-max normalization model is applied to preprocess the given cyber-attack datasets for normalizing the attributes or fields,which increases the overall intrusion detection performance of ***,a novel Adaptive Marine Predator Optimization Algorithm(AOMA)is implemented to choose the optimal features for improving the speed and intrusion detection performance of ***,the Deep Supervise Learning Classification(DSLC)mechanism is utilized to predict and categorize the type of intrusion based on proper learning and training *** evaluation,the performance and results of the proposed AOMA-DSLC based IDS methodology is validated and compared using various performance measures and benchmarking datasets.

关键词： Intrusion Detection System(IDS) security Mobile Ad-hoc Network(MANET) min-max normalization Adaptive Marine Predator Optimization Algorithm(AOMA) Deep Supervise Learning Classification(DSLC)

Understanding the neighborhoods’in-between spaces on spatial perception,social interaction,and security

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Frontiers of Architectural Research 2024年第1期13卷 21-36页

作者： Lizeth Félix Mariel Organista Autonomous University of Baja California Ensenada 22860Mexico

This study reflects on the impact that the neighborhoods’in-between spaces have on:spatial perception,social interaction,and *** sites,characterized by their abandonment and deterioration,can also be seen as crucial spaces of opportunity for cities,in the architectural,urban and landscape *** paper aims to analyze the sociospatial relationships in the neighborhoods’in-between spaces and examine the impact of inbetween space configuration on urban *** investigation draws on a survey of perception to residents about the requirements for a suitable social interaction in these *** study was developed in a neighborhood in the city periphery,characterized by their social dynamics and location in a nature conservation *** findings indicate that the appropriation process,activities,and collective practices are dependent on the spatial legibility,in this case when this increases,gives rise to improve the habitability and the rehabilitation of the in-between ***,the lack of design on in-between spaces substantially affects the use of these spaces and the social interaction among residents.

关键词： In-between spaces Socio-spatial relationships Habitability Neighborhoods security

Soils for food security

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Frontiers of Agricultural Science and Engineering 2024年第2期11卷 213-215页

作者： Guangzhou WANG Qichao ZHU Junling ZHANG State Key Laboratory of Nutrient Use and Management National Academy of Agriculture Green DevelopmentCollege of Resources and Environmental SciencesChina Agricultural UniversityBeijing 100193China

Food security is among the most fundamental of national interests and productive farmland is essential for secure grain *** the increase of agricultural intensification and the impact of global climate change,the soil... 详细信息

关键词： farmland security earth

Machine Learning Empowered security and Privacy Architecture for IoT Networks with the Integration of Blockchain

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Intelligent Automation & Soft Computing 2024年第2期39卷 353-379页

作者： Sohaib Latif M.Saad Bin Ilyas Azhar Imran Hamad Ali Abosaq Abdulaziz Alzubaidi Vincent Karovic Jr. Department of Computer Science The University of ChenabGujrat50700Pakistan Department of Creative Technologies Air UniversityIslamabad42000Pakistan Computer Science Department College of Computer Science and Information SystemsNajran UniversityNajran66244Saudi Arabia Department of Computer Science Umm Alqura UniversityAlQunfudah28821Saudi Arabia Department of Information Systems Faculty of ManagementComenius University in BratislavaBratislava82005Slovakia

The Internet of Things(IoT)is growing rapidly and impacting almost every aspect of our lives,fromwearables and healthcare to security,traffic management,and fleet management *** has generated massive volumes of data and security,and data privacy risks are increasing with the advancement of technology and network *** access control solutions are inadequate for establishing access control in IoT systems to provide data protection owing to their vulnerability to single-point OF ***,conventional privacy preservation methods have high latency costs and overhead for resource-constrained *** machine learning approaches were also unable to detect denial-of-service(DoS)*** study introduced a novel decentralized and secure framework for blockchain *** avoid single-point OF failure,an accredited access control scheme is incorporated,combining blockchain with local peers to record each transaction and verify the signature to ***-based attribute-based cryptography is implemented to protect data storage privacy by generating threshold parameters,managing keys,and revoking users on the *** innovative contract-based DOS attack mitigation method is also incorporated to effectively validate devices with intelligent contracts as trusted or untrusted,preventing the server from becoming *** proposed framework effectively controls access,safeguards data privacy,and reduces the risk of *** results depict that the suggested framework outperforms the results in terms of accuracy,precision,sensitivity,recall,and F-measure at 96.9%,98.43%,98.8%,98.43%,and 98.4%,respectively.

关键词： Machine learning internet of things blockchain data privacy security Industry 4.0