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Smart Agriculture-Based Food Quality Analysis with Healthcare security System Using Cloud Machine Learning Model

Remote Sensing in Earth Systems Sciences 2024年第4期7卷 389-398页

作者： Vaithianathan, V. Rebecca, B. Begum, M. Fathima Sundarraj, Antony Allwyn Kumar, M. Prema Kiran, Ajmeera Department of Electronics and Communication Engineering Sri Sivasubramaniya Nadar College of Engineering Kalavakkam Chennai 603110 India Department of Computer Science and Engineering Marri Laxman Reddy Institute of Technology and Management Hyderabad Telangana Dundigal 500043 India Assistant Professor Department of Computer Science and Engineering (Cyber Security) Madanapalle Institute of Technology and Science Andhra Pradesh-517325 Madanapalle India Department of Food Technology Sri Shakthi Institute of Engineering and Technology Coimbatore Tamilnadu Coimbatore India Dept. of ECE Shri Vishnu Engineering College for Women (A) Andhra Pradesh Bhimavaram 534202 India Department of Computer Science and Engineering MLR Institute of Technology Hyderabad India

The primary sector of our Indian economy is agriculture. Today’s world’s most important and vital industries are agriculture and irrigation. Information and communication technology must be used in our agriculture sectors in order to support farmers and agriculturalists in improving their practices across the entire crop-growing and post-harvest processes. It is still challenging to define processed food, even in light of mounting research that suggests consuming more ultra-processed food has negative health effects. This research proposes novel technique in smart agriculture model based on cloud machine learning in cloud machine learning and healthcare system. By leveraging IoT and cloud-based data to create data-driven product decisions, cloud computing in agriculture can assist farmers with smart agriculture practices. Here, the input has been collected as food quality based on smart agriculture using a cloud model as well as processed for noise removal and normalisation. Then, based on this data, the healthcare security system has been analysed using reinforcement adversarial stacked encoder with Markov fuzzy algorithm. The experimental analysis has been carried out for various food quality datasets in terms of training accuracy, random precision, normalised correlation ratio, F-1 score, and AUC. The proposed technique achieved training accuracy of 96%, F-1 score of 94%, random precision of 97%, normalised correlation ratio of 93%, and AUC of 92%. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.

关键词： Adversarial stacked encoder Cloud machine learning Cloud machine learning Healthcare system Smart agriculture

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EBAKE-SE: A novel ECC-based authenticated key exchange between industrial IoT devices using secure element

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Digital Communications and Networks 2023年第2期9卷 358-366页

作者： Chintan Patel Ali Kashif Bashir Ahmad Ali AlZubi Rutvij Jhaveri School of Artificial Intelligence Information Technology and Cyber SecurityRashtriya Raksha UniversityGujaratIndia Department of Computing and Mathematics Manchester Metropolitan UniversityUnited Kingdom Woxsen School of Business Woxsen UniversityIndia Department of Computer Science and Mathematics Lebanese American UniversityBeirutLebanon Computer Science Department Community CollegeKing Saud UniversityP.O.Box 28095Riyadh11437Saudi Arabia Department of Computer Science and Engineering School of TechnologyPandit Deendayal Energy UniversityGujaratIndia

Industrial IoT(IIoT)aims to enhance services provided by various industries,such as manufacturing and product *** suffers from various challenges,and security is one of the key challenge among those *** and access control are two notable challenges for any IIoT based industrial *** IoT based Industry 4.0 enterprise designs networks between hundreds of tiny devices such as sensors,actuators,fog devices and ***,articulating a secure authentication protocol between sensing devices or a sensing device and user devices is an essential step in IoT *** this paper,first,we present cryptanalysis for the certificate-based scheme proposed for a similar environment by Das et *** prove that their scheme is vulnerable to various traditional attacks such as device anonymity,MITM,and *** then put forward an interdevice authentication scheme using an ECC(Elliptic Curve Cryptography)that is highly secure and lightweight compared to other existing schemes for a similar ***,we set forth a formal security analysis using the random oracle-based ROR model and informal security analysis over the Doleve-Yao *** this paper,we present comparison of the proposed scheme with existing schemes based on communication cost,computation cost and security index to prove that the proposed EBAKE-SE is highly efficient,reliable,and trustworthy compared to other existing schemes for an inter-device *** long last,we present an implementation for the proposed EBAKE-SE using MQTT protocol.

关键词： Internet of things Authentication Elliptic curve cryptography Secure key exchange Message Queuing telemetry transport

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Novel Approach for Key-Based Hashing Algorithm

Novel Approach for Key-Based Hashing Algorithm

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2023 IEEE Region 10 Symposium, TENSYMP 2023

作者： Shah, Kaushal Joshi, Kunj Parmar, Dwireph Patel, Dhrumin Padhya, Mukti Pandit Deendayal Energy University Department of Computer Engineering Gandhinagar India National Forensics Sciences University Department of Cyber Security Gandhinagar India

ISBN: (纸本)9781665482585

The existing key-based hashing algorithms, such as HMAC, NMAC and GMAC are highly dependent on pre-existing hashing algorithms such as MD5 and SHA1 which are self-sufficient and independent from the usage of keys. Hence, as a result, the key-based hashing algorithms inherit many aspects of security from its underlying algorithm and usually enhance it. But this feature also accounts for the loopholes in key-based hashing algorithms. The key-based hashing algorithms also inherit the number of rounds, used to hash the message, from its underlying algorithm as well. A fixed number of rounds also allows attacks on particular rounds in the algorithm to crack it. In this paper, a new, independent hashing algorithm is introduced which does not have a fixed number of rounds and is based on basic mathematical and Boolean concepts of Bitwise Operators. The performance and security analysis have shown in results, that the proposed algorithm is resistant towards known attacks on hashing algorithms and a few other attacks proposed by other researchers. Its performance analysis shows that it works in O(k3/2) time complexity which is efficient than O(k2) Time Complexity used in many widely used Key-Based Hashing Algorithms. © 2023 IEEE.

关键词： Message passing

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Guarding Voices, Protecting Homes: A Comprehensive Case Study on Voice Assistant security in Smart Living 12

Guarding Voices, Protecting Homes: A Comprehensive Case Stud...

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12th International Symposium on Digital Forensics and security, ISDFS 2024

作者： Rehman, Fazalur Hashmi, Joudat Abdullah, Moiz Zaman, Hafsah School of Electrical Engineering and Computer Science National University of Sciences and Technology Islamabad Pakistan College of Engineering Georgia Tech University Department of Analytics United States Air University Faculty of Computing and Artificial Intelligence Department of Cyber Security Islamabad Pakistan

ISBN: (纸本)9798350330366

The evolution of technologies in the last decades has transformed the whole human interaction experience with the digital world. Integrated into users' home voice assistant devices has rationalized personal interaction with the technology however convenience of intelligent voice assistant presents security and privacy risks. This paper investigates the security vulnerabilities of smart voice assistant devices specifically focusing on Google Home Mini. Through a series of simulated attacks and comprehensive analysis, this study uncovers potential risks ranging from unauthorized access to user data privacy compromise within home networks. The objective is to raise awareness about these vulnerabilities and their implication urging the need for robust security measures and providing valuable observation for future research. As voice devices are becoming an integral part of daily life addressing these challenges is paramount to ensuring user privacy data integrity and overall security of the smart home ecosystem. © 2024 IEEE.

关键词： Risk assessment

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GLIMMER: Incorporating Graph and Lexical Features in Unsupervised Multi-Document Summarization 27

GLIMMER: Incorporating Graph and Lexical Features in Unsuper...

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27th European Conference on Artificial Intelligence, ECAI 2024

作者： Liu, Ran Liu, Ming Yu, Min Jiang, Jianguo Li, Gang Zhang, Dan Li, Jingyuan Meng, Xiang Huang, Weiqing Institute of Information Engineering Chinese Academy of Sciences China School of Cyber Security University of Chinese Academy of Sciences China School of Information Technology Deakin University Australia Department of Computer Science Beijing Technology and Business University China

ISBN: (纸本)9781643685489

Pre-trained language models are increasingly being used in multi-document summarization tasks. However, these models need large-scale corpora for pre-training and are domain-dependent. Other non-neural unsupervised summarization approaches mostly rely on key sentence extraction, which can lead to information loss. To address these challenges, we propose a lightweight yet effective unsupervised approach called GLIMMER: a Graph and LexIcal features based unsupervised Multi-docuMEnt summaRization approach. It first constructs a sentence graph from the source documents, then automatically identifies semantic clusters by mining low-level features from raw texts, thereby improving intra-cluster correlation and the fluency of generated sentences. Finally, it summarizes clusters into natural sentences. Experiments conducted on Multi-News, Multi-XScience and DUC-2004 demonstrate that our approach outperforms existing unsupervised approaches. Furthermore, it surpasses state-of-the-art pre-trained multi-document summarization models (e.g. PEGASUS and PRIMERA) under zero-shot settings in terms of ROUGE scores. Additionally, human evaluations indicate that summaries generated by GLIMMER achieve high readability and informativeness scores. © 2024 The Authors.

关键词： Semantics

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A Performance Analysis of Hyperledger Fabric for Blockchain-Based Concert Ticketing Systems 4

A Performance Analysis of Hyperledger Fabric for Blockchain-...

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4th International Conference on Electrical engineering and computer Science, ICECOS 2024

作者： Juliansyah, Muhammad Rafi Khunaifi, Aan Syariati, Ali Reza Prasetyo, Andri Puji Rafianti, Dewi Suci Wijanarto, Fajaryan Ramadhan, Insan Handoyo, Karina Mayasita Santoso, Tanzi Mubaroq Harmanda, Topan Try Sahreza, Yosi National Research and Innovation Agency Research Center for Artificial Intelligence and Cyber Security Jakarta Indonesia Gunadarma University Department of Technology and Engineering Jakarta Indonesia

ISBN: (纸本)9798350368253

Indonesia's booming music industry faces a rise in fraudulent ticketing, impacting both event organizers and concertgoers. This research develops and analyzes a blockchain-based concert ticketing system using Hyperledger Fabric, with a focus on performance under varying transaction loads. The system architecture comprises various components, including chaincode which facilitate ticket creation, transfer, and querying. The network setup consists of three peers, one orderer, one channel, and a copy of the chaincode deployed on each peer. Benchmarking with Hyperledger Caliper showed that at a load of 1000 transactions, the system achieved a throughput of 249.4 TPS and an average latency of 1.46 seconds. However, at 2000 transactions, throughput dropped to 135.8 TPS with an average latency of 9.52 seconds. In conclusion, while the system performs well under moderate loads, it's crucial to address scalability for handling significantly higher transaction volumes. This research demonstrates that Hyperledger Fabric offers a promising solution for combating concert ticket fraud in Indonesia by providing a secure and reliable ticketing experience for concertgoers. © 2024 IEEE.

关键词： Blockchain

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Unveiling the Future: Exploring the Impacts and Challenges of Artificial Intelligence in Workplace Applications 3

Unveiling the Future: Exploring the Impacts and Challenges o...

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3rd International Conference for Advancement in technology, ICONAT 2024

作者： Pragith, S. Supriya, S. Sasikala, S. Sateesh, Rayala Swamy, Hemanth Karpagam, P. Vellore Institute of Technology Department of Computer Science Engineering Vellore India Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Department of Computer Science and Engineering India Tagore Engineering College Department of ECE Chennai India MLR Institute of Technology Department of ECE Hyderabad India Motorola Solutions United States Dhanalakshmi College of Engineering Department of Cyber Security Chennai India

ISBN: (纸本)9798350354171

Unveiling the Future: Exploring the Impacts and Challenges of Artificial Intelligence in Society' embarks on a comprehensive journey through the transformative landscape shaped by Artificial Intelligence (AI). This abstract offers a nuanced examination of AI's profound implications, ranging from its disruptive potential to its ethical complexities, and the societal imperatives it underscores. Delving into the evolution of AI technologies, from foundational concepts to cutting-edge innovations, the abstract elucidates their growing significance across diverse sectors including healthcare, finance, transportation, and beyond. However, amidst the promises of efficiency and innovation, ethical concerns loom large. The abstract navigates through the ethical intricacies of AI, addressing issues of bias, accountability, and the erosion of privacy. Furthermore, it ventures into the societal ramifications of AI adoption, exploring its impact on employment dynamics, socioeconomic disparities, and the fabric of human interaction. By interrogating the dual narratives of promise and peril, this abstract offers a holistic understanding of AI's role in shaping the future of society. It underscores the imperative for thoughtful governance, ethical stewardship, and inclusive decision-making to ensure that AI serves as a force for collective progress rather than exacerbating existing divides. Through its interdisciplinary lens, this abstract serves as a roadmap for stakeholders across academia, industry, and policymaking to navigate the complex terrain of AI's integration into society, ultimately paving the way for a future where AI augments human capabilities while upholding fundamental values of fairness, equity, and justice. © 2024 IEEE.

关键词： Decision making

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Optimizing Energy Management and Load Balancing Through AI-Driven Quantum Approximate Optimization 4

Optimizing Energy Management and Load Balancing Through AI-D...

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4th IEEE International Conference on Mobile Networks and Wireless Communications, ICMNWC 2024

作者： Manjunath Kamath, K. Manasa, M. Anitha, B.S. Mahadevi Tlajiya, Falguni Chavan, Sangramjit Department of Cyber Security Karkala India Brindavan College of Engineering Department of Artificial Intelligence and Machine Learning Bengaluru India Sarada Vilas College Department of Computer Science Mysuru India Parul institute of Engineering and Technology Parul University Department of Electrical Engineering Gujarat India Pune India

ISBN: (纸本)9798350352931

The integration of Quantum Approximate Optimization Algorithm (QAOA) and Quantum Annealing (QA) offers a promising approach to addressing energy management and load balancing challenges in modern power systems. This study explores the application of these quantum computing techniques, coupled with Artificial Intelligence (AI), to optimize energy distribution across smart grids. The proposed hybrid model leverages the problem-solving capabilities of QAOA for discrete optimization and the real-time adaptability of QA for minimizing energy consumption and operational costs. AI techniques are employed to predict energy demand, balance loads, and ensure efficient resource allocation. Simulations were conducted on a smart grid scenario involving renewable energy sources, varying demand, and distributed energy generation. The results demonstrate that the hybrid model achieved a 25% improvement in load balancing efficiency and a 30% reduction in energy wastage compared to traditional optimization methods. Additionally, the model reduced peak energy demand by 20%, contributing to overall grid stability. The quantum-enhanced approach also decreased computational complexity by 40%, enabling faster decision-making in dynamic environments. These findings highlight the potential of combining quantum algorithms with AI for sustainable and efficient energy management. © 2024 IEEE.

关键词： Quantum computers

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Forensic Analysis of I2P Communication Network in Android and macOS Environments 18

Forensic Analysis of I2P Communication Network in Android an...

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18th INDIAcom;11th International Conference on Computing for Sustainable Global Development, INDIACom 2024

作者： Wangchuk, Tashi Mandela, Ngaira Mbinda, Tumaini Damedjate, Kamboisssoi Etyang, Felix Makopa, Joel Royal University of Bhutan Department of Information Technology Dewathang Bhutan National Forensic Sciences University School of Cyber Security and Digital Forensics Gandhinagar India Cochin University of Science and Technology School of Computer Science and Engineering Kochi India

ISBN: (纸本)9789380544519

The Invisible Internet Project (I2P) has emerged as a crucial privacy-centric communication network, offering users a secure and anonymous online environment. As the utilization of I2P continues to expand, the demand for specialized forensic techniques tailored to this network becomes imperative. This paper comprehensively investigates I2P forensics within Android and macOS environments, addressing the unique challenges inherent in extracting and scrutinizing digital evidence from I2P applications. The research explores various artifacts and techniques to aid in reconstructing user activities within the I2P network, including analyzing storage files, configuration data, logs, and cache files. Additionally, the study investigates memory forensics as a complementary approach to I2P forensics. The outcomes of this research contribute to advancing forensic analysis techniques in privacy-centric networks, facilitating the efficient investigation of I2P-related crimes. © 2024 Bharati Vidyapeeth, New Delhi.

关键词： Android forensics dark web digital evidence digital forensics eepsite, Anti-forensics I2P forensics macOS forensics memory forensics privacy-centric networks

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A RECENT REVIEW ON IoT BASED TECHNIQUES AND APPLICATIONS

A RECENT REVIEW ON IoT BASED TECHNIQUES AND APPLICATIONS

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2024 International Conference on Sustainable Computing and Integrated Communication in Changing Landscape of AI, ICSCAI 2024

作者： Singh, Arjun Kumar, Sandeep Kumar, Sandeep Bahuguna, Renu Singh, Mahesh Kumar Raj, Nikhil Department Of Computer Science and Engineering Greater Noida Institute of Technology Greater Noida India Department Of Information Technology Raj Kumar Goel Institute Technology Ghaziabad India Department Of Electronics and Communication Engineering G.L. BAJAJ Institute of Technology & Management Greater Noida India Department Of Cyber Security COER University Roorkee India Department Of Computer Science and Engineering Dronacharya Group of Institutions Greater Noida India

ISBN: (纸本)9798350355338

IoT known as Internet of Things is an advanced mechanics which has changed the way humans’ smart devices, smart things, data, and information are connected throughout the world. IoT is a single concept of embedding everything. IoT evolution is yet in its premature steps, and there is a slew of interconnected hurdles to overcome. The IoT has the potential to boost the globe's accessibility, probity, availability, scalability, secrecy, and interoperability. Although, numerous challenges and concerns must be overcome before the IoT's full promise can be realized. Various components of IoT data are recognized and defined, including data sources, data collection, data processing, and transmitting devices. In terms of analytical and substantial data management, as well as transmission networks, the challenges that arise from the need to manage large amounts of heterogeneous data over their systems are mentioned. Sensors can be placed in isolated or far, huge, low-population localities in some applications, while sensors are used to monitor tight locations in others. Clustering the detectors lattice’s nodes in multiple clusters is fundamentally beneficial clearly for scalability grounds, & it can be used to create conservation or utilization schedules that can significantly extend the lattice's life. Current study compares and contrasts common and advanced clustering schemes, as well as size, type of data collected, and performance as a function of non-uniformity and noise level. A combined met heuristic approach, a combined metaheuristic approach, WOA combined with SA, is also used in the proposed work. © 2024 IEEE.

关键词： Clustering IoT (Internet of Things) Metaheuristic Algorithms Simulated Annealing WOA Algorithm (Whale Optimization Algorithm)

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