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Improved Food Traceability for Restaurant customers using Blockchain Technology

Improved Food Traceability for Restaurant customers using Bl...

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Advancement in Technology (ICONAT), international conference for

作者： Shital Dinde Suresh Shirgave Department of Computer Science and Engineering Department of Technology Shivaji University Kolhapur Department of Computer Science and Engineering DKTE’s Textile and Engineering Institute Ichalkaranji

Traceability has become prominent in multi-tiered production systems. It provides assurance to consumers about the transparency and quality of the product. Blockchain food traceability has reasonable attention from the agri-food area. To boost the credibility, efficiency, and safety of the food products, the supply chain should quickly trace the entire lifecycle of food items from their starting point to each phase of the networks. Restaurant customers can trace their food from “farm to fork” with the help of QR codes and smart contracts. This study focuses on restaurant traceability as an example, in which the relationship between supply-chain partners and their networks is shown using a smart contract. The proposed system can build trust among entities that participate in the supply chain network, where distributed ledgers are often used to record and authenticate transactions.

关键词： Production systems distributed ledger Data security Supply chains Smart contracts QR codes Blockchains

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Leveraging Deep Autoencoders for security in Big Data Framework: An Unsupervised Cloud Computing Approach

Leveraging Deep Autoencoders for Security in Big Data Framew...

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distributed Computing and Optimization Techniques (ICDCOT), international conference on

作者： Sourav Roy Nijaguna G S Smitha Sharath Shankar Myasar Mundher Adnan P Umaeswari Department of Electronics and Communication engineering CHRIST (Deemed to be University) Bangalore India Department of Information Science and Engineering S.E.A. College of Engineering and Technology Bangalore India Dept of ECE Nitte Meenakshi Institute of Technology Bengaluru India The Islamic university Najaf Iraq Department of Computer Science and Business Systems R.M.K. Engineering College Kavaraipettai Tamil Nadu India

Abnormalities recognition in bank transaction big data is the number one issue for stability of financial security system. Due to the rate digital transactions are increasing it is vital to have effective ways. Encryption with deep autoencoder model should be explored as it involves trained neural networks that learn such patterns from the complex transaction data. The following paper demonstrates application of anomaly detection using deep autoencoders in the banking big data transactions. It focuses on the theoretical bases, network design, preparedness and the testing measures for deep autoencoders. On the other hand, it solves problems such as high dimensionality and imbalanced dataset. This research paper shows deep autoencoders effectiveness in deep learning and how the network identifies different fraudulent big data transactions, money laundry and unauthorized access. It also encompasses recent developments of cloud environments and future methods using deep autoencoders including the fact that constant search for new possible solutions is a must. The insights delivered contribute to the discourse in financial security community, which incorporates researchers, practitioners, and policymakers involved in anomaly detection in cloud.

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Blockchain Approaches for Healthcare: A Review and Outlook

Blockchain Approaches for Healthcare: A Review and Outlook

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Electronics and Sustainable Communication systems (ICESC), 2020 international conference on

作者： Natasha Shaikh Smita Kasar Department of Computer Science & Engineering Maharashtra Institute of Technology Aurangabad India

ISBN: (数字)9798350379945

ISBN: (纸本)9798350379952

Nowadays, the application of information technology worldwide is accelerating the digital transformation of the healthcare sector. Incorporating blockchain technology into healthcare provides better and more innovative solutions for healthcare providers to enhance the patient's care. By establishing a shared ledger that is cooperatively maintained and impenetrable to tampering, blockchain (BC) technology offers a novel approach to record historical data and ensure the reliability and security of data stored in distributed networks. Nevertheless, new issues relating to privacy and security arise with the integration of the blockchain into the healthcare industry. Hence, this research review concentrates on offering a thorough literature assessment of the chosen papers to emphasize the research subjects that are currently being investigated in blockchain-based healthcare systems and highlight their limitations and potential directions for strengthening the digital security of healthcare data. By analyzing current trends and implications, this research aims to provide a concise overview of existing approaches, and how BC is being utilized to enhance data security, interpretability, and transparency in the healthcare system. The research analyzes 25 literature papers on BC technology for the healthcare domain. Further, the evaluation based on the metrics utilized and year-wise analysis of the selected publications is carried out in this research. Finally, the research also provides an overview of blockchain-related healthcare mechanisms that provide solutions for various applications.

关键词： Industries Measurement Privacy Reviews Data security Scalability Medical services Real-time systems Blockchains Reliability

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Quantum Assisted Architectures for Wireless systems, the Case of Quantum 6G 23

Quantum Assisted Architectures for Wireless Systems, the Cas...

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Proceedings of the 7th international conference on Future networks and distributed systems

作者： Ahtesham Ali Mohammed Ahcene Bounceur Mohammad Hammoudeh Information and Computer Science Department King Fahd University of Petroleum and Minerals Saudi Arabia Computer Science Department King Fahd University of Petroleum and Minerals Saudi Arabia

ISBN: (纸本)9798400709036

The development of a quantum-based architecture for wireless systems is required to respond to the growing need for faster and more effective communication. Quantum computing offers a huge promise for improving wireless communication networks due to its ability to perform complex computations and simulations in a fraction of the time compared to classical computing. With a focus on Quantum 6G, this paper examines the foundations of quantum computing, the state of conventional wireless systems, and the potential for quantum-assisted wireless systems. This paper also analyzes future research areas and briefly discusses the newly developing topic of quantum machine learning in the context of 6G. It starts with reviewing Quantum 6G, covering facets like its effectiveness and security. It also explores the challenges and constraints of managing wireless resources with quantum assistance. This study seeks to explore these issues in order to advance knowledge of quantum 6G networks and encourage additional investigation into this exciting area.

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Enhancing Intrusion Detection in Smart Grids: A Machine Learning-based Defense Against DDoS Attacks with Imbalance-Aware Optimization

Enhancing Intrusion Detection in Smart Grids: A Machine Lear...

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Electronics and Renewable systems (ICEARS), international conference on

作者： Mahaveerakannan R T. Rajesh Kumar Balamanigandan R Parnandi Srinu Vasarao Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai Tamil Nadu India Department of Computer Science and Engineering Swarnandhra College of Engineering and Technology Narsapur Andhra Pradesh India

ISBN: (数字)9798331509675

ISBN: (纸本)9798331509682

The presence of numerous bidirectional communication devices connecting customers to the grid makes smart grid networks particularly vulnerable to network attacks. As an instance of a network attack that could impact the smart grid, a distributed denial of service (DDoS) attack occurs when a compromised grid communiqué devices or nodes send a flood of false data or requests to the smart grid network. This can cause problems with smart meters, data servers, and the state estimator, which in turn affects the services that end users receive. The problem of protecting the network from distributed denial of service (DDoS) attacks is best addressed by methods that rely on machine learning. One major drawback of using machine learning-based approaches is that models need to be retrained every time new types of attacks appear. Despite the fact that DDoS attack detection has long relied on Intrusion Detection systems (IDS), previous research has been limited due to a number of factors. Actually, it is highly discouraged to interfere with the regular functioning of the smart grid. to suggest using reconstructive deep learning methods to identify DDoS attacks efficiently and with minimal downtime in order to tackle this difficulty. In order to identify typical attacks on a communication network, this research introduces a shallow neural network with just 110 artificial neurones triggered by ReLU. to suggest a better attack-sharing loss function to handle unbalanced learning, which will allow for the training of such tiny neural networks. A Lungs Performance-based Optimisation (LPO) was devised using the suggested model to hone the parameters. In smart grid settings, our suggested approach improves the scalability and dependability of IDS and provides useful insights for building strong IDS based on machine learning. This enables organisations to strengthen their defences against harmful cyber-attacks and proactively reduce security risks.

关键词： Training Deep learning Lungs Intrusion detection Denial-of-service attack Smart grids security Reliability Optimization Business

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Enhancing Scalability and Performance in IoT networks through Off-Chain Data Processing and Blockchain Integration

Enhancing Scalability and Performance in IoT Networks throug...

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Communication, Computing and Signal Processing (IICCCS), IEEE international conference on

作者： Rajesh Kumar Rewa Sharma Department of Computer Engineering YMCA J.C. Bose University of Science and Technology Faridabad India

ISBN: (数字)9798350390759

ISBN: (纸本)9798350390766

The rapid proliferation of IoT devices has led to an exponential increase in data generation, posing significant challenges in terms of data security, scalability, and performance. This paper proposes an innovative approach to address these challenges by integrating off-chain data aggregation with blockchain technology. Leveraging MongoDB for off-chain storage and Hyperledger Fabric for ensuring data integrity, our approach enhances the scalability and performance of IoT networks. We present a detailed system architecture, implementation details, and performance evaluation to demonstrate the effectiveness of our solution. The results indicate that the proposed method significantly improves data management capabilities, offering a scalable and secure solution for IoT networks.

关键词： Performance evaluation distributed ledger Scalability systems architecture Data aggregation Signal processing Fabrics Blockchains Telecommunication computing Internet of Things

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Impacts of High Denisty Cloud Computing on Data Protection and security Management for 6G Networking

Impacts of High Denisty Cloud Computing on Data Protection a...

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Disruptive Technologies (ICDT), international conference on

作者： Vinay Mallikarjunaradhya Haritha Yennapusa Ranadeep Reddy Palle K. Suganyadevi Nidhi Gupta Legal Tech Platform Thomson Reuters Toronto Canada Department of Computer Science University of central Missouri Austin Texas USA Department of Computer Science University of Houston Austin Texas USA Department of ECE Sri Eshwar College of Engineering Coimbatore Tamil Nadu India Department of Computer Science and Engineering G.L. Bajaj Institute of Technology and Management Greater Noida India

Data protection and security management in the 6G era is a key challenge due to the emergence of high density cloud computing. The availability of high density cloud computing technologies creates a platform for massive data storage, processing, and analytics capabilities at a scale that has never been seen before. High density cloud computing facilitates the deployment of complex distributed systems consisting of hundreds or thousands of nodes in a single deployment. This can have a significant impact on data protection and security management as it increases the potential threat to the system from malicious actors. To protect data in this environment, organizations must adopt more advanced security practices such as access control, encryption, and defensive layers to protect against malicious actors. The use of encryption can provide a layer of security by making it difficult for outsiders to access information without authorization. Access control can also prevent unauthorized users from accessing certain parts of the system, while defensive layers can help detect and block malicious attacks. The results of this study showed that high density cloud computing can potentially improve the efficiency and performance of data protection and security management in 6G networks.

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Blockchain-based Federated Learning for Decentralized Energy Management systems

Blockchain-based Federated Learning for Decentralized Energy...

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Blockchain Computing and Applications (BCCA), international conference on

作者： Abdulrezzak Zekiye Öznur Özkasap Department of Computer Engineering Koç University Istanbul Türkiye

The Internet of Energy (IoE) is a distributed paradigm that leverages smart networks and distributed system technologies to enable decentralized energy systems. In contrast to the traditional centralized energy systems, distributed Energy Internet systems comprise multiple components and communication requirements that demand innovative technologies for decentralization, reliability, efficiency, and security. Recent advances in blockchain architectures, smart contracts, and distributed federated learning technologies have opened up new opportunities for realizing decentralized Energy Internet services. In this paper, we present a comprehensive analysis and classification of state-of-the-art solutions that employ blockchain, smart contracts, and federated learning for the IoE domains. Specifically, we identify four representative system models and discuss their key aspects. These models demonstrate the diverse ways in which blockchain, smart contracts, and federated learning can be integrated to support the main domains of IoE, namely distributed energy trading and sharing, smart microgrid energy networks, and electric and connected vehicle management. Furthermore, we provide a detailed comparison of the different levels of decentralization, the advantages of federated learning, and the benefits of using blockchain for the IoE systems. Additionally, we identify open issues and areas for future research for integrating federated learning and blockchain in the Internet of Energy domains.

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A Survey on Privacy-Preserving Communication Frameworks in Machine Learning for Cybersecurity Threat Detection

A Survey on Privacy-Preserving Communication Frameworks in M...

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Ubiquitous Computing and Intelligent Information systems (ICUIS), international conference on

作者： Banothu Suneetha R. Kesavan Department of Computer Science & Engineering Saveetha School of Engineering SIMATS Chennai India

ISBN: (数字)9798331529635

ISBN: (纸本)9798331529642

This survey covers the new trend of privacy-preserving communication frameworks in machine learning in the FL, DP and SMPC for cyber threat detection domains. The specific research performed between the year of 2020 and 2024 has been surveyed and included in this paper. The main contribution is monitoring cybersecurity threats using privacy-preserving frameworks in distributed systems such as IoT and industrial networks. 40 research papers have been reviewed and categorized to several related themes such as FL implementations, privacy-preserving methods, and cybersecurity threat detection. The relevance of privacy-preserving frameworks for the real-world cybersecurity scenario is illustrated with dataset CISA 2022 Vulnerability Dataset. The study of privacy-preserving communication shows that FL can be combined with DP and SMPC to achieve data privacy preservation while deduction accuracy of detecting cyber threats can be well-maintained. Moreover, the research gaps and challenges of scalability, communication overhead have been addressed and identified to facilitate the future research and development.

关键词： Surveys Protocols Scalability Network security Market research Ubiquitous computing Threat assessment Blockchains computer security Research and development

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A Blockchain-Based Intelligent IoT Communication System for Enhanced security, Reliability, and Efficiency

A Blockchain-Based Intelligent IoT Communication System for ...

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Advanced Computing Technologies (ICoACT), international conference on

作者： Dinesh Kumar K J. Gobinath Jayavadivel Ravi S. Saravanakumar Senthil P B. Prabhu Shankar Department of Computer Science and Engineering Vel Tech University Chennai India Department of Computer Science and Engineering Rajiv Gandhi College of Engineering Chennai India School of Computer Science and Engineering Presidency University Bengaluru India Department of Information Technology Paavai Engineering College Paachal India Department of Artificial Intelligence and Data Science T.J.S.Engineering college Chennai India Department of Artificial Intelligence and Machine Learning Vel Tech University Chennai India

ISBN: (数字)9798331509859

ISBN: (纸本)9798331509866

This research proposes a new approach for developing and implementing a smart communication system of IoT through developmental blockchain technology. Regarding the proposed solution, it is suggested that a distributed ledger can improve security, reliability, and efficiency of communication of IoT devices. They tackle issues such as data integrity, privacy and security in IoT networks as well as the problem of trust in such networks. The solution provides a decentralised and secure IoT ecosystem communication hence allowing monitoring, controlling and administration of the IoT build ecosystems in real time. Blockchain technology, however, when combined with nextgeneration communication interfaces and modern data analysis techniques, can offer various superior characteristics such as device identification, origin of information, etc. to IoT applications. It also enhances the dependability and capacity of IoT systems regarding capability and efficiency. Analysis and performance comparisons substantiate the performance benefits of the proposed intelligent communication system based on blockchain technology In addition these theoretical and performance analyses and experimental evaluation confirm the applicability and potential of the blockchain-based intelligent communication system to transform IoT communication models and facilitate the new generation of eIOT applications in a number of fields. The key to the solution to incorporate blockchain fundamental infrastructure to augment the communication channel of IoT devices. Using cryptography and consensus methodologies with the decentralized framework, integrity and confidentiality of the data is properly maintained because of the barriers of malicious interception or manipulation of the data. The communication system also boosts trust within the network participants because it offers a decentralized and immutable ledger of data transactions on the blockchain. Instead, one of the compelling benefits of this solution

关键词： Performance evaluation computers Communication systems Ecosystems Transforms Real-time systems Blockchains Internet of Things Reliability Monitoring

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