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5th International Conference on Innovative Data Communication Technologies and Application, ICIDCA 2024

作者： Amasala, Likhitha Ponnuru, Mahesh Srideviponmalar, P. School of Computer Science and Engineering Vellore Institute of Technology Amaravathi522237 India School of Computing SRM Institute of Science and Technology Potheri603203 India Department of Computational Intelligence School of Computing Faculty of Engineering and Technology SRM Institute of Science and Technology Potheri603203 India

At present, technological systems lack a secure and transparent method for tracking goods and preventing theft in e-commerce, leading to trust issues and data vulnerabilities. There is a pressing need for a comprehensive solution that integrates Ethereum blockchain, IPFS, and advanced cryptographic techniques to address these challenges and enhance the security and transparency of transactions. This research paper presents a robust system that harnesses the Ethereum blockchain, IPFS (Interplanetary File System), and advanced cryptographic algorithms to create a secure, decentralized approach for tracking goods and preventing theft incidents. Unique identifiers and related information will be sent to the mail of the customer and same should entered by the customer for successful transaction. By assigning unique identifiers to purchased products and employing cryptographic techniques to encrypt sensitive data, our system ensures both user privacy and the creation of an immutable transaction ledger. Users can efficiently manage their purchased goods, block stolen items, and communicate with sellers through an intuitive interface. Additionally, the system provides sellers with a comprehensive transaction history, enhancing accountability and transparency within the supply chain. Through this research, we demonstrate the effectiveness of our blockchain based anti-theft measures, underpinned by Ethereum, IPFS, and cutting-edge cryptographic algorithms, in fostering secure, trustless transactions. This work highlights the transformative potential of blockchain technology and decentralized protocols in revolutionizing security and transparency across diverse sectors. © 2024 The Authors. Published by Elsevier B.V.

关键词： Smart contract

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Optimizing Energy Consumption in Smart Grids Using Demand Response Techniques

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Distributed Generation and Alternative Energy Journal 2024年第1期39卷 111-136页

作者： SwornaKokila, M.L. Venkatarathinam, R. Rose Bindu, Joseph P. Manivasagam, M.A. Kishore, Kakarla Hari Department of Computing Technologies School of Computing College of Engineering and Technology Faculty of Engineering and Technology SRM Institute of Science and Technology SRM Nagar Kattankulathur TN Chennai India Department of Information Technology Sri BalajiChockalingam Engineering College A.C.S. Nagar Irumbedu Thiruvannamalai District Tamil Nadu Arni India Department of Mathematics Dayananda Sagar College of Engineering Bangalore India Computer Science and Engineering Siddartha Institute of Science and Technology Andhra Pradesh India Department of Electronics and Communication Engineering KoneruLakshmaiah Education Foundation Guntur Andhra Pradesh Vaddeswaram India

Smart grids have developed as a potentially game-changing strategy for controlling the demand and supply of energy. Unfortunately, peak demand is a significant source of grid instability and rising energy prices, making it one of the most critical difficulties in smart grids. During times of high energy demand on the grid, demand response (DR) strategies incentivize consumers to change how they use energy. This study’s overarching goal is to learn how DR methods may be used to help smart grids make better use of their energy resources. The primary research is to develop a smart DR system that can predict times of high energy demand and proactively alter usage to reduce such periods. Machine learning strategies are utilized in the proposed system to estimate peak demand via past data, weather predictions, and other variables. The system will then alter energy use based on real-time data from smart meters along with other sensing devices to meet the projected demand. The simulation model will include several scenarios for testing the DR system’s flexibility, including a range of weather conditions, load profiles, and grid topologies. Several indicators, including peak demand reduction (80.04%), energy savings (38.09%), environmental consequences, and reaction time ( © 2024 Taylor and Francis Inc.. All rights reserved.

关键词： Smart power grids

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Secure Image Communication Using Galois Field,Hyper 3D Logistic Map,and B92 Quantum Protocol

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Computers, Materials & Continua 2024年第12期81卷 4435-4463页

作者： De Rosal Ignatius Moses Setiadi Nova Rijati Ahmad Rofiqul Muslikh Bonifacius Vicky Indriyono Aceng Sambas Faculty of Computer Science Universitas Dian NuswantoroSemarang50131Central JavaIndonesia Research Center for Quantum Computing and Materials Informatics Faculty of Computer ScienceUniversitas Dian NuswantoroSemarang50131Central JavaIndonesia Faculty of Information Technology Universitas MerdekaMalang65146East JavaIndonesia Faculty of Economics and Business Universitas STRADA IndonesiaKediri64133East JavaIndonesia Faculty of Informatics and Computing Universiti Sultan Zainal AbidinCampus BesutBesut22200TerengganuMalaysia Department of Mechanical Engineering Universitas Muhammadiyah TasikmalayaTamansari GobrasTasikmalaya46196Indonesia

In this paper,we propose a novel secure image communication system that integrates quantum key distribution and hyperchaotic encryption techniques to ensure enhanced security for both key distribution and plaintext ***,we leverage the B92 Quantum Key Distribution(QKD)protocol to secure the distribution of encryption keys,which are further processed through Galois Field(GF(28))operations for increased *** encrypted plaintext is secured using a newly developed Hyper 3D Logistic Map(H3LM),a chaotic system that generates complex and unpredictable sequences,thereby ensuring strong confusion and diffusion in the encryption *** hybrid approach offers a robust defense against quantum and classical cryptographic attacks,combining the advantages of quantum-level key distribution with the unpredictability of hyperchaos-based *** proposed method demonstrates high sensitivity to key changes and resilience to noise,compression,and cropping attacks,ensuring both secure key transmission and robust image encryption.

关键词： Galois field hyper 3D logistic map hyperchaotic map image security improved logistic map secure communication quantum security

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Designing Quantum-Resilient Blockchain Frameworks: Enhancing Transactional Security with Quantum Algorithms in Decentralized Ledgers

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International Journal of Advanced Computer science and Applications 2025年第4期16卷 618-628页

作者： Kale, Meenal R. Baker El-Ebiary, Yousef A. Sathiya, L. Burugari, Vijay Kumar Yulduz, Erkiniy Muniyandy, Elangovan Alanazi, Rakan Department of Humanities Yeshwantrao Chavan College of Engineering Hingna Nagpur India Faculty of Informatics and Computing UniSZA University Malaysia Department of CSE Panimalar Engineering College Chennai India Dept of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Vaddeswaram Andhra Pradesh Guntur India Automatic Control and Computer Engineering Department Turin Polytechnic University in Tashkent Tashkent Uzbekistan Department of Biosciences-Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai India Applied Science Research Center Applied Science Private University Amman Jordan Department of Information Technology Faculty of Computing and Information Technology Northern Border University Rafha Saudi Arabia

Quantum computing is progressing at a fast rate and there is a real threat that classical cryptographic methods can be compromised and therefore impact the security of blockchain networks. All of the ways used to secure blockchain like Rivest–Shamir–Adleman (RSA), Elliptic Curve Cryptography (ECC) and Secure Hash Algorithm 256-bit (SHA256) are the characteristic of the traditional cryptographic techniques vulnerable to attack by quantum algorithms: Shor’s and Grover’s algorithms: can efficiently break asymmetric encryption and speed up brute force attacks. Because of this vulnerability, there exists a need to develop an advance quantum resilient blockchain framework to protect the decentralized ledgers from the future threats of the quantum. This research proposes Post-Quantum Cryptography (PQC), Quantum Key Distribution (QKD) and Quantum Random Number Generation (QRNG) as a formidable architectural integration, to fortify security of blockchain. Classical encryption is replaced with PQC, QKD with secure key exchange by detecting eavesdropping, and QRNG with improving cryptographic randomness to remove the predictable key vulnerability. Only with a small loss of transaction efficiency, we increase transaction encryption accuracy, key exchange security, and resistance to quantum attacks. In this quantum enhanced blockchain design, the idea is to preserve the decentralization, transparency and security and at the same time overcome the future quantum threat. By going through rigorous analysis and comparative evaluation, we demonstrate that the approach saves blockchain networks from the emerging quantum risks to make sure that the decentralized finance, smart contracts and cross chain transactions. © (2025), (science and Information Organization). All rights reserved.

关键词： Quantum cryptography

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Anomaly-Based Intrusion Detection System in WSN using DNN Algorithm 1

Anomaly-Based Intrusion Detection System in WSN using DNN Al...

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1st International Conference on Emerging Technologies for Dependable Internet of Things, ICETI 2024

作者： Al-Fuhaidi, Belal Farae, Zainab Al-Sorori, Wedad Maqtary, Naseebah Al-Ashmoery, Yahya Al-Fuhaidy, Farouk Al-Taweel, Sadik Faculty of Computing and IT University of Science and Technology Sana’a Yemen Department of IT Al-Razi University Sana’a Yemen Dept. Mathematics & Computer Faculty of Science Sana’a University Sana’a Yemen Department of Electrical Engineering Faculty of Engineering Ibb University Ibb Yemen

ISBN: (纸本)9798331533557

Intrusion detection systems (IDSs) are a necessary principle in WSN security, which can successfully prevent various hackers' and intruders' attempts to hack the network. In this research, we address the problem of achieving high accuracy in detecting intrusions in WSNs due to specific characteristics of WSN data, including the appropriate dataset, the drawbacks of feature selection, and choosing the proper algorithms for the classification process. In this paper, we proposed the anomaly-based IDS model using the DNN algorithm and mutual information (MI) technology to select features. The proposed model has been implemented using the Python language used in the Anaconda platform and relying on the standard NSL-KDD dataset. The experimental results showed the capability of the proposed model to achieve high-performance accuracy in intrusion detection using the DNN algorithm compared to the state-of-the-art. The proposed model outperforms other previous relevant works by 3.65% enhancement in terms of accuracy. © 2024 IEEE.

关键词： Network intrusion

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A proposal of Android services generator for inter-connection with ADAS

A proposal of Android services generator for inter-connectio...

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2023 IEEE Zooming Innovation in Consumer Technologies Conference, ZINC 2023

作者： Boskovic, Ognjen Kokinovic, Aleksandar Kenjic, Dusan Kastelan, Ivan University of Novi Sad Faculty of Technical Science Department of Computing and Control Engineering Novi Sad Serbia

ISBN: (纸本)9798350347722

The integration of software in the automotive industry has become increasingly complex and time-sensitive, necessitating the implementation of efficient tools. One such tool is the utilization of a generator. Over the past decade, the implementation of In-Vehicle-Infotainment systems has become ubiquitous, occupying a central position within vehicles. Another system present in vehicles is the Advanced Driver Assistance System. Despite their prevalence, these systems operate in isolation. However, the utilization of Android services and a service-client architecture can facilitate communication between disparate systems through the implementation of various service-client-based protocols. This study proposes the development of a generator for Android services that enable communication between Advanced Driver Assistance System systems through the use of CommonAPI proxy. The implementation of this generator will expedite the production process of code that integrates these independent systems. © 2023 IEEE.

关键词： Advanced driver assistance systems

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Idecomp: imbalance-aware decomposition for class-decomposed classification using conditional GANs

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Discover Artificial Intelligence 2023年第1期3卷 31页

作者： Buczek, Patryk Zidan, Usama Gaber, Mohamed Medhat Abdelsamea, Mohammed M. School of Computing and Digital Technology Birmingham City University Birmingham100190 United Kingdom Faculty of Computer Science and Engineering Galala University Suez435611 Egypt Department of Computer Science Faculty of Computers and Information Assiut University Assiut71515 Egypt

Medical image classification tasks frequently encounter challenges associated with class imbalance, resulting in biased model training and suboptimal classification performance. To address this issue, the combination of class decomposition and transfer learning has proven to be effective in classifying imbalanced medical imaging datasets. Nevertheless, in order to further augment the performance gains achieved through the utilisation of class decomposition within deep learning frameworks, we propose a novel model coined imbalance-Aware Decomposition for Class-Decomposed Classification (iDeComp) model. By incorporating a conditional Generative Adversarial Network (GAN) model, iDeComp is capable of generating additional samples specifically tailored to underrepresented decomposed subclasses. This paper investigates the application of iDeComp using two different medical imaging datasets. iDeComp selects underrepresented samples from the training set of the sublevel classes within each dataset, which are then employed to train separate conditional Deep Convolutional GAN (DCGAN) models and verification models. The conditional DCGAN model is responsible for generating additional samples, while the verification model critically evaluates the appropriateness of the synthesised images. Subsequently, the resulting augmented samples are utilized to train the classification model. To assess the effectiveness of iDeComp, we employ various evaluation metrics including accuracy, precision, recall, and F1 score. The results obtained from our experiments clearly indicate that iDeComp outperforms existing approaches in terms of classifying both imbalanced datasets. © The Author(s) 2023.

关键词： Generative adversarial networks

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A Secure Framework for Blockchain Transactions Protection

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Computer Systems science & engineering 2023年第5期45卷 1095-1111页

作者： Wafaa N.Al-Sharu Majdi K.Qabalin Muawya Naser Omar A.Saraerh Department of Electrical Engineering Faculty of EngineeringThe Hashemite UniversityZarqa13133Jordan Department of Computer Science King Hussein School of Computing SciencesPrincess Sumaya University for TechnologyAmman11941Jordan

One of the most extensively used technologies for improving the security of IoT devices is blockchain *** is a new technology that can be utilized to boost the *** is a decentralized peer-to-peer network with no central *** nodes on the network mine or verify the data recorded on the *** is a distributed ledger that may be used to keep track of transactions between several *** one can tamper with the data on the blockchain since it is *** the blocks are connected by hashes,the transaction data is *** is managed by a system that is based on the consensus of network users rather than a central *** immutability and tamper-proof nature of blockchain security is based on asymmetric cryptography and ***,Blockchain has an immutable and tamper-proof smart contract,which is a logic that enforces the Blockchain’s *** is a conflict between the privacy protection needs of cyber-security threat intelligent(CTI)sharing and the necessity to establish a comprehensive attack chain during blockchain *** paper presents a blockchain-based data sharing paradigm that protects the privacy of CTI sharing parties while also preventing unlawful sharing and ensuring the benefit of legitimate sharing *** builds a full attack chain using encrypted threat intelligence and exploits the blockchain’s backtracking capacity to finish the decryption of the threat source in the attack *** contracts are also used to send automatic early warning replies to possible attack *** tests are used to verify the feasibility and efficacy of the suggested model.

关键词： Manuscript preparation typeset format

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Smart Surveillance System and Prediction of Abnormal Activity in ATM Using Deep Learning

Smart Surveillance System and Prediction of Abnormal Activit...

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International Conference on Data science and Network engineering, ICDSNE 2023

作者： Gnanavel, S. Duraimurugan, N. Jaeyalakshmi, M. Department of Computing Technologies Faculty of Engineering and Technology SRM Institute of Science and Technology Tamil Nadu Kattankulathur 603203 India Department of Computer Science and Engineering Rajalakshmi Engineering College Thandalam Chennai6021053 India

ISBN: (纸本)9789819967544

Although surveillance cameras are used in ATM cells, we face some problems of robbery and theft at ATMs due to lack of security;however, the monitoring capacity of law enforcement agencies has not kept pace. ATM spoofing attacks can be carried out to break or damage the ATM by stealing the machine and taking cash from the ATM. To reduce this problem, we arm the ATM with a camera module mounted in the room to perform continuous video observation. The camera detects the human and his activity in the ATM and attempts to breach the ATM. It detects unusual activities and immediately sends an alert notification to the police. Therefore, the system handles the application developed to automate video surveillance and detect any potential criminal activity at ATMs. Therefore, in this work, abnormal behavior is observed using CNN and RNN in surveillance videos. These algorithms can be used to recognize faces, detect and track camera movements, and detect and identify the action required to prevent such activity. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Deep learning

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YOLO-based Food Damage Detection: An Automated Approach for Quality Control in Food Industry 8

YOLO-based Food Damage Detection: An Automated Approach for ...

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8th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2024

作者： Dhelia, Ayushi Chordia, Srishti Kanisha, B. Srm Institute of Science & Technology Department of Computing Technologies Chengalpattu Tamil Nadu Kattankulathur603203 India Srm Institute of Science & Technology Faculty of Engineering and Technology Department of Computing Technologies Tamil Nadu 603203 India

ISBN: (纸本)9798350376425

In modern food production and quality control, accuracy and efficiency are paramount. This study presents a pioneering application of artificial intelligence technology that integrates the advanced object recognition model YOLOv8 into food quality assessment. This approach uses high-resolution images for detection and aims to transform the food industry by providing real-time insights and actionable data to ensure quality. The main goal of this research is to create a comprehensive AI-based system that uses YOLOv8 and #039 capabilities to identify and locate spoiled food in complex and diverse production flows. Leveraging YOLOv8's state-of-the- art object detection capabilities, the approach enables rapid detection of damaged products and quality assessment, improving overall food quality control practices. In addition, YOLOv8 integration with cloud-based systems facilitates dynamic visualization and monitoring of key performance metrics. With these visualization tools, the system can provide real-time information about detection accuracy, model behavior, and potential biases. This continuous monitoring enables quick adjustments and refinements, resulting in an optimized and reliable food quality control solution. With the innovative fusion of YOLOv8 and cloud technology, the paper aims to promote accurate food quality control. By providing kitchen processors with timely and accurate information about product quality and potential damage, the system can transform traditional quality assurance practices and usher in a new era of information-driven food production. © 2024 IEEE.

关键词： Food industry

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