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检索条件"任意字段=1st International Conference on Computer Science and Information Technology"

共 82912 条记录，以下是71-80 订阅

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Random Security Generators with Enhanced Cryptography for Cybersecurity in Financial Supply Chains 1

Random Security Generators with Enhanced Cryptography for Cy...

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1st international conference on Advances in computer science, Electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Thammareddi, Latha Anumolu, Venkateswara Rao Kotte, Kulasekhara Reddy Chowdari Marella, Bhagath Chandra Arun Kumar, K. Bisht, Jatin India ERP Solutions-Information Technology India SLRI Solutions INC India Insights & Data Department of Financial Services India Big Data Architect India Bipin Tripathi Kumaon Institute of Technology Department of Computer Science & Engineering Almora India

ISBN: (纸本)9798331518578

Blockchains, like Ethereum, depend on a distributed system of collaborative servers referred to as inspectors or mine workers to validate transactions and generate novel legal blocks. In today's electronic world, it is critical to secure financial supply chains (FSCs) from complex cyber-attacks. This study combines Quantized Random Security Generators (QRSGs) with Artificial Intelligence (AI) to improve cybersecurity in FSC. QRSGs use quantum physics to produce random outcomes, which is critical for establishing safe cryptography credentials and resolving the flaws of regular predictable RSGs. This study found that the QRSG-based approach outperformed traditional RSG methods. The QRSG demonstrated strong entropy and uncertainty, transferring both NIst SP800-22 and Diehard examinations at much greater levels. The platform's real-time safety features were improved by the AI element's outstanding performance measures in identifying security breaches. More rapid decoding and encryption times, reduced delay, and increased resilience to brute-force, quantum, and prediction assaults were all demonstrated by the coupled QRSG and AI methods. This study emphasizes how crucial it is to use AI and QRSGs to safeguard FSCs. The combined platform provides a complete option to reduce cyber-attacks by offering strong cryptography security and real-time attack identification. These results demonstrate how QRSG and AI innovations can completely transform cybersecurity in the banking industry, safeguarding vital financial systems and guaranteeing the privacy and reliability of financial payments. © 2025 IEEE.

关键词： Quantum optics

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MRAM-Based Physical Unclonable Function that is Resilient to Deep Learning Attacks 1

MRAM-Based Physical Unclonable Function that is Resilient to...

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1st international conference on Advances in computer science, Electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Venkadeshwaran, Kuthalingam Alam, Intekhab Faculty of Engineering and Technology Department of Mechanical Engineering Ramnagar District Karnataka India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India

ISBN: (纸本)9798331518578

Electronic devices are everywhere, so strong hardware security is needed to keep private data safe from dangers. A physical Unclonable Function (PUF) device constructed using magneto-resistive random-access memory (MRAM) is shown in this study. The circuit generates appropriate outputs for problem-solving by using built-in properties derived from various manufacturing processes, such as the resistance of the magnetic tunnel junction (MTJ) cell. This proposal differs from Arbiter PUF in that it satisfies the rigorous avalanche criteria (SAC). Additionally, the proposed circuit is impervious to machine learning-based modelling assaults due to its grid-like architecture. Various ML approaches are evaluated for two- and four-array designs, including systems such as support vector machine (SVM), linear regression (LR), and multilayer perceptron (MLP). Accuracy of MLP-attack forecasts remained 53.62% for two array circuit & 49.88% for four array circuit. This demonstrates that the system continues to function well despite substantial process modifications. A convolutional neural network (CNN), a recurrent neural network (RNN), a multi-layer perceptron (MLP), and a Larq are all used in high-dimensional models that are based on deep learning. These nets have an accuracy rating of 50.32%, 50.26%, and 50.32%, along with 50.32%, correspondingly. For a simpler two-array design, the suggested circuit's efficiency at the layout stage is also looked into. Based on the simulations, the suggested circuit has an average intra-hamming distance (HD) of 0.99% and an average inter-hamming distance (HD) of 49.97%. It also has an average diffuseness of 49.08. © 2025 IEEE.

关键词： Hamming distance

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LegalAI Across Languages: A Comprehensive Survey on Tasks, Methodologies and Challenges 1

LegalAI Across Languages: A Comprehensive Survey on Tasks, M...

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1st international conference on AIML-Applications for Engineering and technology, ICAET 2025

作者： Deshpande, Anjali Deshmukh, Pratiksha COEP Technological University Dept. of Computer Science and Engineering Pune India PICT Dept. of AI & DS Pune India School of Computational Sciences COEP Technological University Dept. of Computer Science and Engineering Pune India

ISBN: (纸本)9798350355611

Natural Language Processing (NLP) is revolutionizing the legal domain, enabling tasks such as predicting legal outcomes, summarizing complex documents, identifying key entities, and assessing bail risks. This survey paper presents a comprehensive review of the existing research on NLP tasks applied to legal documents and judgments across various languages, with a special emphasis on low-resource languages. Despite the extensive work done in widely spoken languages like English, there remains a critical need to extend these advancements to languages with limited resources and data availability. This paper categorizes and analyzes the NLP tasks in the legal domain based on the languages they target. It highlights the methodologies employed, datasets utilized, and the performance of different models across diverse languages. Furthermore, it identifies the gaps in current research and proposes potential directions for future work, particularly in improving the accessibility and applicability of NLP solutions for legal texts in underrepresented languages. By providing a comprehensive overview of advancements and obstacles, this survey seeks to assist future research endeavors that bridge the disparity between high-resource and low-resource languages in legalAI applications. © 2025 IEEE.

关键词： Risk assessment

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A Hybrid Approach Using Cryptography and K-Least Significant Bit steganography Algorithm in Cloud Computing 1

A Hybrid Approach Using Cryptography and K-Least Significant...

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1st international conference on Advances in computer science, Electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Goyal, Anshika Gupta, Bhumika VMSB Uttarakhand Technical University Dept. of Computer Science & Engineering Dehradun India G.B. Pant Institute of Engineering & Technology Dept. of Computer Science & Engineering Pauri India

ISBN: (纸本)9798331518578

The exponential growth of communication technologies has broadened the cloud computing ecosystem horizon to meet main communication needs. However, in-parallel upsurge in online attacks has alarmed industries to ensure optimal data security. The combination of steganography and cryptosystems has been recognized as an enhanced security model for data transfer among the main security systems now in use. In this paper, a hybrid approach using cryptography and K- Least Significant Bit steganography algorithm in Cloud Computing (HYBC-KLSBS-CC) are proposed. Initially, input text data is retrieved from cloud storage and compressed using Huffman Compression Coding (HCC) to reduce data size. The compressed data is then encrypted with a Hybrid Cryptography Algorithm (Hyb-MRFC-ALC), combining Modified Random Fibonacci Cryptography and Asymmetric Lightweight Cryptography to ensure robust encryption. Finally, encrypted data is embedded within an image using the K-Least Significant Bit (KLSB) steganography technique, providing additional layer of security. The proposed method enhances data confidentiality, integrity, and storage efficiency in cloud environments. The proposed HYBC-KLSBS-CC approach attains 26.89%, 29.49% and 18.64% lower PSNR and 26.89%, 29.49% and 18.64% lower MSE when analyzed through existing techniques like data security dependent on cryptography steganography related with OTP procedure and Huffman coding in the cloud environment (CS-OTP-CE), a novel hybrid cryptographic framework for secure data storage in cloud computing: Integrating AES-OTP and RSA with adaptive key management and Time-Limited access control (AES-OTP-RSA-CC) and Crypto-stegno dependent model for securing medical information on IOMT platform (CS-SMI-IOMT). © 2025 IEEE.

关键词： Cloud platforms

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Ensuring Data Integrity in Multi-Tenant Cloud Environments Through Advanced Testing 1

Ensuring Data Integrity in Multi-Tenant Cloud Environments T...

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1st international conference on Advances in computer science, Electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Gali, Vinay Kumar Chauhan, Sansar Singh Gupta, Gopal Kumar Bulani, Padmini Rajendra Ravalji, Vardhansinh Yogendrasinnh Jayaraman, Kumaresan Durvas Nagarjuna University Andhra Pradesh Guntur522510 India G.L. Bajaj Institute of Technology and Management Department of Computer Science and Engineering Greater Noida201306 India Nagpur Campus Pune440008 India Institute of Chartered Accountants of India India Northeastern University BostonMA United States Bharathidasan University Tamil Nadu Tiruchirappalli India

ISBN: (纸本)9798331518578

fortunately, multi-tenant cloud environments offer a more cost-effective provisioning model that consumes infrastructure to store and access data. As the volume of sensitive data processed and stored in the cloud continues to grow, ensuring data integrity has become a top concern for organizations. Data integrity is the information that is correct, consistent, and reliable is stored in the cloud. To address this issue, we also present a solution that allows us to maintain integrity in a multi-tenant cloud environment using advanced testing. The standard approach to testing (functional and performance testing) does not identify and will enable us to prevent data integrity problems. That's because these approaches describe the system's functionality and performance rather than the accuracy of the system's data. They proposed a solution that used techniques like anomaly detection, data profiling, and data quality checks to discover possible integrity issues in the dataset. The new techniques work within the testing process, while all data is assessed for integrity before being stored in the cloud. © 2025 IEEE.

关键词： Data integrity

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AI-Driven Decision Support Systems for Project Management in Automobile Engineering 1

AI-Driven Decision Support Systems for Project Management in...

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1st international conference on Advances in computer science, Electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Vasudevan, M. Kumar, B. Senthil Deevi, Durga Praveen More, Amrita Baid Huddar, Vikrant Turdialiev, Mukhammad Ali School of Management Hindustan Institute of Technology & Science Tamil Nadu Chennai India Hindustan Institute of Technology & Science Department of School of Management Tamil Nadu Chennai India O2 Technologies Inc CA United States Medi-Caps University Department of Management Studies Madhya Pradesh Indore India Mumbai University Department of Management Studies India Tashkent state university of law Department of Private International Law Tashkent Uzbekistan

ISBN: (纸本)9798331518578

The integration of artificial intelligence in project management with revolutionize engineering processes like automobile. The present study explores the impact of artificial intelligence in decision support system to optimise the project workflow with improved decision making and prediction of potential bottlenecks in automotive engineering. The technology driven decision support system includes natural language processing predictive analytics and machine learning examined for product innovation time management and cost production. The study discusses about the challenges in adaptability of artificial intelligence data security and system integration in the complex environment. The real-world applications are analysed for highlighting the ai driven decision support system to enhance competitiveness and agility in automobile engineering for project management. The study emphasises the potentiality of artificial intelligence in redefining the conventional engineering practises for data driven and smarter decision making in automotive sector. © 2025 IEEE.

关键词： Project management

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Machine Learning-Enhanced Voice Interaction: Revolutionizing Windows Desktop Applications 1

Machine Learning-Enhanced Voice Interaction: Revolutionizing...

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1st international conference on Advances in computer science, Electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Vora, Raj Chakrawarti, Rajesh Kumar Raghuwanshi, Namrata Sushila Devi Bansal College of Technology Computer Science and Engineering Indore India

ISBN: (纸本)9798331518578

The use of voice interaction is changing the way human being communicate with devices as it offers a simple and effective way of interaction. To implement voice interaction within desktop applications and make it more effective as it is integrated with the operating system, there is a various need models, to particularly improve Convolutional its neural quality. Networks This (CNNs), paper Recurrent considers Neural how Networks (RNNs), and transformers, can enhance the effectiveness of voice interaction in the context of Windows desktop platforms. The research focuses on several major issues: enhancing the speech recognition performance in the presence of background noise, handling the differences in user's accent and speech manner, and real-time operation with reduced delay. It also examines issues of privacy relating to handling of sensitive voice information and ways of reducing these vulnerabilities. Using and enhanced user machine intent learning and results operating encompass connecting detection strategies, the indicate system the in this user's and that voice possibility developing voice research experience provides the interaction the of recognition in is an application with next increasing systems. Different designed better of other these generation the practical user to machine current models of multilingual applications experience. Improve learning and are desktop capabilities, including the enhances future assessed apps. Implementing productivity current The AI from the tools, limited paper effectiveness solutions, the ability accessibility capabilities also and thus perspective to features of provides quality stating of recognize and contextual recommendations of that performance, users' intelligent understanding for voice flexibility emotions, assistants. Future control is and the research, commands the which on key them to Windows. © 2025 IEEE.

关键词： Speech recognition

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Optimization of Energy Efficiency in IoT inside Smart Grids Utilizing Machine Learning and Artificial Intelligence Techniques 1

Optimization of Energy Efficiency in IoT inside Smart Grids ...

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1st international conference on Advances in computer science, Electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Thimmappa, Arunkumar Devalapura Singh, Swati Faculty of Engineering and Technology Department of Mechanical Engineering Karnataka India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India

ISBN: (纸本)9798331518578

It is possible for hard jobs to be done by machines with the help of machine learning. computers and cell phones could make it simpler to regulate the temperature inside a smart grid (a SG), keep an eye on security, and do regular repair. The Internet of Things, or IoT, links the different parts of smart buildings together. As the idea of the Internet of Things (IoT) grows, SGs are being added to bigger networks. The Internet of Things (IoT) is a big part of Smart Grid (SG) s as it makes life better for everyone. It is proven that current methods for life support are harmless & work well to keep people alive. The main purpose of this study is to find out why IoT devices are being put in smart buildings as well as the grid. Looking at it this way, the system that serves IoT devices along with the parts that make them up is very important. Smart grid tracking systems that can be set up remotely can make buildings safer and more comfortable for the people who live or work there. Everything from household technology to SGs needs sensors to work and be watched. Devices that are tied to a network should use less power and can be monitored from afar. Their goal is to help people come up with solutions that use AI, IoT, as well as SGs. The writers also look into SG, networking, and machine intelligence. The last thing we do is look at studies on SG along with IoT. A number of parts of the IoT technology are up for discussion. The first part of this study talks about the most popular ways to use machine learning to predict how much energy a building will need. The authors then talk about IoT and the ways it works, along with SG along with smart meters, and these are needed to get real-time energy information. Then, researcher look into how the different smart grid, Internet of things & machine learning parts work together and combine utilizing basic design with layers that are grouped into entities that talk to each other through links. © 2025 IEEE.

关键词： Smart power grids

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Blockchain-Enabled Financial Reengineering for Sustainable Social Innovation in the Indian IT Industry 1

Blockchain-Enabled Financial Reengineering for Sustainable S...

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1st international conference on Advances in computer science, Electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Tirpude, Raman Kowtal, Jayashree Palav, Manesh R. Ganapa, Jhansi Rani Shrivastava, Namrata Moholkar, Nilambari Maharashtra National Law University Nagpur India Ramaiah Institute of Management General Science Building Karnataka MSR Nagar MSRIT Campus Bengaluru India Global Business School & Research Centre MBA department Dr. D.Y.Patil Vidyapeeth Maharashtra Pimpri Pune India Centurion University of Technology and Management Andhra Pradesh India The Bhopal School of Social Sciences Department of Economics Madhya Pradesh Bhopal India Dr.D.Y.Patil Institute of Technology Pimpri Pune India

ISBN: (纸本)9798331518578

Blockchain enabled financial system enhance the efficiency, security and transparency. The study examines the sustainable social innovation in the Indian IT industry. It leverages the decentralized nature of blockchain so that the organizations streamline the financial operations, enhance accountability and reduce fraud to foster economic growth. The study examines the applications of blockchain including secure digital payments, decentralized finance and smart contracts and the impact on initiatives for corporate sustainability. The challenges are highlighted in the study including adoption hurdles, scalability and regulatory barriers. The findings suggest development of business model with social responsibility to promote long-term sustainability in Indian IT sector. © 2025 IEEE.

关键词： Decentralized finance

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Enhancing Cloud Infrastructure Security with GraphSAGE-Based Intrusion Detection Systems 1

Enhancing Cloud Infrastructure Security with GraphSAGE-Based...

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1st international conference on Intelligent Systems and Computational Networks, ICISCN 2025

作者： Kumar, G. Nanda Kishor Syed, Shakir Mogal, Amit Karbhari Abid, Tahera Perada, Anvesh Suneetha, Sampathirao University of South Florida United States Malla Reddy University Department of Computer Science and Engineering Hyderabad India Bargersville IN United States Mvp Samaj's Cmcs College Department of Computer Science and Application Nashik India Nawab Shah Alam Khan College of Engineering and Technology Department of Information Technology Hyderabad India Drexel University Department of Electrical and Computer Engineering Philadelphia United States Koneru Lakshmaiah Education Foundation Department of Computer Science and Engineering Vaddeswaram India

ISBN: (纸本)9798331529246

Cloud computing provides scalable and adaptable infrastructure however is significantly susceptible to cyber-attacks. This work presents a hybrid methodology that integrates the GOA and GA for feature selection, alongside the Residual GraphSAGE model for intrusion detection. The hybrid GOA-GA method enhances feature selection by optimizing the balance between exploration and exploitation, mitigating overfitting, and augmenting classification performance. The Residual GraphSAGE model alleviates over smoothing while effectively capturing node and edge interactions for precise intrusion classification. Assessment on a benchmark dataset reveals exceptional performance, attaining an accuracy of 91.74%, surpassing established models such as GCN and ResNet. This study emphasizes the need of hybrid optimization and sophisticated graph-based learning in improving cloud infrastructure security. © 2025 IEEE.

关键词： Network intrusion

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