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ZCube: A Zero-Trust, Zero-Knowledge, and Zero-Memory Platform for Privacy and yet Secured Access 6

ZCube: A Zero-Trust, Zero-Knowledge, and Zero-Memory Platfor...

引用

6th IEEE International Conference on Trust, Privacy and Security in Intelligent Systems, and Applications, TPS-ISA 2024

作者： Quach, Vinh Dantu, Ram Talapuru, Sirisha Zaman, Shakila Pokharel, Apurba University of North Texas Dept. of Computer Science and Engineering DentonTX United States

ISBN: (纸本)9798350386745

As concerns over privacy and trust escalate among individuals and corporations, traditional memory-based trust systems are increasingly seen as inadequate and undesirable. The rise of microservice architecture complicates this by making data paths harder to track. Given these concerns, the critical question arises: How can we establish trust or verify an entity's credibility without collecting private information or relying on comparisons with pre-existing data, while knowing the exact data path of each request? To address this challenge, we introduce a lightweight, scalable, ZCube platform that employs nested Zero Knowledge Proofs (ZKPs), eliminating reliance on memory or evaluations based on past actions. This platform verifies and maintains trust in real-time without centralizing trust in any specific part of the system. It anticipates intentions and rigorously monitors them, ensuring operational integrity while preserving privacy. Distinctive for its ZKP trustless setup incorporating blockchain, each request begins anew and is rigorously monitored bidirectionally during execution. Our tests on the realistic example of a microservice-based distributed system, OpenTelemetry Demo, confirm that our novel approach - combining proof segmentation with plan adherence - exhibits fast response times of less than 200ms on average for most test cases. This ZCube platform surpasses traditional methods in efficiency and security. Our analysis shows comprehensive security and enhanced performance while effectively maintaining bidirectional trustlessness. © 2024 IEEE.

关键词： Differential privacy

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Deciphering Deceit: Multimodal Classification of Optimal Algorithms for Fake Website Detection 3

Deciphering Deceit: Multimodal Classification of Optimal Alg...

引用

3rd IEEE International Conference on Blockchain and Distributed Systems Security, ICBDS 2024

作者： Thombre, Supriya Doifode, Vaibhaw Kokardekar, Sakshi Hasija, Udit Wazalwar, Sampada Yeshwantrao Chavan College of Engineering Dept. of Computer Technology Nagpur India Yeshwantrao Chavan College of Engineering Dept. of Electrical Engineering Nagpur India Kpit Technologies Limited Pune India Bhartiya Vidyapeeth College of Engineering Dept. of Computer Science and Engineering New Delhi India G.H. Raisoni College of Engineering Dept. of Information Technology Nagpur India

ISBN: (纸本)9798350354348

Detecting fake website URLs is crucial in today's digital era, where online scams and malicious/ fraudulent activities abound. Such websites pose a myriad of problems in the digital landscape, ranging from financial loss and identity theft to the dissemination of misinformation and the erosion of trust in online platforms. Individuals who fall victim to fraudulent websites may suffer financial repercussions, as they may unknowingly disclose confidential information such as details of credit card or login credentials. Moreover, fake websites can deceive users by spreading false information or promoting illegitimate products and services, which can undermine public trust in online sources and exacerbate societal issues such as misinformation and cybercrime. Therefore, there is a pressing need to detect fake websites promptly to mitigate these risks and protect users' privacy, financial security, and trust in the online environment. This study by the authors evaluates the predictive performance of five machine learning (ML) models - Random Forest (RF) Classifier, Decision Tree (DT)) Classifier, K-Neighbors (KN) Classifier, SGD Classifier and Gaussian NB (GNB) - in the reference of malicious and fake website URL detection. Leveraging a diverse dataset encompassing both benign and malicious URLs, our analysis encompasses rigorous evaluation metrics. The results highlight distinct strengths and weaknesses among the models, offering valuable insights for practitioners seeking to optimize predictive capabilities in the realm of cybersecurity. These findings contribute to the ongoing refinement of machine learning strategies for effective malicious URL detection and mitigation. © 2024 IEEE.

关键词： Phishing

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Strategies for Data Security and Privacy Protection in Cloud Infrastructure 3

Strategies for Data Security and Privacy Protection in Cloud...

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3rd IEEE International Conference on Blockchain and Distributed Systems Security, ICBDS 2024

作者： Naikwade, Namrata Pathan, Shafi Mit Art Design and Technology University Dept. of Computer Science & Engineering Pune India

ISBN: (纸本)9798350354348

In today's rapidly growing digital era, cloud computing has emerged as an important technology, providing the ability to scale resources efficiently, accessibility, and cost-effectiveness for storing and processing huge amounts of data. However, alongside its numerous benefits, the adoption of cloud computing has also introduced deep concerns regarding data protection and privacy. The current scenario of cloud computing is characterized by increase in usage of cloud services and an exponential growth of data. While organizations leverage the cloud to enhance agility and innovation, the data sharing ability of cloud and the outsourcing of data management raise significant challenges for ensuring the privacy, integrity, and availability of sensitive data. Moreover, the rising cyber threats, regulatory compliance requirements, and the possibility for unauthorized access bring out the critical importance of robust data protection mechanisms in the cloud *** paper presents a comprehensive survey of strategies for data protection and identity protection in the context of cloud based systems. It examines encryption techniques, access control mechanisms, identity management solutions, among other approaches, highlighting their strengths, limitations, and applicability in different cloud deployment models and use cases. Furthermore, the paper discusses emerging trends such as homomorphic encryption, Attributes Based Encryption (ABE) Schemes and Identity Based Encryption (IBE), which hold promise for enhancing data protection in the developing landscape of cloud technology. © 2024 IEEE.

关键词： Cloud security

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Classifying Alzheimer's Disease Stages via Bootstrap Aggregation of CNN Architectures on MRI Scans 1

Classifying Alzheimer's Disease Stages via Bootstrap Aggrega...

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1st International Conference on Pioneering Developments in computer science and Digital Technologies, IC2SDT 2024

作者： Neeharika, S. Rao, D. Rajeswara Nagaveni, V. Lalitha V.R. Siddhartha Engineering College Computer science Dept. Vijayawada India

ISBN: (纸本)9798350365016

Alzheimer's disease (AD) presents a pressing challenge in healthcare globally, necessitating timely and accurate diagnosis for effective management. Magnetic Resonance Imaging (MRI) holds promise for AD detection due to its ability to reveal structural brain changes. However, manual MRI analysis is labor-intensive and prone to human error. To tackle these issues, this study proposes a novel method for AD classification using ensemble learning with Convolutional Neural Network (CNN) architectures-specifically, CNN, Inception V3,DenseNet121, and MobileNet-leveraging bootstrap aggregation. This ensemble approach diversifies training data subsets, leading to enhanced accuracy. The proposed model achieved an impressive 84% accuracy with bootstrapping and 94 % without. Additionally, specificity values underscore the model's robustness, with 0.93 and 0.97 for bootstrapped and non-bootstrapped ensembles, respectively. This innovative approach not only improves accuracy but also addresses scalability and generalization challenges, offering promise for AD diagnosis and management based on neuroimaging data. © 2024 IEEE.

关键词： Convolutional neural networks

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Textual Authenticity in the AI Era: Evaluating BERT and RoBERTa with Logistic Regression and Neural Networks for Text Classification 16

Textual Authenticity in the AI Era: Evaluating BERT and RoBE...

引用

16th International Symposium on Electronics and Telecommunications, ISETC 2024

作者： Hazim, Layth Rafea Ata, Oguz Altinbas University Dept. of Electrical and Computer Engineering Istanbul Turkey College of Computer Science and Mathematics Tikrit University Tikrit Iraq Altinbas University Dept. of Software Engineering Istanbul Turkey

ISBN: (纸本)9798350390865

AI-generated content impersonating human writing is an issue that has gained attention as AI spreads its wings. This particular study serves as a comparison between the existing Logistic Regression and Feedforward Neural Networks (FNNs) by employing sentence-BERT-appended models and RoBERTa in the determination of authenticity in a given text. A dataset that was balanced between human-written and AI-generated texts was utilized. Techniques like tokenization and normalization were first used, followed by feature extraction using transformer-based models. Cross-validation and confusion matrix analysis that used measures such as accuracy, precision, recall, F1 score, and ROC AUC were included to guarantee the models' robustness. The hybrid RoBERTa-FNN model that was deposed challengers was the most outstanding model in respect of precision and recall, and the highest accuracy (99.95%) was obtained as mentioned in the data. The improved performance serves as a proof of how effectively RoBERTa uses its embeddings to represent context on the fine-grained level required for this kind of text classification. This work is a stepping stone to the creation of strong AI text detection systems, besides our advancements to the knowledge of models and embedding performance with respect to text classification. The results lay emphasis on the selection of model configuration and the embedding technique, as they are the key factors in achieving the best results in practical applications. © 2024 IEEE.

关键词： Logistic regression

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Semi-automatic performance support robot that can attach and detach guitars 13

Semi-automatic performance support robot that can attach and...

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13th IEEE Global Conference on Consumer Electronic, GCCE 2024

作者： Tsurumi, Kazuki Marutsuka, Ryo Koutaki, Gou Kumamoto University Dept. of Computer Science and Electrical Engineering Kumamoto860-8555 Japan

ISBN: (纸本)9798350355079

Research has primarily focused on fully automatic instrument-playing robots. However, it is difficult to support the experience of playing musical instruments for people with physical disabilities or those who are inexperienced in playing musical instruments. To address this issue, we studied a "semi-automatic"instrument-playing robot based on human-robot collaboration. Our research specifically focused on the guitar, which are stringed instruments with complex pressed strings. The developed robot enables individuals with physical disabilities and those without musical experience to easily play musical instruments. Additionally, the instruments can be easily removed without causing damage. © 2024 IEEE.

关键词： User centered design

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Experimental Validation of Blockchain Based Triple Branch MRC for Secured Communication in Adverse Fading Conditions

Experimental Validation of Blockchain Based Triple Branch MR...

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2024 IEEE Region 10 Symposium, TENSYMP 2024

作者： Upadhyay, Deepak Upadhyay, Abhay Gupta, Mridul Sharma, Kunj Bihari Maindola, Meenakshi Garg, Shobhit Graphic Era Hill University Dept. of Computer Science and Engineering Dehradun India Graphic Era Deemed to be University Dept. of Computer Science and Engineering Dehradun India Graphic Era deemed to be University Dept. of Electronics and Communication Engineering Dehradun India Graphic Era Deemed to be University Dept. of Management Studies Dehradun India

ISBN: (纸本)9798350364866

The investigation in this study entails integrating blockchain technology with maximal ratio combining in a triple branch configuration for secure communications under multipath fading conditions. The proposed combines blockchain's decentralized and immutable characteristics with MRC's communication outcomes and flaws, which are worsened by the multipath fading channels. To evaluate this, the team carried out various empirical tests with the key findings being the Signal-to-Noise Ratio performance. Since the blockchain integrated system is anticipated to exhibit a higher SNR, our results showed a substantial increase in SNR. This confirms the robust and secure communication capabilities of the integrated solution under study. Therefore, the researchers demonstrate how blockchain can greatly enhance security as well as the quality of the communication, presenting a better solution in challenging data transmission conditions. This study establishes the foundation for further research on blockchain technology applications in the communication field. © 2024 IEEE.

关键词： Blockchain

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Futuristics Technologies for Reduction of Plastic Waste 13

Futuristics Technologies for Reduction of Plastic Waste

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13th International Conference on System Modeling and Advancement in Research Trends, SMART 2024

作者： Dhiman, Riya Sharma, Ashish Chandigarh University Dept. of Computer Science Mohali India Chandigarh University Dept. of Electrical Engineering Mohali India

ISBN: (纸本)9798350380583

Plastic plays a vital role in daily life most of the food items, Baggies, vegetables are packed in plastic material. As plastic is non-biodegradable there are harming effect on human beings and animals. Due to these global warming also increases. Although 80% Fishes, 88% Vertebrates, 56% Mammals and 52% Reptiles are affected due to plastic waste. In this work with the various techniques proposed like Eco-bricks, Furniture, Replace Plastic By Bamboo and also Doormats are made through the Plastic Waste. It is seen that by using above techniques significantly reduce the harmful effect of plastic and there is improvement in life of human beings and animals also the alternative techniques to reuse the plastic and to replace plastic are proposed with which there is a increase in the earning of poor peoples. Above techniques are helpful to decrease the employment and also by using these techniques more than 60% of plastic reuse, with this the temperature is also decreased. © 2024 IEEE.

关键词： Invertebrates

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Real-Time Traffic Management System Using YOLOv8 and CNN: A Deep Learning Approach with IoT Integration 1

Real-Time Traffic Management System Using YOLOv8 and CNN: A ...

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1st International Conference on Advances in computer science, Electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Saklani, Sumit Manchanda, Mahesh Sharma, Raman Singh, Devendra Graphic Era Hill University Dept. of Computer Science and Engineering Dehradun India Graphic Era Deemed to be University Dept. of Computer Application Dehradun India

ISBN: (纸本)9798331518578

Traffic management also plays a crucial role in urban planning and development, with pressing challenges related to congestion, safety, and environmental impact. In this study, we proposed a real time traffic control system using YOLOv8 and CNNs combined with Internet of Things (IoT) technologies. As a high-performing object detection model, YOLOv8 is able to accurately and rapidly detect vehicles, pedestrians, and other traffic objects. When combined with CNN based data analytics, the proposed system can successfully monitor traffic flow, discover irregularities, and control the signals dynamically. Creating a cohesive framework for intelligent decision-making IoT integration ensures real-time data acquisition from sensors, cameras and edge devices. IoT framework for a smart urban environment the proposed architecture provides the versatility through scalability, low latency, and adjustment to several urban perspective scenarios. The combination leads to greatly enhanced traffic flow efficiency, accident prevention and environmental impact reduction as experimental results show. With data till October 2023, this study resolves a gap between the developing field of deep learning and the Internet of Things (IoT), that creates to be utilized to connect to advanced town environments. © 2025 IEEE.

关键词： Decision making

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IoT-driven automatic vehicle accident rescue system implemented with Proteus 1

IoT-driven automatic vehicle accident rescue system implemen...

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1st International Conference on Optimization Techniques for Learning, ICOTL 2023

作者： Hemalatha, K. Ganga Devi, S.V.S. Deepika, V. Madanapalle Institute of Technology and Science Dept. of Computer Science & Engineering-Artificial Intelligence Andhra-Pradesh Madanapalle India Madanapalle Institute of Technology and Science Dept. of Computer Science & Engineering-Cyber Security Andhra-Pradesh Madanapalle India Sri Venkateswara College of Engineering Dept. of Computer Science & Engineering Andhra-Pradesh India

ISBN: (纸本)9798350328042

IoT-driven automatic vehicle accident rescue system implemented with Proteus is an inventive solution aimed at enhancing emergency response and rescue operations following vehicle accidents. Given the rising vehicle usage alongside population growth, the frequency of accidents has also surged over time, leading to unfortunate loss of life due to delays in ambulance arrival at accident scenes. Swift transportation of accident victims to medical facilities is of paramount importance. Upon occurrence of an accident, the proposed "IoT-driven automatic vehicle accident rescue system implemented with Proteus"immediately transmits accident details to the ambulance service, investigation unit, and designated emergency contacts. Simultaneously, the accident's precise location is shared via a Google Maps link to the users' smart devices equipped with mobile network connectivity. This facilitates efficient location identification for both ambulance services and police departments. Comprising elements such as accelerometers, GPS (Global Positioning System) modules, GSM (Global System for Mobile Communication) modules, motors, buzzers, LEDs, and more, the system seamlessly integrates these components with a central microcontroller unit using Proteus software. The core objective of this initiative revolves around two key goals: rescuing drivers involved in accidents and expediting victim recovery during the critical early stages of mishaps. © 2023 IEEE.

关键词： Global system for mobile communications

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