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11th International Conference on Information and Communication technology, ICoICT 2023

作者： Eghtessad, Shayan Hasanli, Turan Huynh, Richard Workneh, Kidus Ibrahem, Mohamed I. Fouda, Mostafa M. George Mason University Dept of Cyber Security Engineering FairfaxVA United States Augusta University School of Computer and Cyber Sciences AugustaGA United States Idaho State University Department of Electrical and Computer Engineering PocatelloID United States

ISBN: (纸本)9798350321982

As increasing vehicular technology is becoming more popular due to global climate change and the promotion of renewable energy sources, electric vehicles (EVs) with an array of improved features are becoming increasingly prevalent in the realm of automobile technology. As EVs require frequent charging sessions, it is integral to consider the potential privacy and security risks associated with the extensive data collected when charging or discharging from smart grids, smart buildings, or other EVs. This sensitive data includes users' locations, driver's licenses, and more. Therefore, preserving their privacy is a major concern. This paper investigates the existing privacy-preserving solutions developed in the literature to address these issues, including blockchain technology which is essential in protecting user data and thwarting privacy attacks around the charging station-to-vehicle (CS2V) and vehicle-to-vehicle (V2V). Additionally, privacy-preserving context-based online dispatching systems (PCOEDS) are presented as an effective strategy to authenticate users' information and protect their privacy in the context of vehicle-to-building (V2B) charging/discharging. Finally, a thorough comparison of the existing works is presented along with future research directions that will serve to further enhance the security levels of future EV transportation systems. © 2023 IEEE.

关键词： Privacy-preserving techniques

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Privacy-Aware Artificial Intelligence with Homomorphic Encryption using Machine Learning

Privacy-Aware Artificial Intelligence with Homomorphic Encry...

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2023 International Conference on Sustainable Computing and Smart Systems, ICSCSS 2023

作者： Srinivasa Rao, B. Chattopadhyay, Saumitra Singh, Prashant Hazela, Bramah Sabarinathan, G. Yamini, Kalva Department of Computer Science and Engineering Bachupally Telangana Hyderabad India Graphic Era Hill University Department of Computer Science and Engineering Dehradun India Amity University Amity School of Engineering and Technology Lucknow Department of Computer Science and Engineering Uttar Pradesh India Psna College of Engineering and Technology Department of Mathematics Tamilnadu Dindigul India Sri Ramachandra Institute of Higher Education and Research Cyber Security in Computer Science and Engineering Tamilnadu Chennai India

ISBN: (纸本)9798350333602

Along with the expansion of machine learning (ML) applications, the amount of data required to create predictions increases. Big-data ML has always been limited by off-chip memory capacity and computational speed. Considerably, privacy is one of the limitations of big data, which can be solved by homomorphic encryption (HE). Due to the combination of HE and ML, the multi-party privacy-protected ML suggested in this research may assist numerous users in doing artificial intelligence (AI) without disclosing private data. The technique may train common models in situations of data abuse, particularly in private data protection. The model trained using the ML technique named Artificial Neural Network (ANN) has a similar impact to the model developed using all data on a single computer, according to experiments using the algorithm. The gradient data is simply transmitted by all parties, and homomorphic procedures in the main computing system combine the gradient data. Besides, the optimal key is selected using the significance of the Lion Algorithm (LA). After homomorphic procedures, the learning model is modified depending on the new gradient data. © 2023 IEEE.

关键词： Neural networks

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Detecting Fake News on Twitter by Using Artificial Intelligence 3

Detecting Fake News on Twitter by Using Artificial Intellige...

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3rd International Conference on Advancement in Electronics and Communication engineering, AECE 2023

作者： Suhasini, R. Ratnamala, B. Sravanthi, Gurram Kumari, K. Prasanna Polamuri, Subba Rao Cmr College of Engineering and Technology Department of CSE-Cyber Security Hyderabad India Cmr Technical Campus Department of Ece Hyderabad India Odalarevu India

ISBN: (纸本)9798350330724

A great deal of information, particularly on social networking sites where individuals from all over the globe have continual and straightforward access to upload materials and messages, spreads rapidly throughout the world during the epidemic of Covid-19. The widespread dissemination of fake news may significantly impact people's mental and cognitive health. This case examines the dissemination of false information through Twitter during the coronavirus outbreak. This research presents a novel method for identifying misinformation spread over Tweets during the Covid-19 benchmark. The suggested technique is based on the combination of natural language processing, artificial intelligence, and deep learning, and it employs a categorization strategy that uses attributes unique to recent tweets. Apache Spark is used to implement the procedure in parallel. The experimental findings reveal that when combined with the randomly generated forest algorithm, this method produces extremely beneficial outcomes with an accuracy of 79%. It also shows that the tone of tweets is a crucial factor in identifying hoaxes. Indeed, this approach beats alternatives that do not consider contemporary tweets' unique qualities. © 2023 IEEE.

关键词： Deep learning

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Voice Controlled Humanoid Robot 3-D Printing Industrial Application 3

Voice Controlled Humanoid Robot 3-D Printing Industrial Appl...

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3rd International Conference on Artificial Intelligence and Signal Processing, AISP 2023

作者： Gupta, Amit Meeravali, Shaik Srinivas, K.Y. Chouhan, Arun Singh Malla Reddy University School of Engineering Department of Cyber Security Telangana India Malla Reddy Institute Technology and Science Department of ECE Telangana India

ISBN: (纸本)9798350320749

At this time this rapid evaluation industrial 5.0 age each and each company necessities rapidity in manufacturing to cope up with the customer's requirements. Each and each industrialist cannot meet the expense to revolutionize its unit from manual to semi-automatic or fully automatic, automation uneconomical in India. the essential objective of our project is to develop a flexible and low-cost humanoid that may be utilized in any industry to eliminate this problem. Our humanoid is utilized in the quantity of applications by changing the program of the controller and also the structure is intended in such how that it's proficient to gauge suitable loads but are often able to lift intermediate loads. Our humanoid has infinite possibilities of applications after implementing computing in it. it'll also work borders in situ of kinsmen so it'll help such a lot to our country. © 2023 IEEE.

关键词： Anthropomorphic robots

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Utilizing Machine Learning in Medical Diagnosis: Systematic Review and Empirical Analysis 24

Utilizing Machine Learning in Medical Diagnosis: Systematic ...

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24th International Arab Conference on Information technology, ACIT 2023

作者： Alazaidah, Raed Hassan, Mohammad Al-Rbabah, Lara Samara, Ghassan Yusof, Marina Al-Sherideh, Ala'a Saeb Zarqa University Ai Faculty of Information Technology Department of Data Science Zarqa Jordan Zarqa University Faculty of Information Technology Department of Computer Science Zarqa Jordan The Hashemite University Faculty of Engineering Department of Computer Engineering Zarqa Jordan Selanger Malaysia Zarqa University Faculty of Information Technology Department of Cyber Security Zarqa Jordan

ISBN: (纸本)9798350384307

During the last few years, several real-life applications have attempted to utilize the proven high capabilities of artificial intelligence in general and machine learning in particular. Machine learning has been utilized in several domains, such as spam detection, image recognition, recommendation systems, self-driving cars, and medical diagnosis. This paper aims to survey the most related work of utilizing machine learning in the domain of medical diagnosis. Moreover, the paper proposes a comparative analysis for identifying and determining the best classification model and feature selection method in mind of handling medical datasets. Hence, four different medical datasets have been used to train twenty-three classification models and four well-known feature selection methods with respect to several evaluation metrics such as Accuracy, True Positive ratio, False Positive ratio, Precision, and Recall. The results reveal that RandomForest, J48, and SMO classifiers are the best classifiers when it comes to handling medical datasets respectively. Furthermore, the Gain Ratio method is the best choice for handling the step of feature selection. © 2023 IEEE.

关键词： Classification Feature Selection Machine Learning Medical Diagnosis Prediction

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The Role of AI in Vehicle-to-Infrastructure Communication for Tolling Systems

The Role of AI in Vehicle-to-Infrastructure Communication fo...

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IEEE International WIE Conference on Electrical and computer engineering (WIECON-ECE)

作者： Mahalakshmi S Nithiya Baskaran Pachaivanna Partheeban Kowsalyadevi Krishnara Arjun S Department of Computer Science and Engineering Chennai Institute of Technology Kundrathur Chennai India Department Cyber Security Chennai Institute of Technology Kundrathur Chennai India Department Civil EngDepartment Cyber Security Chennai Institute of Technology Kundrathur Chennai India Department of Cyber Security Sona Institute of Technology Salem India

ISBN: (数字)9798331535476

ISBN: (纸本)9798331535483

The number of vehicles people use is substantial; thus, surveillance must be accurate. License plates are detected and recognized by detecting static and real-time images captured by the camera using OCR technology, computer vision, and AI in the tool booth and other important roads. This model can be used for many things, such as automated services, increased security, determining whether a car is registered, and identifying and validating vehicles connected to traffic violations. Real-time investigations are part of the automated recognition of license plates and their application to other traffic control and highway surveillance aspects. To detect plates from the images and in real-time video, Use Easy OCR with the license plates to read the plate number, utilize tensor flow object detection to detect and recognize, and save the detected license plate for further analysis and search.

关键词： computer vision Image recognition Tensors Surveillance Vehicle-to-infrastructure Object detection Traffic control Real-time systems Artificial intelligence License plate recognition

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Secure and efficient covert communication for blockchain-integrated SAGINs

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security and Safety 2024年第2期3卷 25-42页

作者： Weijia Li Yuan Zhang Xinyu He Yaqing Song School of Computer Science and Engineering(School of Cyber Security) University of Electronic Science and Technology of ChinaChengdu 611731China

Blockchain has brought great potential in improving Space-Air-Ground Integrated Networks(SAGINs)in terms of security and *** blockchain-integrated SAGINs,many applications and services inherently require both the communication contents and communication behaviors to be secure against eavesdroppers,in which a covert communication algorithm is always deployed as a fundamental communication ***,existing covert communication schemes suffer from critical *** the one hand,they require a sender to locally maintain a cryptographic key for a long period of time,which is very costly and inefficient to renew which means renewing the secret *** the other hand,the ciphertext of covertly sent data would explicitly appear in the network,and thereby the schemes are vulnerable to secret key *** this paper,we propose a secure and efficient covert communication scheme for blockchain-integrated SAGINs,dubbed CC-BSAGINs,to free the sender from maintaining secret *** key technique is to map the covertly sent data to some transactions on the underlying blockchain in a secure and efficient way;the mapping information is sent via a covert communication *** a two-step mechanism releases the sender from key management and does not require the ciphertext to be *** provide formal security proofs and conduct a comprehensive performance evaluation,which demonstrates the security and efficiency of CC-BSAGINs.

关键词： Covert communication blockchain Space-Air-Ground Integrated Networks

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Digital-Bracers: A Design Process for an Interactive Monitoring Generative System That Helps People with Hand Movements

Digital-Bracers: A Design Process for an Interactive Monitor...

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2023 International Symposium on World Ecological Design, ISWED 2023

作者： Yao, Yousheng Xie, Yuan Ying, Fangtian Wang, Haoran Huang, Zhihao Zheng, Junpeng Faculty of Humanities and Arts Macau University of Science and Technology China Hexiangning College of Art and Design Zhongkai University of Agriculture and Engineering China College of Computer and Cyber Security Fujian Normal University China

ISBN: (纸本)9781643685069

In the post-New Crown epidemic era, people need to face a period of physical recovery after being infected with New Crown, especially when there are frequent cases of deaths due to over-aggressive or excessive physical exercise after healing, or due to people's concerns about safety hazards, or loss of interest and adherence to fitness due to exercising alone, among other problems. In this paper, we design a complete interactive monitoring generation system for wrist brace components, Digital-Bracers, which consists of both hardware and software. The hardware has integrated textile heart rate monitoring and integrated sensors in a three-lead configuration for a textile-based digital wrist brace that conforms to human comfort. The software is a visualized app with pulse rate, speed, and frequency, oscillation rhythm, content generation social connectivity, etc. The software and hardware are connected via WI-FI or Bluetooth. Through exploration of materials, ergonomics, and textile wrist guard construction, we designed an experimental process and tested Digital-Bracers to determine the system's performance through peak heart rate detection and noise interference. The contribution of the Digital-Bracers Interactive Monitoring and Generation System is the ability to monitor one's own health in real-time during hand exercise to avoid potential risks, while at the same time, The Digital-Bracers Interactive Monitoring System contributes to the real-time monitoring of one's health during hand movements to avoid potential risks, and to the generation of a variety of different sounds to bring a sense of fulfillment and enjoyment to the hand movements. © 2024 The Authors.

关键词： Textiles

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Designing a Forensic Investigation Framework for IoT Monitoring and Modelling

Designing a Forensic Investigation Framework for IoT Monitor...

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2022 IEEE International Conference on Internet of Things and Intelligence Systems, IoTaIS 2022

作者： Jacob, Rijo Nisbet, Alastair Auckland University of Technology Cyber Security Research Laboratory School of Engineering Computer and Mathematical Sciences Csse Department Auckland New Zealand

ISBN: (数字)9798350396454

ISBN: (纸本)9798350396454

Securing a wireless digital scene for IoT based digital investigations has been problematic. Amongst the most pressing issues is the increasingly challenging task of identifying IoT devices. Practical difficulties arise from the rapid introduction, growing variety and likeness to ordinary physical objects of IoT devices. The mostly indistinguishable digital evidence sources are often overlooked during the forensic process of identification. The alternative means of IoT device identification, including from the Device Fingerprinting and Indoor Localisation areas, are lacking for the need of investigators to be able to accomplish the task of identification. To assist the search operations, including for IoT devices, a suitable approach is to reconstruct wireless sensing deployments ahead of the identification task. This, however, will require investigators to harness the communications of IoT devices. This paper apprises the salient features and capabilities desirable for an effective IoT monitoring and modelling system. A model of the envisaged system is light-weight and suited for both forensic and law enforcement purposes. The underlying principles of the contemporary model are three discrete aspects of IoT device communications, namely, monitorability, traceability and discoverability. © 2022 IEEE.

关键词： Wireless sensor networks

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Multi Label Classification Algorithm Based on Conditional Local Correlations among Labels and Ensemble Learning 25

Multi Label Classification Algorithm Based on Conditional Lo...

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25th International Arab Conference on Information technology, ACIT 2024

作者： Alazaidah, Raed Nasir, Ola Hadi, Wael Samara, Ghassan Al Daoud, Essam Aljaidi, Mohammad Khouj, Mohammed Talat Elsoud, Esraa Abu Alzoubi, Haneen Zarqa University Faculty of Information Technology Department of Data Science and Ai Zarqa Jordan Zarqa University Faculty of Information Technology Department of Computer Science Zarqa Jordan Petra University Faculty of Information Technology Department of Cyber Security Amman Jordan University of Business and Technology Department of Electrical Engineering Jeddah21432 Saudi Arabia Applied Science Private University Faculty of Information Technology Department of Computer Science Amman Jordan

ISBN: (纸本)9798331540012

Multi-Label Classification (MLC) is an advanced form of traditional classification, where each data instance is simultaneously associated with multiple labels. The importance of MLC has increased significantly in recent years, due to its wide range of application areas. Modern algorithms, when faced with the challenge of multiple labels, continue to show suboptimal performance, conversely, they show significantly superior performance when processing single-label datasets. This paper proposes a new algorithm to deal with the problem of transforming datasets from multiple labels to single labels by exploiting conditional and local correlations between labels after applying the Apriori predictive algorithm to extract relationships. Six ensemble learning models: Voting Hard, Voting Soft, Voting Weighted, Stacking LR, Stacking RF, and Stacking SVM, along with four classification models: SMO, DecisionStump, Random Forest, and Random Committee, were applied to three datasets. The algorithm showed effective and good performance by comparing the results of the proposed Multi Label Classification algorithm based on Conditional Local Correlations among Labels (MLC-CLCL) with several popular algorithms for dealing with multiple labels. © 2024 IEEE.

关键词： Contrastive Learning

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