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Intelligent cyber Physical Systems and Internet of Things (ICoICI), International Conference on

作者： S Jeevan Kishan Karthik S Jayanth Sharma Mohana Minal Moharir Ashok Kumar A R Computer Science and Engineering (Cyber Security) RV College of Engineering® Bengaluru India

ISBN: (数字)9798331540661

ISBN: (纸本)9798331540678

Vehicle tracking systems have evolved significantly over the years, transitioning from simple passive tracking devices to real-time monitoring systems that utilize global positioning system (GPS) and global system for mobile communications (GSM). These advancements have enabled more precise tracking, better communication capabilities, and enhanced control over vehicle operations. Despite these improvements, there remains a persistent need for systems that are not only reliable but also incorporate multiple layers of security to prevent unauthorized access and use. This research paper introduces GPS and GSM based tracking system designed to significantly enhance vehicle safety and provide real time location monitoring. The system utilizes an Arduino Uno as the primary control unit, interfaced with a GSM module (SIM800L) for communication and a GPS module (NEO-6M) for precise tracking of the vehicle's location. Key components include a relay-controlled ignition switch and a key lock system to manage vehicle startup, a fingerprint sensor for advanced biometric authentication, and a buzzer for auditory alerts. The entire system operates on a 9 $V$ power supply, with voltage regulation managed by an LM2596 step-down converter. This integration of hardware components ensures robust vehicle tracking, remote control capabilities, and heightened security measures, thereby offering an effective solution for personal vehicle safety and efficient fleet management. In an average, for every 10 iterations we observed that 9 iterations are where successful, which shows that the efficiency was 90 % as there was delay in sending and receiving messages.

关键词： GSM Vehicle safety Authentication Real-time systems Hardware security Internet of Things Monitoring Remote control Global Positioning System

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An Urban Electric Vehicle Charging System via Hybrid Heterogeneous Modes

An Urban Electric Vehicle Charging System via Hybrid Heterog...

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2024 IEEE International Conference on Systems, Man, and cybernetics, SMC 2024

作者： Zhang, Keyang Liu, Yueheng Liu, Shuohan Gao, Junqiao Cao, Yue Ahmad, Naveed Zhang, Xu School of Cyber Science and Engineering Wuhan University China Wuhan Cyber Security Association China Qilu University of Technology China College of Computer and Information Sciences Prince Sultan University Riyadh Saudi Arabia Norwich United Kingdom

ISBN: (纸本)9781665410205

Electric Vehicle (EV) is regarded as the optimal alternative to traditional fuel-powered vehicles. However, the exponential surge in EV charging demand poses challenges in charging infrastructure planning and charging behavior management. The efficacy of traditional Grid-to-Vehicle (G2V) charging mode, which obtains power from the grid, is curtailed by the limited number and uneven distribution of charging facilities, inevitably leading to charging congestion. Instead, the concept of Vehicle-to-Vehicle (V2V) charging has emerged as a spatio-temporally flexible charging mode, which expands EV's role from consumer to provider, forming V2V pairs and utilizing urban Parking Lots (PLs) as charging locations. In this paper, we propose a Hybrid Heterogeneous Modes (HHM)-based EV charging optimization scheme in urban settings. Building upon the G2V mode, we introduce synchronous and asynchronous V2V charging modes as optimization strategies, integrating and exploiting the unique advantages of each mode. We also utilize global EV charging scheduling and comprehensively take four dimensions into consideration (energy trading cost, travel cost, waiting time cost and loss cost), thus achieving flexible mode selection, V2V pairing, and designated charging locations. Simulations confirm the effectiveness of the proposed scheme in reducing total charging costs, optimizing user service experiences, and improving charging facility utilization rates. © 2024 IEEE.

关键词： Charging stations

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Collecting and analyzing key-value data under shuffled differential privacy

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Frontiers of computer science 2023年第2期17卷 241-243页

作者： Ning WANG Wei ZHENG Zhigang WANG Zhiqiang WEI Yu GU Peng TANG Ge YU Faculty of Information Science and Engineering Ocean University of ChinaQingdao 266100China School of Computer Science and Engineering Northeastern UniversityShenyang 110819China Key Lab of Cryptologic Technology and Information Security Ministry of EducationShandong UniversityQingdao 266200China School of Cyber Science and Technology Shandong UniversityQingdao 266200China

1 Introduction Key-value data,as NoSQL data widely used in recent years,has been frequently collected and used for analysis in major websites and mobile *** frequency distribution estimation on the key domain,as well as the mean estimation of values associated with the same key,are crucial and worth billion dollars in the ***,in real applications,the key-value records are submitted by terminal devices of different *** collecting the information from users may pose serious risks on personal *** the other hand,the emerging shuffled differential privacy(SDP)model[1]is proposed to collect sensitive data from users.

关键词： NoSQL app value

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Smart Health Monitoring and Anomaly Detection Using Internet of Things (IoT) and Artificial Intelligence (AI)

Smart Health Monitoring and Anomaly Detection Using Internet...

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Intelligent cyber Physical Systems and Internet of Things (ICoICI), International Conference on

作者： Prabu Jayant Elvis Vincent Mohana Minal Moharir Ashok Kumar A R Computer Science and Engineering (Cyber Security) RV College of Engineering® Bengaluru India

ISBN: (数字)9798331540661

ISBN: (纸本)9798331540678

Smart health monitoring systems, powered by AI and IoT, are transforming healthcare by enabling continuous, real-time patient monitoring. In India, where lapses in health monitoring contribute to 20% of premature deaths, our innovative solution addresses this urgent need. Designed specifically for elderly care, the system integrates advanced technology for health monitoring and medication management. It continuously tracks vital signs like heart rate, ECG, and temperature, sending immediate alerts to caregivers and medical professionals upon detecting abnormalities. This proactive approach not only enhances patient care and response times but also supports preventative care, ensuring timely interventions. With its comprehensive monitoring and user-friendly interface, the system is crucial for improving elderly healthcare.

关键词： Heart rate Temperature Smart healthcare Electrocardiography Real-time systems Internet of Things Time factors Older adults Artificial intelligence Monitoring

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Facial Expressions and EEG Signals for Emotion Recognition Using Deep2 Face Algorithm 10

Facial Expressions and EEG Signals for Emotion Recognition U...

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10th International Conference on Advanced Computing and Communication Systems, ICACCS 2024

作者： Swetha, S. Babu, Nirmal Varghese Karunya Institute of Technology and Science Division of Computer Science and Engineering Karunya Nagar Tamil Nadu Coimbatore India Karunya Institute of Technology and Science Division of Data Science and Cyber Security Karunya Nagar Tamil Nadu Coimbatore India

ISBN: (纸本)9798350384369

Emotions, the essence of human connection and understanding, take center stage in this pioneering research on emotion recognition. We look at identifying common emotions including joy, sorrow, neutral, anger, fear, and surprise. Introducing an innovative approach, we seamlessly blend advanced computer vision algorithms and intricate signal processing techniques to concurrently analyze facial expressions and EEG signals. The heart of our methodology lies in the utilization of the state-of- the-art Deep Face Analyzer, guided by the deep2face algorithm for meticulous interpretation of facial features, coupled with a spectrographic analyzer translating EEG signals into spectrograms. The overarching goal is to enhance the accuracy and resilience of emotion recognition, with the added dimension of a real-time Waveform Extractor for dynamic evaluation of audio signals. Within the landscape of diverse algorithms and modalities, the Hybrid Model (CNN + LSTM) emerges as a standout performer, achieving an impressive 88.2% accuracy by synergizing facial expressions and EEG signals. The strategic integration of long short-term memory (LSTM) networks with convolutional neural networks (CNNs) underscores the model's exceptional capacity to capture the nuanced intricacies of human emotions. Beyond mere technological advancement, this study underscores the importance of embracing multiple modalities for a holistic understanding of emotions, positioning the Hybrid Model as a powerful and nuanced tool for precise and multiclass emotion identification across diverse real-world scenarios. In essence, our research charts a path where the realm of emotions converges with technological innovation, fostering a deeper understanding of the human experience © 2024 IEEE.

关键词： Emotion Recognition

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Intrusion Detection in Network Traffic Using LSTM and Deep Learning

Intrusion Detection in Network Traffic Using LSTM and Deep L...

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International Conference on Computing and Networking Technology (ICCNT)

作者： Prabu Jayant M Prathica Shetty S Jeevan Mohana Minal Moharir A R Ashok Kumar Computer Science and Engineering (Cyber Security) RV College of Engineering® Bengaluru India

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

Network Intrusion Detection system (NIDS) helps in detecting the traffic and avoids any potential harm to the system. LSTM is a deep learning model architecture that uses recurrent neural networks (RNN) for handling sequential data. Unlike traditional IDS that depend on fixed signatures, LSTMs can interpret network traffic patterns and detect anomalies that indicate new attack methods. This flexibility makes it more effective against evolving cyber threats. While traditional IDS may only detect malicious activity, LSTMs can predict the specific type of attack by analyzing traffic sequences. This improved accuracy enables quicker and more targeted response strategies to prevent cyber threats. LSTMs have the capability to analyze network traffic data in real-time, allowing for immediate threat identification. The obtained accuracy and F1 score of the model are ${9 2. 8 3 \%}$ and ${9 4. 2 5 \%}$ respectively. This real-time analysis enables faster response times and classification of cyberattacks, reducing the potential impact of any security breaches.

关键词： Deep learning Accuracy Recurrent neural networks Telecommunication traffic Real-time systems Threat assessment Time factors computer crime Protection Long short term memory

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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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Tracking Objects and Activities with Attention for Temporal Sentence Grounding 48

Tracking Objects and Activities with Attention for Temporal ...

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48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023

作者： Xiong, Zeyu Liu, Daizong Zhou, Pan Zhu, Jiahao Huazhong University of Science and Technology Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering China Peking University Wangxuan Institute of Computer Technology China

ISBN: (纸本)9781728163277

Temporal sentence grounding (TSG) aims to localize the temporal segment which is semantically aligned with a natural language query in an untrimmed video. Most existing methods extract frame-grained features or object-grained features by 3D ConvNet or detection network under a conventional TSG framework, failing to capture the subtle differences between frames or to model the spatio-temporal behavior of core persons/objects. In this paper, we introduce a new perspective to address the TSG task by tracking pivotal objects and activities to learn more fine-grained spatio-temporal behaviors. Specifically, we propose a novel Temporal Sentence Tracking Network (TSTNet), which contains (A) a Cross-modal Targets Generator to generate multi-modal templates and search space, filtering objects and activities, and (B) a Temporal Sentence Tracker to track multi-modal targets for modeling the targets' behavior and to predict query-related segment. Extensive experiments and comparisons with state-of-the-arts are conducted on challenging benchmarks: Charades-STA and TACoS. And our TSTNet achieves the leading performance with a considerable real-time speed. © 2023 IEEE.

关键词： computer vision

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IoMT-Based Healthcare Framework for Ambient Assisted Living Using a Convolutional Neural Network

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computers, Materials & Continua 2023年第3期74卷 6867-6878页

作者： Waleed T.Al-Sit Nidal A.Al-Dmour Taher M.Ghazal Ghassan F.Issa Department of Computer Engineering Mutah UniversityAl-KarakJordanHigher Colleges of TechnologyDubaiUAE Department of Computer Engineering College of EngineeringMutah UniversityJordan School of Information Technology Skyline University CollegeUniversity City SharjahSharjahUAE Center for Cyber Security Faculty of Information Science and TechnologyUKM43600BangiSelangorMalaysia

In the age of universal computing,human life is becoming smarter owing to the recent developments in the Internet of Medical Things(IoMT),wearable sensors,and telecommunication innovations,which provide more effective and smarter healthcare *** has the potential to shape the future of clinical research in the healthcare *** sensors,patients,healthcare providers,and caregivers can connect through an IoMT network using software,information,and communication *** assisted living(AAL)allows the incorporation of emerging innovations into the routine life events of *** learning(ML)teaches machines to learn from human experiences and to use computer algorithms to“learn”information directly instead of relying on a *** the sample size accessible for learning increases,the performance of the algorithms *** paper proposes a novel IoMT-enabled smart healthcare framework for AAL to monitor the physical actions of patients using a convolutional neural network(CNN)algorithm for fast analysis,improved decision-making,and enhanced treatment *** simulation results showed that the prediction accuracy of the proposed framework is higher than those of previously published approaches.

关键词： Smart healthcare system neural network machine learning

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Advancements in Operational Transconductance Amplifiers (OTAs) for Design, Applications & Performance Optimization Techniques with Hardware Implementation 3

Advancements in Operational Transconductance Amplifiers (OTA...

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3rd IEEE International Conference of Electron Devices Society Kolkata Chapter, EDKCON 2024

作者： Pramath, V. Pavithra, G. Ninawe, Swapnil S. Manjunath, T.C. Bengaluru India Dayananda Sagar College of Engineering Department of Electronics & Communication Engineering Karnataka Bangalore India Rajarajeswari College of Engineering Department of Computer Science & Engineering IoT Cyber Security & Block Chain Technology Karnataka Bangalore India

ISBN: (纸本)9798350374643

This research paper presents the design and simulation of a novel architecture for Multiple Path Fully Differential Operational Transconductance Amplifiers (OTAs) with a Dual Flipped Voltage Follower, specifically developed for VLSI-based signal processing applications. Utilizing advanced 50nm CMOS technology and Cadence tools, the proposed OTA architecture achieves enhanced performance and versatility in handling various signal processing tasks. Design employs multiple signal paths, which contribute to improvements in bandwidth, gain, and linearity, while also effectively minimizing common-mode noise. This multi-path approach ensures better signal integrity and reliability in high-performance applications. The integration of the Dual Flipped Voltage Follower further strengthens the OTA's stability and dynamic range, allowing it to operate seamlessly in high-speed VLSI systems. The architecture is designed to cater to the rigorous demands of modern signal processing, where precision and speed are critical. Extensive simulation studies were conducted to validate the OTA design, and the results demonstrate that the proposed approach meets or exceeds the stringent requirements of today's signal processing applications. Findings of this research contribute to the ongoing advancements in VLSI design methodologies and provide a promising solution for engineers working with nanoscale CMOS technologies. Simulation results using Cadence tools highlights effectiveness and robustness of proposed design. © 2024 IEEE.

关键词： CMOS integrated circuits

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