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IoT Devices Authentication Using Artificial Neural Network

computers, Materials & Continua 2022年第2期70卷 3701-3716页

作者： Syed Shabih Ul Hasan Anwar Ghani Ikram Ud Din Ahmad Almogren Ayman Altameem Department of Computer Science and Software Engineering International Islamic University Islamabad45000Pakistan Department of Information Technology The University of Haripur22620HaripurPakistan Chair of Cyber Security Department of Computer ScienceCollege of Computer and Information SciencesKing Saud UniversityRiyadh11633Saudi Arabia Chair of Cyber Security Department of Natural and Engineering SciencesCollege of Applied Studies and Community ServicesKing Saud UniversityRiyadh11543Saudi Arabia

User authentication is one of the critical concerns of information *** tend to use strong textual passwords,but remembering complex passwords is hard as they often write it on a piece of paper or save it in their mobile *** passwords are slightly unprotected and are easily *** attacks include dictionary,shoulder surfing,and brute *** passwords overcome the shortcomings of textual passwords and are designed to aid memorability and ease of *** paper proposes a Process-based Pattern Authentication(PPA)system for Internet of Things(IoT)devices that does not require a server to maintain a static password of the login *** server stores user’s information,which they provide at the time of registration,i.e.,the R-code and the symbol,but the P-code,i.e.,the actual password,will change with every login attempt of *** this scheme,users may draw a pattern on the basis of calculation from the P-code and Rcode in the PPA pattern,and can authenticate themselves using their touch dynamic behaviors through Artificial Neural Network(ANN).The ANN is trained on touch behaviors of legitimate users reporting superior performance over the existing *** experimental purposes,PPA is implemented as a prototype on a computer system to carry out experiments for the evaluation in terms of memorability and *** experiments show that the system has an effect of 5.03%of the False Rejection Rate(FRR)and 4.36%of the False Acceptance Rate(FAR),respectively.

关键词： Implicit authentication behavioral authentication artificial neural network processed pattern authentication

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A Comprehensive Vulnerability Tools Analysis for security and Control in IT Environment and Organizations

A Comprehensive Vulnerability Tools Analysis for Security an...

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Electronics and Sustainable Communication Systems (ICESC), 2020 International Conference on

作者： Aryan Chaturvedi Bhumi Lakhani Tanisha Agarwal Mohana Minal Moharir Ashok Kumar A R Computer Science and Engineering (Cyber Security) RV College of Engineering® Bengaluru India

ISBN: (数字)9798350379945

ISBN: (纸本)9798350379952

This research study analyzes the potential of integrating OpenVAS, Wireshark, Nmap, and Metasploit for comprehensive vulnerability analysis and assessment in IT environment and various public and private organizations. Open VAS serves as a robust vulnerability scanning platform, while Wireshark monitors network traffic for potential threats. Nmap identifies open ports and vulnerabilities, and Metasploit facilitates ethical penetration testing. Together, these tools empower organizations to proactively pinpoint and address security weaknesses, strengthening defense against cyber threats. The paper advocates for consistent deployment within a unified vulnerability management strategy, contributing to a proactive and effective approach in safeguarding against cybersecurity challenges.

关键词： Ethics Electric potential Communication systems Organizations Telecommunication traffic computer crime Monitoring Penetration testing

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Efficient UAV Routing Strategies for Wireless Sensor Network Data Retrieval

Efficient UAV Routing Strategies for Wireless Sensor Network...

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2024 International Conference on Decision Aid sciences and Applications, DASA 2024

作者： Ahmed, Amjed Abbas Al-Sharhanee, Kareem Ali Malalah Najim, Ali Hamza Alheeti, Khattab M. Ali Satar, Nurhizam Safie Mohd Hashim, Aisha Hassan Abdallah Universiti Kebangsaan Malaysia Center for Cyber Security Faculty of Information Science and Technology Bangi Malaysia Department of Computer Techniques Engineering Baghdad Iraq College of Engineering Techniques Department of Communication Technical Engineering Al-Farahidi University Baghdad10011 Iraq Department of Computer Technical Al-Diwaniyah Iraq College of Computer and Information Technology University of Anbar Computer Networking Systems Department Anbar Iraq Center for Cyber Security Faculty of Information Science and Technology Bangi43600 Malaysia International Islamic University Malaysia Faculty of Engineering Department of Electrical and Computer Engineering Selangor Malaysia

ISBN: (纸本)9798350369106

WSNs are applied in many disciplines where certain conditions require the ability to adapt to network sink mobility and changes in the dynamics of the area coverage. To meet these needs, it is necessary to develop integrated systems where the ''terrestrial' systems and the Unmanned Aerial Vehicles (UAVs)' collect data from sensors efficiently. Planning of UAV trajectories is another challenging issue if many WSN nodes are randomly deployed. This challenge has a big impact on the overall effectiveness of the system. This paper presents a novel approach for reducing the traveled distance of unscrewed aerial vehicles (UAVs) to improve the data collection efficiency in WSNs with poor node density. Yet the method that has been developed is aimed at increasing 'the efficiency and efficacy of data collection... with the assistance of Unmanned Aerial Vehicles (UAVs)' which means this work reveals practical application solutions. © 2024 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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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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A Comprehensive Analysis of Social engineering Attacks: From Phishing to Prevention - Tools, Techniques and Strategies

A Comprehensive Analysis of Social Engineering Attacks: From...

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

作者： Sarthak Gupta Mayank Pritwani Adarsh Shrivastava 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

As the digitalization has accelerated, Social engineering Attacks have emerged as a prevalent threat in contemporary cybersecurity landscapes. This paper provides a comprehensive exploration of Social engineering Attacks, encompassing their phases, types, and associated tools for simulation and defense across Windows and Linux platforms. Furthermore, it analyzes the role of Artificial Intelligence in both detecting and combating Social engineering Attacks, highlighting its applications and implications. Additionally, the paper addresses design and implementation challenges inherent in combating such attacks and discusses crucial precautions that users must undertake to safeguard themselves against these evolving threats.

关键词： Technological innovation Navigation Prevention and mitigation Phishing Linux Education Organizations Internet of Things Artificial intelligence Research and development

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GPS Based Efficient Real Time Vehicle Tracking and Monitoring System Using Two Factor Authentication and Internet of Things (IoT)

GPS Based Efficient Real Time Vehicle Tracking and Monitorin...

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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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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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