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UPB Scientific Bulletin, Series C: Electrical engineering and computer Science 2024年第4期86卷 151-166页

作者： Bogdan, Ioana Corina Simion, Emil Faculty of Electrical Engineering and Computer Science Department of Electronics and Computers "Transilvania" University of Brasov & CiTi Brasov Romania Department of Mathematical Methods and Models National University of Science and Technology POLITEHNICA Bucharest & CiTi Bucharest Romania

Cybersecurity is a field that unifies concepts from various fundamental areas: mathematics, physics, computer science, electronics, sociology, and management. This field is challenging for government authorities, academic institutions, and private entities alike. By pooling the resources of these three actors, we can build secure and resilient systems. In this context, several challenges emerge, such as the exchange of knowledge and expertise, collaborative research projects, the organization of internships and scholarship programs, the exchange of threat intelligence, training, and awareness, and finally, the standardization and regulatory component. The evolving nature of cyber threats and the growing sophistication of attackers necessitate robust and adaptable security frameworks. A "defense-in-depth security model" is mandatory in this context as it offers multiple layers of protection, ensuring that if one defense mechanism fails, others remain in place to prevent breaches. In this paper, we propose a defense-in-depth security model and highlight how key points within the model can be interconnected. © 2024, Politechnica University of Bucharest. All rights reserved.

关键词： Critical infrastructures

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An Effective Cyber Security Threat Detection in Smart Cities Using Dueling Deep Q Networks 4

An Effective Cyber Security Threat Detection in Smart Cities...

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4th IEEE International Conference on Mobile Networks and Wireless Communications, ICMNWC 2024

作者： Stanly Jayaprakash, J. Kodati, Sarangam Kanchana, A. Al-Farouni, Mohammed Ramachandra, A.C. Mahendra Institute of Technology Department of Computer Science and Engineering Namakkal India Cvr College of Engineering Department of Information Technology Hyderabad India Mahendra Engineering College for Women Department of Computer Science and Engineering Namakkal India College of Technical Engineering The Islamic University Department of Computers Techniques Engineering Najaf Iraq Nitte Meenakshi Institute of Technology Department of Electronics and Communication Engineering Bengaluru India

ISBN: (纸本)9798350352931

In recent days, smart city technologies are developing rapidly with the incorporation of IoT devices and AI-driven systems has modernized and thus facilitated for enhancing productivity, sustainability, and connectivity. The motive is to mitigate the rising cyber threats which are affecting the interrelated organizations of smart cities. Despite advancements in threat detection technologies, challenges persist, including real-time anomaly detection in vast data streams, managing resource constraints on IoT devices, and ensuring adaptability against evolving attack vectors. Therefore, this research suggests a novel approach by using Dueling Deep Q Networks (DDQN) method. Initially, the data is collected from the dataset and then Inter Quartile Range (IQR) is imposed at the preprocessing stage for detection of outliers. Then, extraction of optimal features is done by using Term Frequency-Inverse Document Frequency (TF-IDF) and Recursive Feature Elimination (RFE) which transforms the data into statistical vectors and eliminates the least significance feature respectively. Finally, the obtained optimal features are detected using DDQN method as it has the ability to detect effectively with respect to the state of action. The proposed DDQN has resulted with accuracy of 99.32% when compared with Improved Bacterial Foraging Optimization using optimum deep learning for Anomaly detection (IBFO-ODLAD). © 2024 IEEE.

关键词： Cyber attacks

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From Attacks to Insights: XAI and Defense in Network Security 5

From Attacks to Insights: XAI and Defense in Network Securit...

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5th International Conference on Sustainable Communication Networks and Application, ICSCNA 2024

作者： Kumar, Bharathi Ganesh Shanthini, E. PSG College of Technology Department of Computer Science and Engineering Tamil Nadu India Sri Ramakrishna Engineering College Department of Electronics and Communication Engineering Tamil Nadu Coimbatore India

ISBN: (纸本)9798331530013

Network intrusion poses significant threats to cyber security, as malicious attacks can disrupt systems and compromise sensitive information. Real-world scenarios include unauthorized access to corporate networks, data breaches exposing sensitive customer information, and Distributed Denial of Service (DDoS) attacks that can impair critical infrastructure. This paper addresses these challenges using the UNSW-NB15 dataset, a comprehensive collection of real-world network traffic data. This dataset was chosen for its diversity in capturing contemporary cyber threats, making it ideal for evaluating model performance in detecting intrusions. While numerous classification models exist for this task, the Multi-Layer Perceptron (MLP) classifier is selected due to its ability to capture complex patterns and provide higher accuracy in non-linear datasets. To enhance the interpretability of the model, Explainable AI (XAI) techniques are employed, including SHAP, LIME, and permutation feature importance, which offer insights into model decisions by explaining feature contributions. However, adversarial machine learning introduces an additional layer of threat by exploiting model vulnerabilities. This paper focuses on the Zeroth Order Optimization (ZOO) attack, a black-box method that only requires access to the model's predictions, without needing knowledge of the architecture or gradients, to demonstrate how adversarial examples can drastically reduce model accuracy and compromise network security. Upon generating adversarial examples, a significant drop in accuracy is observed, identifying the features most susceptible to manipulation. Then XAI methods are applied again to analyze the features that contribute most to the misclassification, allowing us to understand the underlying vulnerabilities. Based on these insights, adversarial training is implemented as a defense mechanism, successfully restoring model accuracy and strengthening resilience against attacks. The results

关键词： Network intrusion

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Modified Artificial Hummingbird Algorithm with Deep Learning for Pest Detection through Leveraging Pattern Recognition-based Fusion Approach 7

Modified Artificial Hummingbird Algorithm with Deep Learning...

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7th International Conference on Circuit Power and Computing Technologies, ICCPCT 2024

作者： Rubadevi, B. Suresh, Helina Rajini Abdullah, Ibrahim Choudhary, Prashant Kumar Choudhary, Minu Mathurkar, Piyush Arunai Engineering College Department of Computer Science and Engineering Tamilnadu Tiruvannamalai India Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Department of Electronics and Communication Engineering Chennai India Al-Turath University Computer Science Department Baghdad Iraq Lovely Professional University Department of Electronics and Communication Engineering Phagwara India Lovely Professional University Department of Computer Science and Engineering Phagwara India Vishwakarma Institute of Information Technology Department of Electronics and Telecommunication Engineering Pune India

ISBN: (纸本)9798350372816

The limitations of manual inspection and simple algorithms highlight the need for advanced insect detection systems in agriculture. The study presents the Modified Artificial Hummingbird Algorithm with Deep Learning (MAHADL), a significant breakthrough in pest detection. MAHADL combines the speed and efficacy of the Artificial Hummingbird Algorithm (AHA) with deep learning models such as Recurrent and Convolutional Neural Networks. Combining pattern recognition with the fusion approach improves pest detection accuracy while reducing false positives and negatives. Accurate pest identification is essential for effective agricultural management, which MAHADL provides through data collection, preprocessing, and algorithmic integration. MAHADL outperforms existing systems in terms of accuracy (0.94), recall (0.95), precision (0.92), computational economy (12 hours of training time, 0.5 seconds/image inference time), and decrease in false positives and negatives. The innovative technique provides enhanced agricultural output and sustainability, representing a significant leap in intelligent pest management. © 2024 IEEE.

关键词： Convolutional neural networks

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IoT Based Smart Framework Monitoring System for Power Station

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computers, Materials & Continua 2023年第3期74卷 6019-6037页

作者： Arodh Lal Karn Panneer Selvam Manickam R.Saravanan Roobaea Alroobaea Jasem Almotiri Sudhakar Sengan Department of Financial and Actuarial Mathematics School of ScienceXi’an Jiaotong-Liverpool UniversityChina Department of Electrical and Electronics Engineering Sona College of TechnologySalem636005Tamil NaduIndia Department of Computer Science and Engineering Vel Tech Multi Tech Dr RR Dr SR Engineering CollegeChennai600062Tamil NaduIndia Department of Computer Science College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Department of Computer Science and Engineering PSN College of Engineering and TechnologyTirunelveli627152Tamil NaduIndia

Power Station(PS)monitoring systems are becoming critical,ensuring electrical safety through early warning,and in the event of a PS fault,the power supply is quickly *** technologies are based on relays and don’t have a way to capture and store user data when there is a *** proposed framework is designed with the goal of providing smart environments for protecting electrical types of *** paper proposes an Internet of Things(IoT)-based Smart Framework(SF)for monitoring the Power Devices(PD)which are being used in power substations.A Real-Time Monitoring(RTM)system is proposed,and it uses a state-of-the-art smart IoT-based System on Chip(SoC)sensors,a Hybrid Prediction Model(HPM),and it is being used in Big Data Processing(BDP).The Cloud Server(CS)processes the data and does the data analytics by comparing it with the historical data already stored in the ***-Structural Query Language Mongo Data Base(MDB)is used to store Sensor Data(SD)from the *** proposed HPM combines the Density-Based Spatial Clustering of Applications with Noise(DBSCAN)-algorithm for Outlier Detection(OD)and the Random Forest(RF)classification algorithm for removing the outlier SD and providing Fault Detection(FD)when the PD isn’t *** suggested work is assessed and tested under various fault circumstances that happened in *** simulation outcome proves that the proposed model is effective in monitoring the smooth functioning of the ***,the suggested HPM has a higher Fault Prediction(FP)*** means that faults can be found earlier,early warning signals can be sent,and the power supply can be turned off quickly to ensure electrical safety.A powerful RTM and event warning system can also be built into the system before faults happen.

关键词： System-on-chip cloud server apache kafka apache strom NoSQL MongoDB

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Impact of Air Mass on PV modules Power Generation in Eastern Indian Climatic Zone

Renewable Energy and Power Quality Journal

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Renewable Energy and Power Quality Journal 2022年 20卷 805-810页

作者： Majumdar, Debashis Pal, Sudipta Basu Ganguly, Rajiv Department of Electronics Engineering University of Engineering & Management Kolkata700156 India Department of Computer Science & Technology University of Engineering & Management Kolkata700156 India

The PV technology has matured to the gigawatt (GW) level of power generation. Thus, many PV modules are connected in a series-parallel configuration to configure a GW level PV array. Now the vital question of the reliability of such a PV system depends mainly on the performance of the constituent modules (setting aside the reliability consideration arising from the BOS component). Therefore, different climatic parameters directly impact the power output of PV modules. In this research paper, the authors have tried to find out the impacts of climatological parameters like air mass (AM) on the power output as well as the overall performances of different technology PV modules. Mainly crystalline (mono-Si), amorphous silicon (a-Si), and poly-Si photovoltaic (PV) modules are examined thoroughly for different times of three seasons during the year in the eastern Indian climatic zone. Now, for determining the reliability of any PV array or module, mainly the important parameters considered are regression analysis, Fill Factor variation with changing solar irradiation and temperature. After that, the performance ratio and Fill Factor parameters will be evaluated thoroughly under different climatic conditions. Finally, after the exhaustive evaluations of other reliable PV parameters like FF and PR under naturally outdoor conditions, it is established that the poly-Si module shows the best performance in the Eastern Indian climatic zone with varying AM. © 2022, European Association for the Development of Renewable Energy, Environment and Power Quality (EA4EPQ). All rights reserved.

关键词： Regression analysis

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Personal Safety and Health Monitoring System for Emergency Assistance using IOT 3

Personal Safety and Health Monitoring System for Emergency A...

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3rd International Conference on Artificial Intelligence For Internet of Things, AIIoT 2024

作者： Poovanna, K.B. Rai, Arjun Roy, Sritama Vellore Institute of Technology Department of Computer Science Chennai600127 India Vellore Institute of Technology School of Electronics Engineering Chennai600127 India

ISBN: (纸本)9798350372120

Internet of Things (IoT) has the potential to transform how we live and work. One of the most promising applications of IoT is in the area of emergency response. In this research work, we have presented a smart medical application through IoT environment that combines a pulse rate sensor, a geographic sensor, and an SMS sender using SIM800L and Arduino microcontroller. The work has designed to help people in distress by sending their location and pulse rate to the police or a concerned person. The work has the potential to be used to help people in a variety of situations, such as when they are lost, injured, or being attacked. It is significant because it demonstrates the potential of IoT to be used to improve emergency responses. It also highlights the importance of using open source hardware and software in IoT domain. © 2024 IEEE.

关键词： Internet of things

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Effect of Substrate Selection on the Design of Inset-Fed Patch Microstrip Antennas for Wireless Communication

Effect of Substrate Selection on the Design of Inset-Fed Pat...

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2024 Asia Pacific Conference on Innovation in technology, APCIT 2024

作者： Muthuswamy, Jayanthi Parvathy, A. Reddy, Chanda V Sree, B. Hima Reddy, B. Dheeraj Chowdary, G. Krithi New Horizon College of Engineering Department of Electronics and Communication Engineering Bengaluru India SASTRA University School of Electrical and Electronics Engineering Thanjavur India K. S Institute of Technology Department of Computer and Communication Engineering Bengaluru India

ISBN: (纸本)9798350361537

In the field of wireless communications, the design and optimization of microstrip patch antennas play a crucial role in achieving efficient and reliable wireless connectivity. This paper is used to explore the performance characteristics of an inset-fed patch microstrip antenna employing various substrates. In this work, we investigate the impact of substrate selection on the antenna's performance in order to advance ourunderstanding and contribute to the development of more effective wireless communication systems. The effectiveness of inset-fed patch microstrip antennas using various substratematerials is examined in this proposed work. In order to fabricate antennas, a variety of substrates, including as FR-4, high-frequency dielectrics, are used. Gain, radiation patterns, and impedance matching are the main considerations. Engineers can choose the best materials and insights into how substrate features affect antenna characteristics. This proposedwork provides valuable suggestion for antenna design and optimization by investigating radiation patterns, gain, and return loss for each substrate using computer Simulation technology (CST) Microwave studio. © 2024 IEEE.

关键词： Slot antennas

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Secure Communication Protocols for IoT-Enabled Smart Grids

Secure Communication Protocols for IoT-Enabled Smart Grids

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2024 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems, ICSES 2024

作者： Soni, Vandana Naveen Kumar, C. Jain, Virendra Santhoshkumar, G. Praveen Yuvasri, B. Rajendiran, M. Shah & Anchor Kutchhi Engineering College Department of Computer Engineering Maharashtra Mumbai400088 India Global Academy of Technology Department of Computer Science and Engineering Karnataka Bengaluru560098 India Mandsaur University Department Electrical & Electronics Engineering Madhya Pradesh 458002 India Department Electronics and Communication Engineering Tamil Nadu Erode638052 India R.M.K College of Engineering and Technology Department of Computer Science and Engineering Tamil Nadu Thiruvallur601206 India Panimalar Engineering College Department of Computer Science and Engineering Tamil Nadu Chennai600123 India

ISBN: (纸本)9798331543617

The integration of the Internet of Things (IoT) into smart grids has changed energy management and distribution, and among its benefits are enhanced operational efficiency and real-time monitoring. However, there are significant security dangers associated with this growing interconnectedness, especially about the communication protocols. The goal of this project is to safeguard Internet of Things (IoT)-enabled smart grids from data breaches and cyberattacks by looking at secure communication methods. We provide a study of the available data integrity checks, authentication methods, and encryption technologies to suit the unique requirements of smart grid infrastructure. Furthermore, we assess how well different protocols mitigate common security threats including denial-of-service attacks, man-in-the-middle attacks, and unauthorized data access assaults. The study's conclusions highlight the importance of lightweight security solutions that can maintain high-performance levels and offer reliable protection at the same time. Advanced secure communication protocols can be implemented to increase the resilience of IoT-enabled devices. © 2024 IEEE.

关键词： Data integrity

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Optimising Business Processes in Project Tracking using CRM 2

Optimising Business Processes in Project Tracking using CRM

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2nd IEEE International Conference on Emerging Research in Computational Science, ICERCS 2024

作者： Ramprasath, J. Saranya, N. Arun Kumar, M. Chandru Vignesh, C. Ramprakash, P. Krishnaraj, N. Dr. Mahalingam College of Engineering and Technology Department of Information Technology Pollachi India Sri Krishna College of Technology Department of Computer Science and Engineering Coimbatore India Sri Krishna College of Technology Department of Electronics and Communication Engineering Coimbatore India Vellore Institute of Technology School of Computer Science and Engineering Vellore India Sri Krishna College of Technology Department of AI & DS Coimbatore India

ISBN: (纸本)9798331534950

Customer relationship management, called CRM, is essential for businesses looking to sustain profitable growth in today's fiercely competitive business environment. This essay examines cutting-edge methods to improve clients in the digital era and thoroughly explains CRM practices. The research examines best-serving customers through various touchpoints by integrating data analytics, AI, and personalized marketing strategies. In addition, it explores the role of organizational alignment and a customer-centric culture in developing enduring customer relationships. The study uses theoretical frameworks and practical data to highlight the main obstacles and changes associated with implementing efficient CRM procedures. As a result, synthesizing pertained research and case studies provides insights into new trends and industry best practices for building long-lasting relationships with customers. The results highlight the significance of proactive involvement, ongoing innovation, and ethicizing deliberations in fostering trust and allegiance across various consumer categories. This paper adds to the current conversation on CRM by providing practice advice that companies can use to adjust to and prosper in a constantly changing market. © 2024 IEEE.

关键词： Sales

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