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On False Data Injection Attack against Building automation Systems

On False Data Injection Attack against Building Automation S...

引用

international conference on computing, Networking and communications (ICNC)

作者： Cash, Michael Morales-Gonzalez, Christopher Wang, Shan Jin, Xipeng Parlato, Alex Zhu, Jason Sun, Qun Zhou Fu, Xinwen Univ Cent Florida Orlando FL 32816 USA Southeast Univ Nanjing Peoples R China Univ Massachusetts Lowell Lowell MA USA

ISBN: (纸本)9781665457194

KNX is one popular communication protocol for a building automation system (BAS). However, its lack of security makes it subject to a variety of attacks. We are the first to study the false data injection attack against a KNX based BAS. We design a man-in-the-middle (MITM) attack to change the data from a temperature sensor and inject false data into the BAS. We model a BAS and analyze the impact of the false data injection attack on the system in terms of energy cost. Since the MITM attack may disturb the KNX traffic, we design a machine learning (ML) based detection strategy to detect the false data injection attack using a novel feature based on the Jensen Shannon Divergence (JSD), which measures the similarity of KNX telegram inter-arrival time distributions with attack and with no attack. We perform real-world experiments and validate the presented false data injection attack and the ML based detection strategy. We also simulate a BAS, and show that the false data injection attack has a huge impact on the BAS in terms of power consumption. Our results show an increase in overall energy cost during a false data injection attack. Other the examined ML models, the Support Vector Machine (SVM) classifier achieved the best results with a 100% detection rate with our proposed similarity features compared to mean and variance related features.

关键词： automation

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Detection and Classification of Lung Cancer Using CNN Models 5

Detection and Classification of Lung Cancer Using CNN Models

引用

5th international conference on Circuits, control, communication and computing, I4C 2024

作者： Neelameghasri, K. Mohan, Mamtha Pavitha, U.S. Ramaiah Institute of Technology Department of Electronics and Communication Engineering Bangalore India

ISBN: (数字)9798331528539

ISBN: (纸本)9798331528539

Lung cancer has the maximum number ofmorbidity and mortality globally. Early detection ofpulmonary nodules in the lungs can significantly decrease the incidence of lung cancer. But, detecting small nodules in medical images is extremely difficult due to the vast variation in their shape, size, and location. Additionally, distinguishing between lung cancer and other lung diseases such as pneumonia, tuberculosis, and COVID-19, which typically affect the same regions of the lungs, can lead to diagnostic ambiguity. This complexity makes it difficult to determine the precise treatment. To address this issue, we can develop an automated model to classify CT images according to the type of disease. This approach will facilitate more accurate diagnoses and improve treatment outcomes. © 2024 IEEE.

关键词： Lung cancer

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A Comprehensive Survey on Unmanned Aerial Vehicles (UAVs): Types, Structural Components, communication Systems, and Operating Platforms 3

A Comprehensive Survey on Unmanned Aerial Vehicles (UAVs): T...

引用

3rd international conference on Intelligent and Innovative Technologies in computing, Electrical and Electronics, IITCEE 2025

作者： Tauseef, Md. Reddy, T. Sai Sankalp Lohith, R. Thanushree, M.P. Sravani, K. Reva University School of Ece Bengaluru India

ISBN: (纸本)9798331515911

Unmanned Aerial Vehicles (UAVs), commonly known as drones, have experienced rapid growth and widespread adoption across military and civilian applications in recent years. This paper offers a comprehensive survey of UAV technologies, focusing on their classifications, structural components, communication systems, and operating platforms. UAVs are categorized based on size, range, and altitude capabilities. Key structural elements such as frames, propulsion systems, sensors, and control mechanisms are examined. The paper also addresses communication requirements, architectures, protocols, and associated challenges. Furthermore, it reviews real time operating systems utilized in UAVs, high-lighting their design considerations. The survey concludes by identifying emerging trends and future research directions in UAV development, providing valuable insights for both newcomers and seasoned researchers in the field. © 2025 IEEE.

关键词： Drones

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Performance Analysis of Vehicular Networks with Prioritized Traffic 15

Performance Analysis of Vehicular Networks with Prioritized ...

引用

15th international conference on computing communication and Networking Technologies, ICCCNT 2024

作者： Shenoy, Jaigovind B. Kiran, P.S. Jacob, Jeevan John Bhavana, V. Amrita School of Engineering Amrita Vishwa Vidyapeetham Department of Electronics and Communication Engineering Bengaluru India

ISBN: (纸本)9798350370249

The study leverages Vehicular Ad-Hoc Networks (VANETs) based on IEEE 802.11p for communication to improve the safety of road transport through vehicle navigation, particularly in emergency situations and high traffic loads. Immediate delivery of the safety message is difficult where a vehicle must encounter an emergency and there are significant traffic volumes. To meet this challenge, a priority call admission monitoring policy is suggested that ensures the timely transmission of vital safety messages. The research aims at developing a model for the management of message priorities, as well as implementing two Call's admission control policy. To provide a general basis for analysis of performance, an analytical Markov Chain model has been developed. Furthermore, practical performance results obtained through simulation are compared with the theoretical model to evaluate the efficacy of the proposed approach in enhancing vehicular network performance and safety. © 2024 IEEE.

关键词： Call admission control policy Message priorities Priority call admission monitoring policy Safety messages Timely transmission Vehicular Ad-Hoc networks (VANETs) Vehicular network performance

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Autonomous Ground Vehicle Trajectory Tracking using Adaptive Model Predictive control 15

Autonomous Ground Vehicle Trajectory Tracking using Adaptive...

引用

15th international conference on computing communication and Networking Technologies, ICCCNT 2024

作者： Athira Krishnan, S.R. Hari Kumar, R. Lal Priya, P.S. Apj Abdul Kalam Technological University College of Engineering Trivandrum Kerala India

ISBN: (纸本)9798350370249

Trajectory tracking is crucial for an autonomous vehicle's ability to navigate complex paths, ensuring both overall functionality and maneuverability. This paper proposes an adaptive Model Predictive control (MPC) for autonomous ground vehicles. The performance of the proposed controller is evaluated across various trajectories and the results are compared with traditional MPC. The findings demonstrate that adaptive MPC significantly reduces tracking errors, thereby improving the vehicle's trajectory tracking precision. Furthermore, a lane change maneuvering scenario is also analyzed utilizing the dynamic bicycle model. The simulation and validation of the proposed approach are conducted using MATLAB, showcasing the effectiveness and robustness of the adaptive MPC in diverse driving scenarios. © 2024 IEEE.

关键词： adaptive MPC Autonomous ground vehicle lane change trajectory tracking

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Exploring Machine Learning's Impact on Digital Marketing 15

Exploring Machine Learning's Impact on Digital Marketing

引用

15th international conference on computing communication and Networking Technologies, ICCCNT 2024

作者： Kumari, Mamta Sinha, Raj Chakrabarty, Prasenjit Hasnain, Md Gauhar Qamar, Neshat Gupta, Sandeep L.N.Mishra Institute of Economic Development and Social Change Department of Management Bihar Patna India Lovely Professional University School of Computer Applications Punjab India Techno Main Department of Management Kolkata India International School of Management Department of Management Bihar Patna India Cimage Professional College Department of Management Bihar Patna India Uttarakhand Dehradun India

ISBN: (纸本)9798350370249

This survey paper investigates the profound influence of machine learning (ML) on reshaping digital marketing strategies and practices. As ML technologies evolve rapidly, they are revolutionizing how marketers understand, engage with, and convert consumers. The paper comprehensively analyzes the key ML algorithms and their applications in the digital marketing landscape, including predictive analytics, personalized recommendation systems, sentiment analysis, and customer segmentation. It explores how ML-driven approaches empower marketers with actionable insights, enhance customer experiences, and drive business growth. Additionally, the paper discusses emerging trends, challenges, and future directions in the integration of ML with digital marketing strategies, highlighting the importance of ethical considerations, privacy protection, and ongoing innovation to harness the full potential of ML in shaping the future of marketing. © 2024 IEEE.

关键词： AI in marketing Customer segmentation Digital marketing Machine learning Marketing automation Predictive analytics

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Density-Based Traffic Signal control System 3

Density-Based Traffic Signal Control System

引用

3rd international conference on Intelligent and Innovative Technologies in computing, Electrical and Electronics, IITCEE 2025

作者： Pavan, D.S. Jain, Ronak R. Karmakar, Tirthankar Chaitra, N. Bnmit Bangalore India Pes University Bangalore India

ISBN: (纸本)9798331515911

The Density-Based Traffic Signal control System (DB-TSCS) is an innovative approach to manage traffic flow at intersections. Incorporating advanced sensor technologies and intelligent algorithms, the system adjusts the signal timings dependent on the traffic density at a particular point in time. This provides improvements in the flow of traffic while reducing the level of traffic congestion and improving the use of the transportation system in general. The central control unit uses density-based algorithms to analyze traffic conditions, generating optimized signal timings that prioritize congested directions while minimizing delays in low-density areas. The system also incorporates adaptive learning and can be integrated with smart city infrastructure for communication and real-time traffic updates. © 2025 IEEE.

关键词： Traffic congestion

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Turmeric Farm Monitoring and automation Using Deep Learning and Fuzzy Logic on Raspberry Pi: A Low-cost and Energy Efficient Solution 4

Turmeric Farm Monitoring and Automation Using Deep Learning ...

引用

4th international conference on Advances in Electrical, computing, communication and Sustainable Technologies, ICAECT 2024

作者： Mervin Paul Raj, M. Vijayakumar, J. Bharathiar University Department of Electronics and Instrumentation Tamilnadu Coimbatore India

ISBN: (纸本)9798350343670

Turmeric is valuable in various food, cosmetics, and medicine products. On the other hand, turmeric plants are susceptible to multiple diseases and pests, which can reduce crop yields. The proposed system combines deep learning, fuzzy logic, and Raspberry Pi to improve the efficiency and accuracy of turmeric farm management. The first component of our approach is a deep learning model that categorizes turmeric leaf images as healthy, diseased, or drought-stressed. The model is trained on a large dataset of turmeric leaf images and deployed for real-time classification on a Raspberry Pi. A fuzzy system for controlling grow lights, pesticide spray, air circulation fans, and water pumps is the second component of our system. The fuzzy system receives the deep learning model output as input and generates control signals for the actuators. The fuzzy system is intended to optimize the growth conditions for turmeric plants while reducing pesticide and water use. The system also considers environmental factors such as temperature, humidity, light intensity, and soil moisture. Our approach is built on Raspberry Pi, a low-cost, energy-efficient computing platform. As a result, our system is suitable for deployment in remote areas with limited access to electricity and other resources. The proposed system has achieved a classification accuracy of 95.47%. Simulink is used to build a standalone application for Raspberry Pi using the proposed deep learning model and Fuzzy system. Our system can increase the efficiency of turmeric farm management while lowering production costs. This can assist farmers in increasing their profits and improving their living conditions. © 2024 IEEE.

关键词： Deep learning Environmental Monitoring Fuzzy logic Image classification Turmeric farm management

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Towards Hybrid computing with Scalable Mass Parallelism for High-Performance Cloud computing of Digital Twins 8

Towards Hybrid Computing with Scalable Mass Parallelism for ...

引用

8th international conference on Information, control, and communication Technologies, ICCT 2024

作者： Zatuliveter, Yury Fishchenko, Elena V.A. Trapeznikov Institute of Control Sciences of the RAS Moscow Russia

ISBN: (纸本)9798331517564

In order to improve the computing performance of the cloud implementations of digital twin models, the possibilities of hybridization of cloud servers using single-chip accelerating general-purpose computers with mass multi-core parallelism are investigated. Such accelerating computers belong to the class of Multi-Processor Systems-on-a-Chip (MPSoC). The variants for system-engineering integration of mass multi-core parallelism of accelerating computer of class MPSoC into a virtual environment of cloud computing resources are considered. On the example of the requirements for the creation of digital twins of nuclear power plants (NPPs), the possibilities of using hybrid computing systems based on the proposed single-chip accelerator with mass multi-core parallelism of the MPSoC class are considered. The proposed multi-SIMD architecture of such accelerators is based on the scalable multiprocessor architecture of accelerating computers PS-2000 for the eponymous hybrid computing complexes, which were produced in a large industrial series in the absence of world analogues. The high efficiency of architecture PS-2000 had been confirmed by the wide practice of application in various fields. At the conceptual level, it is shown that the use of the proposed single-chip accelerating computers with in-chip integration of mass multicore parallelism into the virtual environment of cloud servers opens up opportunities for cloud systems to expand the scaling ranges of computing performance of cloud servers by orders of magnitude. It is necessary when building digital twins of technogenic systems with increased security and computing performance requirements, for example, for NPP. © 2024 IEEE.

关键词： Nuclear power plants

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Helmet Guard: Engine Management and Accident Severity Assessment for Motorcycles 15

Helmet Guard: Engine Management and Accident Severity Assess...

引用

15th international conference on computing communication and Networking Technologies, ICCCNT 2024

作者： Vanga, Siva Reddy Angadala, Niharika Alajangi, Purna Gowtham Velagapudi Ramakrishna Siddhartha Engineering College Electronics and Communication Engineering Vijayawada India

ISBN: (纸本)9798350370249

Motorcycle safety systems traditionally face limitations in engine control, accident assessment, and rider protection. This paper introduces a solution that enhances engine management employs machine learning for accurate accident severity analysis, and incorporates alcohol detection with accelerometer-based tilt assessment designed for motorcycles. This project mandates helmet usage before the engine starts, ensuring the rider's safety. The system concurrently monitors critical factors such as alcohol concentration and tilt angles and deactivates the engine upon detecting irregularities. This innovative approach helps make riding motorcycles safer and smarter by overcoming previous problems. It represents a significant advancement, promising enhanced security and intelligence on the road. © 2024 IEEE.

关键词： Motorcycles

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