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1st EAI International Conference on Security and Privacy in Cyber-Physical Systems and Smart Vehicles, SmartSP 2023

作者： Liang, Sisheng Li, Zhengxiong Jiang, Chenxu Guo, Linke Zhang, Zhenkai School of Computing Clemson University Clemson United Kingdom Department of Computer Science and Engineering University of Colorado Denver Denver United States Holcombe Department of Electrical and Computer Engineering Clemson University Clemson United Kingdom

ISBN: (纸本)9783031516290

Application fingerprinting is a technique broadly utilized in diverse fields such as cybersecurity, network management, and software development. We discover that the mechanical vibrations of cooling fans for both the CPU and power supply unit (PSU) in a system strongly correlate with the computational activities of running applications. In this study, we measure such vibrations with the help of mmWave sensing and design a new application fingerprinting approach named mmFingerprint. We create a prototype of mmFingerprint and demonstrate its effectiveness in distinguishing between various applications. To showcase the use of mmFingerprint in cybersecurity for defensive purposes, we deploy it in a real computer system to detect the execution of reputable Rowhammer attack tools like TRRespass and Blacksmith. We find that the detection can reach a very high accuracy in practical scenarios. Specifically, the accuracy is 89% when exploiting CPU fan vibrations and nearly 100% when leveraging PSU fan vibrations. © ICST Institute for computer Sciences, Social Informatics and Telecommunications engineering 2024.

关键词： Software design

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Identification with CNNs by Fusing Face, Fingerprint, and Voice Recognition 14

Identification with CNNs by Fusing Face, Fingerprint, and Vo...

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14th IEEE Annual Ubiquitous computing, Electronics and Mobile Communication Conference, UEMCON 2023

作者： Ehgartner, Samuel B. Jouny, Ismail Lafayette College Department of Electrical and Computer Engineering EastonPA United States

ISBN: (纸本)9798350304138

In this paper, classifications using three convolutional neural networks (CNN) are fused together to explore the performance of an identification system. In this system facial, voice, and fingerprint recognition are used to demonstrate fusion. These three sets of data vary in complexity and represent a range of image quality and perspectives. A convolutional neural network's success is entirely dependent upon its ability to accurately classify images. By fusing CNNs, the algorithm has more data to add in the decision-making process, thereby increasing classification accuracy. In order to demonstrate fusion's potential advantages, a mock security system is designed to evaluate reliability. Three methods of fusion are compared to determine the most effective way to boost performance of the designed fusion architecture. Each method is evaluated on 50 unique profiles containing face, fingerprint and voice data. To further determine fusion's effectiveness, noise was added to an identical dataset and evaluated using the same methods. © 2023 IEEE.

关键词： Convolutional neural networks

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Voting Classifier and Metaheuristic Optimization for Network Intrusion Detection

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computers, Materials & Continua 2023年第2期74卷 3183-3198页

作者： Doaa Sami Khafaga Faten Khalid Karim Abdelaziz A.Abdelhamid El-Sayed M.El-kenawy Hend K.Alkahtani Nima Khodadadi Mohammed Hadwan Abdelhameed Ibrahim Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt The Department of Civil and Environmental Engineering Florida International UniversityMiamiFLUSA Department of Information Technology College of ComputerQassim UniversityBuraydah51452Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt

Managing physical objects in the network’s periphery is made possible by the Internet of Things(IoT),revolutionizing human *** attacks and unauthorized access are possible with these IoT devices,which exchange data to enable remote *** attacks are often detected using intrusion detection methodologies,although these systems’effectiveness and accuracy are *** paper proposes a new voting classifier composed of an ensemble of machine learning models trained and optimized using metaheuristic *** employed metaheuristic optimizer is a new version of the whale optimization algorithm(WOA),which is guided by the dipper throated optimizer(DTO)to improve the exploration process of the traditionalWOA *** proposed voting classifier categorizes the network intrusions robustly and *** assess the proposed approach,a dataset created from IoT devices is employed to record the efficiency of the proposed algorithm for binary attack *** dataset records are balanced using the locality-sensitive hashing(LSH)and Synthetic Minority Oversampling Technique(SMOTE).The evaluation of the achieved results is performed in terms of statistical analysis and visual plots to prove the proposed approach’s effectiveness,stability,and *** achieved results confirmed the superiority of the proposed algorithm for the task of network intrusion detection.

关键词： Voting classifier whale optimization algorithm dipper throated optimization intrusion detection internet-of-things

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Intelligent Backoff Management Scheme Applying Adaptive Neuro-Fuzzy Inference System in Vehicular Ad-hoc Networks

Intelligent Backoff Management Scheme Applying Adaptive Neur...

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2023 IEEE Symposium Series on Computational Intelligence, SSCI 2023

作者： Limouchi, Elnaz Chan, Francois Royal Military College of Canada Department of Electrical and Computer Engineering KingstonON Canada

ISBN: (纸本)9781665430654

Intelligent Transportation Systems rely heavily on the Vehicular Ad-hoc Network to enhance road safety and comfort. This research proposes and evaluates an intelligent backoff management scheme, utilizing Adaptive Neuro-Fuzzy Inference System (ANFIS), for the Vehicular Ad-hoc Networks. The proposed scheme is trained by TensorFlow to adjust the contention window size at the MAC layer of IEEE 802.11p. Taking into account the local density, local spatial distribution, and successful/unsuccessful transmission records, each transmit-ting node can determine the best contention window value for transmitting packets. This scheme effectively mitigates packet collisions, ensuring a high packet delivery ratio and average throughput, along with a low average end-to-end delay for various network scenarios. Simulation results confirm the efficiency of the proposed scheme and also show that it outperforms the conventional IEEE 802.11p method and other recent protocols. © 2023 IEEE.

关键词： ANFIS backoff management contention window IEEE 802.11p TensorFlow Vehicular Ad-hoc Networks

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Template Matching Based Cash Register for Disabled Workers

Template Matching Based Cash Register for Disabled Workers

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2023 IEEE International Conference on Dependable, Autonomic and Secure computing, 2023 International Conference on Pervasive Intelligence and computing, 2023 International Conference on Cloud and Big Data computing, 2023 International Conference on Cyber Science and Technology Congress, DASC/PiCom/CBDCom/CyberSciTech 2023

作者： Sarpong, Michael Simoni, Cristian Samaroo, Brandon Rodriguez, Camilo Samaniego, Daniel Elmannai, Wafa Wang, Yi Manhattan College Electrical and Computer Engineering Department Riverdale10471 United States

ISBN: (纸本)9798350304602

There are numerous consumer-oriented and retail spaces that use cash registers and POS systems, such as restaurants, grocery stores, department stores, etc. The typical cashier working in a retail environment will find these systems to be incredibly efficient and simple to use. There are also some limitations associated with these systems in terms of who is able to comfortably operate them. It will be necessary to provide a register/smart POS system to alleviate the difficulty in counting currency among disabled workers as the number of such workers increases. The contribution we make is the proposal of a novel chase register system based on a template matching technique. The system will include client applications and designed integrated circuits. Using image classification, this system recognizes currency and relays that information to a user through an easy-to-use graphical user interface (GUI). In addition, the software will be able to calculate the currency and count for the workers, enabling them to work efficiently and without having to worry about money issues. © 2023 IEEE.

关键词： Cash registers

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Modified Model Predictive Control for Power Balancing in Multilevel Inverter for Battery Energy Storage Applications 32

Modified Model Predictive Control for Power Balancing in Mul...

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32nd IEEE International Symposium on Industrial Electronics, ISIE 2023

作者： Grote, Henry Zhu, Yuehao Sajadian, Sally Lafayette College Department of Electrical & Computer Engineering EastonPA United States

ISBN: (纸本)9798350399714

Battery energy storage systems (BESS) will play a critical role in the modern power system (MPS) with high penetration of renewable energy resources. In MPS energy paradigm, it is required to deploy and integrate BESS at different voltage level from low voltage distribution system to medium voltage levels. This requires high number of battery cells in series to reach to desired voltage level for grid integration which is challenging from BESS technology point of view and unequal state of health of batteries over time. On the other hand, cascaded multilevel inverters (CMI) provides a unique opportunity for minimizing the direct series connection of battery cells for medium voltage grid integration of BESS. However, conventional CMI's linear and non-linear control schemes suffers from unequal power drawn from battery cells at each h-bridge. This paper proposes a modified predictive control scheme that leverages the inherent characteristics of finite-set model predictive control (MPC) and balance power drawn from the battery cells. Conventional MPC is based on a cost function optimization that select the first optimal switching state, this approach will result in unequal power drawn form battery cells. The proposed approach includes a constraint optimization that mitigates the unequal power drawn from battery cells. The theoretical analysis are validated via several case studies, the results demonstrate promising performance of proposed modified MPC for CMI interfaced BESS. © 2023 IEEE.

关键词： Model predictive control

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A Smart Cane with Fall Detection System for People with Visual Impairments

A Smart Cane with Fall Detection System for People with Visu...

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作者： Appiah, Obed Elmannai, Wafa Manhattan College Electrical and Computer Engineering Department New York United States

ISBN: (纸本)9798350304602

According to the World Health Organization, at least 2.2 billion people suffer from near or distance vision impairment, and this number is expected to increase as the population ages. The prevalence of vision impairment in low- and middle-income regions is four times greater than in high-income regions, which poses a significant challenge for visually impaired individuals in terms of accessibility, mobility, and independence. It is imperative that assistive technology be affordable. Among visually impaired individuals, aging is associated with a decrease in independence and an increased risk of falling. A study conducted by *** estimated that approximately 30% of adults over 65 fall each year, and this risk is more than double for those who are visually impaired. These individuals are also limited in their activities by a fear of falling. We propose a smart white cane that includes an emergency fall alert system to alert appropriate personnel and the family of a visually impaired individual who has fallen. Users receive haptic feedback when approaching obstacles using ultra-sensors. A smart cane detects a fall and sends a text message to the appropriate persons in the event of a fall with more than 95% accuracy. Our contribution includes a detection algorithm, a falling alert system, and a wireless communication approach. © 2023 IEEE.

关键词： Fall detection

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60 GHz Printed Yagi-Uda Beam-Deflector Integrated Refractive Index Metamaterial 3

60 GHz Printed Yagi-Uda Beam-Deflector Integrated Refractive...

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3rd IEEE International Maghreb Meeting of the Conference on Sciences and Techniques of Automatic Control and computer engineering, MI-STA 2023

作者： Beltayib, Abduladeem Omran, Allafi The College of Technical Sciences Electrical and Computer Engineering Department Bani Walid Libya

ISBN: (纸本)9798350319897

An approach for deflection of the main radiation of the end-fire dipole antenna in a specific direction by changing the effective constitutive parameters of metamaterials are introduced. The concept of this phenomenon is creating a new medium that has different characteristics, in front of the electromagnetic waves to enforce it to propagate in a specific direction. This act has been done by embedding Modified Gradient Refractive Index Metamaterial (MGRIM) unit-cells (UCs) in front of the dipole-printed antenna. However, by changing the load dimensions of MGRIM, the permittivity and permeability of unit cells are going to change. Because the refractive index (n) of the medium changed, the phase of entered EM waves to this medium will be changed. So, the aim here is to create a new medium with different properties to provide a proper phase shift to tilt the end-fire radiation pattern. The challenge in this approach is are provide a high tilting beam angle, high gain, and low side lobe level simultaneously. Two unit cells are used in this paper to provide a high deflection angle and keep a high gain with a low side lobe level. First one to get medium has a gradient refractive index. The second one uses as a band stop structure in order to minimize the side lobe level (SLL) and enhance the gain. The simulation results show that by using the nonperiodicity arrangement of MGRIM UCs in front of a dipole-printed antenna, the main beam of the radiation pattern in the E-plane can be tilted 43oin the end-fire direction at 60 GHz. The proposed design exhibits an increasing gain of about 2.7dB and reduces the side lobe level to -11.2dB. © 2023 IEEE.

关键词： Metamaterials

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Monitoring of Individual Household electrical Appliances and Prediction of Energy Consumption Using Machine Learning 5

Monitoring of Individual Household Electrical Appliances and...

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5th International Conference on Intelligent Communication Technologies and Virtual Mobile Networks, ICICV 2024

作者： Selvam, N. Seenivasan, D. Naveen, G. Sudahar, R. Janagan, P. Dhanushmathi, S. M.Kumarasamy College of Engineering Department of Electrical and Electronics Engineering Karur India M.Kumarasamy College of Engineering Department of Computer Science and Business Systems Karur India

ISBN: (纸本)9798350385649

The study suggests a scalable method for estimating residential power usage. To increase the forecasting accuracy, an SVM (support vector machine) based technique combines many machine learning models, such as random forests, decision trees, and linear regression. Real-world data from Dutch families were used in the study, and the findings demonstrate that the suggested strategy performs better than conventional single-model techniques and attains higher accuracy in predicting energy use. The method is suited for usage in real-world applications since it is scalable and applies to huge datasets. An approach for machine learning used in load forecasting is called SVM (Support Vector Machine). Applications for long-term individual household forecasting include calculating advance payments to customers. However, there is a dearth of research on this type of forecasting;most techniques either concentrate on long-term predictions at the aggregate level or on individual family-level short-term projections. In order to close this distance, we provide a technique that uses only a few months' worth of current year's consumption data to anticipate each monthly consumption throughout the next year. Even with little data, utility suppliers may use this technique to predict any customer's consumption for the upcoming year. Data power use in the future may be predicted using linear regression. The linear regression process is used to forecast data in the future. © 2024 IEEE.

关键词： Forecasting

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DOA Using Blind Compressive Sensing in the Presence of Mutual Coupling

DOA Using Blind Compressive Sensing in the Presence of Mutua...

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2023 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, AP-S/URSI 2023

作者： Jouny, Ismail Lafayette College Department of Electrical and Computer Engineering EastonPA United States

ISBN: (纸本)9781665442282

Compressive sensing reconstruction techniques have been used to estimate the arrivals of correlated or uncorrelated signals impinging on a uniformly or nonuniformly space linear or circular arrays. DOA is accomplished without the need for spatial smoothing or interpolation if the array geometry is known a priori. The presence of mutual coupling renders such an approach ineffective. This paper proposes using blind compressive sensing with deterministic measuring matrix to perform DOA even with incomplete information about array geometry and with mutual coupling. The approach used here requires large number of antennas but does lead to reliable DOA estimates unlike MUSIC or other high-resolution methods. © 2023 IEEE.

关键词： Compressed sensing

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