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intelligent systems for Cybersecurity (isCs), international Conference on

作者： AsHUtOsH YADAV ANUsHKA MisHRA HiMANsHU siNGH VRiNDA sACHDEVA Department of Computer Science & Engineering I.T.S Engineering College Greater Noida Uttar Pradesh India

ISBN: (数字)9798350375237

ISBN: (纸本)9798350375244

One of the biggest uses of image processing is face recognition, which is essential to the industry. the ability to recognize a human face is a current concern for authentication, particularly when it comes to student attendance. Face biostatistics, which are based on high definition monitoring and other computer technologies, are used in the face recogn ition process of the attendance system to identify students. the goal of establishing this system is to digitally replace the conventional method of recording attendance by calling names and keeping paper records. the methods used today to record attendance are laborious and time-consuming. Manually recording attendance allows for easy manipulation of the records. Both the current biometric methods and the conventional method of taking attendance are susceptible to proxies. it is consequently suggested that this article address each of these issues. the suggested system uses Gabor filters, generative algorithms such as CNN, sVM, and KNN. Attendance reports will be created and saved in Excel format following face recognition. the system is evaluated in a variety of settings, including lighting, head motions, and changes in the student-camera distance. Following rigorous testing, the total accuracy and complexity are computed. Biometric technology, such as face recognition, relies on identifying an individual's facial characteristics. individuals gather the facial picture data, which is then automatically processed by the recognition technology. the paper provides an overview of relevant facial recognition research from several angles. the report outlines the phases of development and associated facial recognition technology. We provide the general assessment standards, the general databases, and the research on face recognition in real-world situations.

关键词： Deep learning support vector machines Ethics image recognition Face recognition surveillance Lighting

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solar energy capacity assessment and performance evaluation of a standalone PV system using PVsYst

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Materials today: Proceedings 2023年 80卷 3385-3392页

作者： shrivastava, Anurag sharma, Rajneesh Kumar saxena, Mohit shanmugasundaram, V. Lal Rinawa, Moti Ankit Lakshmi Narain College of Technology and Science Indore Madhya Pradesh 453111 India Department of Civil Engineering Engineering College Jhalawar Rajasthan 326023 India Department of EEE I.T.S Engineering College Greater Noida India Department of Electrical and Electronics Engineering Sona College of Technology Tamilnadu Salem636005 India Department of Mechanical Engineering Government Engineering College Jhalawar Rajasthan 326024 India Mechanical Engineering Department Government Engineering College Jhalawar Rajasthan 326023 India

in today's time, photovoltaic systems are continuously gaining popularity and emerging due to their high sustainability, autonomy, and viability. it is necessary to assess the performance of these systems to understand various aspects related to their operation. the study analyses the usefulness of a PV system installation that supplies electricity to an academic institution. this paper aims to evaluate the performance of a grid-connected silicon-poly PV system with a peak power of 20.0 kW and voltage of 17v. the software used for analysis is PVsyst (7.1.7 version). PVsyst is a widely used simulation software for estimating the energy yield and for optimizing the system design. the PVsyst software has been used to design a grid-connected PV system for the Karunya institute of technology. the simulated system has silicon-poly PV modules assembled in it. Each module consists of numerous photovoltaic cells interconnected. Each module has a power rating of 180wP and voltage sizing of Vmpp (60-degree Celsius) 17.5v Voc (−10degree) 28.9v. the photovoltaic modules are assembled in a total of 13 strings. Modules in a string are series-connected. Each string in the system consists of 10 PV modules connected in series with a power rating of 20.8 kW. the arrangement is grid-connected with a utility meter. the weather dataset used for evaluation is extracted from PVsyst's database and has the attributes, solar radiation, and ambient temperature. © 2021

关键词： solar panels

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Email traceback: securing systems from Phishing and Malicious Link Prevention

Email Traceback: Securing Systems from Phishing and Maliciou...

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Advances in Computing, Communication and Networking (iCAC2N), international Conference on

作者： Nikunj Kaushik trilochan singh Rathore Pawan Kumar Computer Science and Engineering I.T.S Engineering College Ghaziabad India CFEES DRDO Delhi India

ISBN: (数字)9798350356816

ISBN: (纸本)9798350356823

in a generation where cyber crimes are on a constant rise and digital communication is getting more unsafe by various threats due to phishing and malicious files, email tracking has become a necessity to uncover the origins and routes of digital messages for preventing cyber crimes. this reference provides a comprehensive review of email tracking technologies, discussing the challenges involved and the significant implications associated with them. this paper begins with an overview of the email tracking processes, highlighting the key elements involved in email history monitoring. this research focuses on email headers and metadata, including a consolidated data set such as iP addresses, timestamps, and routing data that contribute to email traceability. Additionally, a study of a number of email protocols such as sMtP, iMAP, and POP3 is performed to explore their impact on tracking capabilities and reveal their unique strengths and weaknesses. to contextualize contemporary practice, this search evaluates cutting-edge forensic equipment and techniques used by law enforcement, cybersecurity professionals, and other investigative agencies. this evaluation indicates the effectiveness, limitations, and room for improvement of these methods. But the email tracking experience isn’t over the hurdle yet. this research identifies and examines the challenges encountered in tracking email, specifically the presence of sender anonymization technologies such as proxy servers, VPNs, and the tor network that prevent the accurate attribution of messages. Ethical and criminal law concerns are also paramount, as the delicate balance between investigative requirements and individual rights in the digital realm needs to be explained and respected. this reference goes beyond the technical aspects to consider the broader implications of email tracking. specifically, it explores the impact of tracking on cyber crime deterrence and its exploitation and exploitation opportunities in survei

关键词： Ethics Law enforcement Reviews Phishing surveillance Routing Electronic mail Virtual private networks servers computer crime

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Early Kidney stone Detection Among Patients Using a Deep Learning Model on an image Dataset 6th

Early Kidney Stone Detection Among Patients Using a Deep Lea...

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6th international Conference on innovative Computing and Communication, iCiCC 2023

作者： Buri, sharwan shrivastava, Vishal Computer Science & Engineering Arya College of Engineering & I.T. Jaipur302028 India

ISBN: (纸本)9789819933143

Kidney stones, also known as renal calculi, are solid masses formed by the crystallization of urine. to perform surgical procedures on the urinary calculus, it is essential to determine the specific and correct location of the calculus. Consequently, since ultrasound pictures include speckle noise, it is challenging to visually identify urinary calculi in ultrasound images, and it’s, therefore, necessary to use automated algorithms for the identification of kidney stones in computed tomography. Renal abnormalities such as changes in kidney size and location, leg swelling, and the production of stones as well as cystic variations can be diagnosed using ultrasound imaging methods. this report summarizes the results of an audit on the detection and acceptance of renal abnormalities in most populations. significant progress has been achieved in the field of artificial intelligence with the help of deep learning (DL) method, which proposes the automatic detection of kidney stones (whether they contain stones or not) using coronal computed tomography (Ct) images, which can be used to recommend an automated diagnosis of kidney stones. We discovered that our model is able to reliably detect kidney stones of any size, including stones that are very small. it has been shown in this work that the newly popular DL approaches may be used to handle additional difficult issues in urology. According to this study, we can detect even very small stones in the early stages of stone formation and it has obtained new results by improving the algorithm used based on the results of previous studies, which are discussed in the paper. the methodology used in this paper can achieve the accuracy of 100% on the kidney stone dataset. © the Author(s), under exclusive license to springer Nature singapore Pte Ltd. 2023.

关键词： computerized tomography

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Design and implementation of Artificial Neural Network Classifiers based on Hypertuning Parameters for Breast Cancer Diagnosis 5

Design and Implementation of Artificial Neural Network Class...

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5th international Conference on innovative Data Communication technologies and Application, iCiDCA 2024

作者： Gupta, Neetu Gupta, Hemant Kumar srivastava, Rahul saxena, Chhavi surjeet Department of Computer Science & Engineering Manipal University Jaipur Rajasthan Jaipur303007 India Department of Electronics & Communication Engineering Arya College of Engineering & I.T. Jaipur Rajasthan 302028 India Department of Computer Science & Engineering Arya College of Engineering & I.T. Jaipur Rajasthan 302028 India Department of Electronics & Communication Engineering Bharati Vidyapeeth's College of Engineering New Delhi110063 India

Breast cancer is an extremely prevalent disease which impacts women all over the world, and minimizing the death rate among women requires detection at an early stage. this research employs Artificial Neural Network (ANN) to predict and detect breast cancer at an early stage. the suggested model is trained and tested using the 569 patient records taken from Wisconsin Diagnostic dataset for breast cancer. the dataset is split between training and testing sets using 80:20 ratio, with the random states being 0, 1, and 2 for each set. With random state 1 benign and malignant cases are split in same ratio as were in original dataset. the binary cross-entropy function is used to calculate the discrepancy between the predicted class probability and the actual class label. in this research, an Adam optimizer is employed to reduce the loss function. Overall, the parameters of the model are tuned to produce the best outcomes for particular tasks depending on the choice of different random states, activation function, loss function, and optimizer. several measurements, including training and testing accuracy, confusion matrix, precision, sensitivity, F1_score, FPR, MCC (Matthews correlation coefficient), AUC, and ROC curve, are employed to evaluate the model performance. Our experimental findings show that the suggested model is capable of making precise predictions and diagnosis of breast cancer. © 2024 the Authors. Published by Elsevier B.V.

关键词： Neural networks

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Enhanced Route Optimization for Wireless Networks Using Meta-Heuristic engineering

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computer systems science & engineering 2022年第10期43卷 17-26页

作者： s.Navaneetha Krishnan P.sundara Vadivel D.Yuvaraj t.satyanarayana Murthy sree Jagadeesh Malla s.Nachiyappan s.shanmuga Priya Department of Electronics and Communication Engineering SACS MAVMM Engineering CollegeMaduraiIndia Department of Computer Science and Engineering SACS MAVMM Engineering CollegeMaduraiIndia Department of Computer Science Cihan University-DuhokKurdistan RegionIraq Department of Computer Science and Engineering Bapatla Engineering College BapatlaAndhra PradeshIndia Department of Computer Application National Institute of TechnologyThiruchirapalliIndia School of Computer Science and Engineering Vellore Institute of TechnologyChennaiIndia Department of Computer Science and Engineering M.I.E.T Engineering CollegeTrichyIndia

Wireless sensor Networks(WsN)are commonly used to observe and monitor precise *** consist of a large number of inexpensive sensor nodes that have been separated and distributed in different *** base station received the amount of data collected by the numerous *** current developments designate that the attentFgion in applications of WsNs has been increased and extended to a very large *** trust-Based Adaptive Acknowledgement(tRAACK)intrusion-Detection system for Wireless sensor Networks(WsN)is described based on the number of active positive deliveries and the Kalman filter used in Modified Particle swarm Optimization(MPsO)has been proposed to predict knot *** were run for non-malicious networks(0%malicious)and different percentages of malicious nodes were *** findings suggest that the proposed method tRAACK Modified Particle swarm Optimization(MPsO)packet delivery rate outperforms tRAACKPsO by 3.3%with 0%malicious ***,the packet delivery rate of tRAACKMPsO is 30%malicious,3.5%better than tRAACKPsO in WsN.

关键词： trust-based adaptive acknowledgment(tRAACK) modified particle swarm optimization(MPsO) intrusion detection system(iDs) kalman filter

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Diagnosing Progressive Face Recognition from Face Morphing Using Vit technique through DL Approach 1

Diagnosing Progressive Face Recognition from Face Morphing U...

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1st iEEE international Conference on Networking and Communications, iCNWC 2023

作者： Mohamed Faizal, M.K. Geetha, s. Barveen, A. M.I.E.T. Engineering College Department of Computer Science and Engineering Tamilnadu Trichy India

ISBN: (纸本)9798350336009

the face-morphing attack, which occurs in private, public, and governmental institutions, is one of the most well-known in today's world. Face recognition systems tend to be vulnerable if the face images are manipulated with duplicate images. Manipulated images are combined with the original image so that the images look like legitimate ones. several face recognition studies are being conducted to determine whether the face images are manipulated. Using the DL algorithm, the face image is trained to attain the original and morphed face images by recognizing the face images. DL algorithms determine the images by classifying whether they are morphs or not recognizable to humans. in this paper, the foremost emphasis is on diagnosing the face recognition from those face-morphed images using the different DL techniques. Different DL techniques are effectively compared, where the Vit transformer attains improved accuracy when compared to Resnet, RNN, and CNN, respectively. this paper provides an overview of the various deep learning algorithms for detecting those face recognition images that focus on challenges and issues in the facial datasets from Face Recognition Kaggle dataset with training and testing image dataset. it determines the higher contrast in image efficiency and the evaluation of the face recognized images with an improved image. © 2023 iEEE.

关键词： Face recognition

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Meme Expressive Classification in Multimodal state with Feature Extraction in Deep Learning 2

Meme Expressive Classification in Multimodal State with Feat...

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2nd international Conference on Electrical, Electronics, information and Communication technologies, iCEEiCt 2023

作者： Barveen, A. Geetha, s. Faizal, M.K.Mohamed M.I.E.T. Engineering College Department of Computer Science and Engineering Trichy India University College of Engineering Department of Computer Applications Tamilnadu Trichy India

ISBN: (纸本)9798350397635

Memes are a socially interactive way to communicate online. Memes are used by users to communicate with one another on social networking sites and other forums. Memes essentially focus on speech recognition and image macros. While a meme is being created, it focuses on the semiotic type of resources that the internet community interprets with other resources, which facilitates the interaction among the internet and meme creators. Memes recreate based on various approaches, which fall under various acts such as existing speech acts. Based on the expressive face with captioned short texts, even the short text is exaggerated. Every year, meme mimicking applications are created that allow users to use the imitated meme expressions. Memes represent the shared texts of the younger generations on various social platforms. the classifications of sentiment based on the various memetic expressions are the most efficient way to analyse those feelings and emotions. HOG feature extraction allows the images to be segmented into blocks of smaller size by using a single feature vector for dimension, which characterizes the local object appearances to characterize the meme classification. the existence of specific characteristics, including such edges, angles, or patterns, is then analyzed by combining HOG features using multi-feature analysis on patches. Based upon the classification methodology, it classifies the sentiments, which tend to improve the learning process in an efficient manner. By combining a deep learning approach with a recurrent neural network, the extended LstM-RNN can identify subtle nuances in memes, allowing for more accurate and detailed meme classification. this proposed method effectively evaluates several classification techniques, including CNN and Extended LstM-RNN for meme image characterization. through training and validation, Extended LstM-RNN achieved 0.98% accuracy with better performance than CNN. © 2023 iEEE.

关键词： Feature extraction

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secure Key Management Based Mobile Authentication in Cloud

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computer systems science & engineering 2022年第12期43卷 887-896页

作者： s.shanmuga Priya D.Yuvaraj t.satyanarayana Murthy Varghese s.Chooralil s.Navaneetha Krishnan P.Banumathy P.sundaraVadivel Department of Computer Science and Engineering M.I.E.T Engineering CollegeTrichyTamilnaduIndia Department of Computer Science and Engineering Cihan UniversityDuhokKurdistan RegionIraq Department of Computer Science and Engineering Bapatla Engineering CollegeBapatlaAndhra PradeshIndia Department of Computer Science and Engineering Rajagiri School of Engineering and TechnologyKakkanadKeralaIndia Department Electronics and Communication Engineering SACS MAVMM Engineering CollegeMaduraiTamilnaduIndia Department of Information Technology Karaikal Polytechnic CollegeVarichikudy-KaraikalIndia Department of Computer Science and Engineering SACS MAVMM Engineering CollegeMaduraiIndia

Authentication is important to the security of user data in a mobilecloud environment. Because of the server’s user credentials, it is subject toattacks. to maintain data authentication, a novel authentication mechanism is proposed. it consists of three independent phases: Registration, login, and authentication and key agreement. the user registers with the Registration Center (RC)by producing a secret number that isn’t stored in the phone, which protects againstprivileged insider attacks. the user and server generate a nonce for dynamic useridentity and agree on a session secret key for safe communication. the passwordsare not stored on the computer or provided in plain text, they are resistant toreplay, guessing, and stolen verification attacks. the suggested protocol uses aone-way hash function and XOR operations, with the client having remote accessto a large number of servers over a secure communication channel. Concentrateson HMAC and sHA3 for Collision Free Hashing and to overcome length extension attacks. HMACs are substantially less affected by collisions than their underlying hashing algorithms alone. so adding an HMAC to an MD5 or sHA hashwould make it substantially more difficult to break via a rainbow table.

关键词： Registration center siM iMEi

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Effective & smart Urban Mobility system at Low Cost 2

Effective & Smart Urban Mobility System at Low Cost

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2nd international Conference Computational and Characterization techniques in engineering and sciences, iC3tEs 2024

作者： Jyothula, Hari Rao, Y Laxmana Prasad, K. Vara Usha, Chiriki Manikyamba, i Lakshmi Aditya University Department of Computer Science and Engineering Surampalem India Vignan's Institute of Engineering for Women Department of It Visakhapatnam India Avanthi Institute of Engineering & Technology I Department of Computer Science and Engineering India Dadi Institute Of Engineering And Technology Department of Computer Science and Engineering India University College of Engineering Science & Technology Hyderabad Jawaharlal Nehru Technological University Department of Computer Science and Engineering Hyderabad India

ISBN: (纸本)9798350364699

there is no established metric for measuring urban smartness at this time. Various writers use various metrics to assess smart city transportation systems. the assessment indicators for the transport system that were offered in the scholarly works were reviewed, and the most relevant and impactful indicators were chosen. A hierarchical assessment model for smart city transport systems is developed in this paper. there are five categories, or "factors,"that the indications fall into. several indicators are assigned to each of the categories. this study used the hybrid MCDM (multi-criteria decision-making) method to evaluate urban transport systems and identify which of the given characteristics were most important. top Priority sorting based on ideal solution similarity (tOPsis), COPRAs, and simple Additive Weighting (sAW) were the multi-criteria assessment methods in use. the importance of the components and indicators was determined using an analytical hierarchy process (AHP), rankings (prioritization), and direct evaluation (experts evaluate each criterion as a percentage;total assessments of all criteria equal 100%). there were two phases to the evaluation and comparison of mobility systems: first, smart mobility systems were evaluated comprehensively according to the integrated importance of the indicators;and second, multi-criteria evaluations were conducted according to the indicators of every factor separately. Based on the amount of intelligence, a top city is determined and rated. Building a hierarchical model for evaluating smart transportation systems is the focus of this paper. © 2024 iEEE.

关键词： Evaluation smart transportation MCDM smart City smart Mobility system Urban smartness

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