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2nd International Conference on Emerging Trends in Information Technology and engineering, ic-ETITE 2024

作者： Bhaskar, Swasthika Vanitha, M. School of Computer Science Engineering and Information Systems Vellore Institute of Technology Vellore India

ISBN: (纸本)9798350328202

In this constructive healthcare industry, AI-based IOMT (Internet of Medical Things) is one of the highly used Technologies. The virtual world is customary to lose responsible data in cyberspace. Without any doubt, IOMT comes under this category. IOMT applications do not intensively focus on Security and privacy and it is a Serious downside of IOMT applications. Considering this crucial issue, we use the Multiple-node machine learning Technique. It is widely used for preserving the privacy of the huge records. It does not want to share its sensitive data from one node to another node, which result in providing security and privacy to medical record by adding protection to input records, output tags, parameters, etc. This paper exclusively focuses on the Security and Privacy of Medical Records and also shows the various roles of Distributed Machine Learning. © 2024 IEEE.

关键词： Machine learning

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Equalizer Zero-Determinant Strategy in Discounted Repeated Stackelberg Asymmetric Game

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Journal of systems science & Complexity 2024年第1期37卷 184-203页

作者： CHENG Zhaoyang CHEN Guanpu HONG Yiguang Key Laboratory of Systems and Control Academy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing 100190China School of Mathematical Sciences University of Chinese Academy of SciencesBeijing 100049China School of Electrical Engineering and Computer Science KTH Royal Institute of Technology10044 StockholmSweden. Department of Control Science and Engineering Tongji UniversityShanghai 201804China Shanghai Research Institute for Intelligent Autonomous Systems Tongji UniversityShanghai 210201China

This paper focuses on the performance of equalizer zero-determinant(ZD)strategies in discounted repeated Stackelberg asymmetric *** the leader-follower adversarial scenario,the strong Stackelberg equilibrium(SSE)deriving from the opponents’best response(BR),is technically the optimal strategy for the ***,computing an SSE strategy may be difficult since it needs to solve a mixed-integer program and has exponential complexity in the number of *** this end,the authors propose an equalizer ZD strategy,which can unilaterally restrict the opponent’s expected *** authors first study the existence of an equalizer ZD strategy with one-to-one situations,and analyze an upper bound of its performance with the baseline SSE *** the authors turn to multi-player models,where there exists one player adopting an equalizer ZD *** authors give bounds of the weighted sum of opponents’s utilities,and compare it with the SSE ***,the authors give simulations on unmanned aerial vehicles(UAVs)and the moving target defense(MTD)to verify the effectiveness of the proposed approach.

关键词： Discounted repeated Stackelberg asymmetric game equalizer zero-determinant strategy strong Stackelberg equilibrium strategy

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Face Recognition Based Attendance Management System Using Deep Learning Method 2

Face Recognition Based Attendance Management System Using De...

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2nd International Conference on Emerging Trends in Information Technology and engineering, ic-ETITE 2024

作者： Angulakshmi, M. Susithra, V. School of Computer Science Engineering and Information Systems Vellore Institute of Technology Vellore India

ISBN: (数字)9798350328202

ISBN: (纸本)9798350328202

Deep learning and transfer learning are extremely important in the internet sector and the health care industry. Face recognition technology is essential in practically every industry in our digital age. Several improvements have been made to automatic facial recognition (AFR) technology in an ever-changing world. Managing the daily student attendance system is made simple with Smart attendance with Real-Time Face Recognition. In the proposed method, Images of the students in class are used to construct a dataset. Both Face detection and recognition are performed using the Multitask Convolution Neural Network algorithm. The data will be uploaded after the face is recognition. The proposed method compared with Haar Cascade Convolution Neural Network Classification method and other few methods. The proposed method produced better resultcompared to other methods © 2024 IEEE.

关键词： Students

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Enhancing User Authentication with a Secure Human-Computable Password Scheme 2

Enhancing User Authentication with a Secure Human-Computable...

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2nd International Conference on Emerging Trends in Information Technology and engineering, ic-ETITE 2024

作者： Ayeswarya, S. John Singh, K. School of Computer Science Engineering and Information Systems Vellore Institute of Technology Vellore India

ISBN: (纸本)9798350328202

Authentication in the digital world has become a challenging and difficult task. The username-password combination is no longer reliable and the tools that support authentication mechanism are all breakable. In addition to authentication, to avoid bots, CAPTCHA is used which increases the complexity of the system. Thus the research is going towards making use of human brain which is so unique and powerful in the authentication process. This will also eliminate the need for CAPTCHA since human is computing the password. To make it feasible, the function that is computed by the human should be simple enough. The existing method trusts the computer to store the public images and if there is a key logger installed in the system, the adversary will be able to get the password. This again tends to be a fixed password. Instead, if it is based on a challenge from the server, the password will be dynamic and secure. In this paper a human computable password protocol is suggested. The experimental results prove that the proposed technique is efficient and is less prone to attacks. © 2024 IEEE.

关键词： Authentication

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A Hybrid Approach to Validate and Retrieve Fingerprint Image for Authenticating Database Sensitive Information Access and to Verify Some of Topological Multi-Granular Rough Sets Properties on Authenticated Database Fields 2

A Hybrid Approach to Validate and Retrieve Fingerprint Image...

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2nd International Conference on Emerging Trends in Information Technology and engineering, ic-ETITE 2024

作者： Raghavan, R. John Singh, K. School of Computer Science Engineering and Information Systems Vellore Institute of Technology Vellore India

ISBN: (纸本)9798350328202

Content based image retrieval has already begun to turn into an intriguing and exceptionally needed field to meet with the client prerequisite. Fingerprint approvals likewise have become a fascinating field to principally uphold the confirmation framework. Notwithstanding foundations regulating guaranteed about information straightforwardly, affiliations are also obliging them to examine the fingerprint endorsement. Despite establishments overseeing ensured about data, directly associations are similarly obliging them to research the fingerprint check. Organizations and foundations both are typically utilizing the idea of fingerprint for the participation and presence reason. Nevertheless, establishments presently managing secured information as like institutes and additionally going along with them to investigate the fingerprint authentication. More than this usual action there are some particular applications where the authentication would be considerable to help the application than using a traditional pattern of password. We proposed a fingerprint authentication system for the scientific based industry database access system. We removed the noise if any found in the input fingerprint using anisotropic Gauss filtering. The noise free fingerprint image is not further passed to the binarization phase as the need of binarization and some form of the drawback of binarization is replaced with a thinning algorithm. The thinned fingerprint image is followed by the matching process and once it is matched, then only the sensitive and highly confidential information are allowed to access from the database. The testing is done using OpenCV and FVC 2004 dataset to assess the projected retrieval method. Further the matched fingerprints are used to prove some of the internal structure properties of multi-granular rough sets (MGRS) on authenticated database fields. The accuracy obtained in this hybrid approach is found to be more satisfactory and hence the security towards acce

关键词： Database systems

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Securing the Industrial IoT: A Novel Network Intrusion Detection Models 3

Securing the Industrial IoT: A Novel Network Intrusion Detec...

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

作者： Ramaiah, Mangayarkarasi Rahamathulla, Mohemmed Yousuf Vellore Institute of Technology School of Computer Science Engineering and Information Systems Vellore India

ISBN: (纸本)9798350372120

The growth of automation in the industry makes securing IoT networks a critical priority. A resilient network intrusion detection system (NIDS) can reduce cyber threats. Detecting network traffic irregularities with deep learning (DL) and machine learning (ML) techniques can improve IoT network security and reduce cyber threats. This study analyzes the merits of LSTM and other ML models in mitigating anticipated security breaches in Industrial IoT (IIoT) networks. To design robust NIDS, including an appropriate dataset is essential. Therefore, to identify dynamic threats targeting Industrial Internet of Things (IIoT) networks, deep learning (DL) and machine learning (ML) models underwent training and evaluation utilizing the EdgeIIoT-2021 dataset. The experimental findings demonstrate that the proposed approach surpasses the performance of the current state-of-the-art Network Intrusion Detection systems (NIDS). The ERT-based IIoT-NIDS achieved a cyber-attack detection accuracy of 99.93%, while the LSTM-based IIoT-NIDS achieved an accuracy of 99.85%. © 2024 IEEE.

关键词： Network security

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Enhancing Video Protection: A Reversible Digital Watermarking approach using Swin features and Arnold Transform enabled Multi-Aggregation Model 3

Enhancing Video Protection: A Reversible Digital Watermarkin...

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

作者： Dilip, Mali Satish Agilandeeswari, L. Vellore Institute of Technology School of Computer Science Engineering and Information Systems Vellore India

ISBN: (纸本)9798350372120

Nowadays, the widespread internet technology brings out rapid advancement in the use of videos for sharing huge amounts of secret data. Conversely, the privacy of transmitted digital content is jeopardized by digital image processing techniques that are capable of producing flawless image or video duplication. Moreover, providing security to digital records in the form of videos is a highly challenging task, which requires a fusion-based watermarking technique to protect the data from illegitimate access and fraudulent usage. In this investigation, a tiny Swin and Arnold Transform-enabled Multi-aggregation model was introduced to protect video based on digital watermarking characteristics at a very low computational cost. Here, the Swin-T features are extracted from the input video, over which the Arnold transform and multi-aggregation model is developed in two phases. The best embedding location is identified by using multi aggregation model initially at the embedding phase and the inverse Arnold transform for secret image (VIT Logo) embedding in a binary embedding location to obtain the embedded video. The secret image is extracted from the attacked embedded video using the Arnold transform-multi-aggregation model in the extraction phase. The developed data-hiding technique is also evaluated to compute the robustness using the evaluation parameters. The simulation results reveal that the developed scheme achieved Peak-Signal-to-Noise Ratio (PSNR) and Similarity Index Measure (SSIM) values of 64.57 ∼dB and 0.9993 respectively. © 2024 IEEE.

关键词： Embeddings

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A Study on Enhanced Curricula Delivery Using Augmented/Virtual Reality 2

A Study on Enhanced Curricula Delivery Using Augmented/Virtu...

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2nd International Conference on Emerging Trends in Information Technology and engineering, ic-ETITE 2024

作者： Sarath, T. Brindha, K. School of Computer Science Engineering and Information Systems Vellore Institute of Technology Vellore India

ISBN: (纸本)9798350328202

In human perceptive, Augmented Reality (AR) or Virtual Reality(VR) is an effective and deep technology because it creates new replicated world. The AR or VR technique is a distinctive and lucrative application;its imminent will consume a positive influence on technique. Moreover, AR/VR technology is accomplished by persons as amount of new thoughts discoveries and provides us wide concepts like sensory relationship with humans. The AR/VR operates different types of locations which consume different goals and boost the abilities in building, engineers, interior designers and upsurge production in changed business zones and familiarize a novel physical world. By using VR, multiusers developed and implemented collaboration, which highpoints the creativity of human's, and maximum people can carry their choices. Consequently, AR or VR is relatively new technique that is being used at the experimental stage for curriculum building and training design. In this context, here identified some current uses of augmented reality in training and curriculum design. The themes covered in this article are: a brief introduction about AR, the current uses of AR/VR tools in curriculum and training development, how AR/VR works used in education for student engagement, future implications of augmented reality in curriculum and training development. © 2024 IEEE.

关键词： Curricula

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Survival Analysis of Superficial Bladder Cancer patients using DeepSurv and Cox models 2

Survival Analysis of Superficial Bladder Cancer patients usi...

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2nd International Conference on Emerging Trends in Information Technology and engineering, ic-ETITE 2024

作者： Supriya, K. Anitha, A. School of Computer Science Engineering and Information Systems Vellore Institute of Technology Vellore India

ISBN: (纸本)9798350328202

The advancements in technology help in analyzing and predicting the disease of human life using automation. Out of various technologies, Machine Learning (ML) and Deep learning (DL) provide some promising results to help humankind. Automated technologies help improve the prediction process of the healthcare system, especially in carcinoma detection based on past information. Thus, the proposed model made a survival analysis of the patients who are affected by bladder cancer (BC) based on their past health records. The tumor in the urinary bladder indicates that cancer among patients, when not treated can be spread to the other parts of the human body and cause death. However, the health records provide some linear combinations of the data to analyze the survival rate on treatments such as Placebo and Thiotepa. Thus, the proposed work utilized DeepMLPSurv and CoxPH survival model to make an analysis on the tumour recurrence and predicts the survival rate among the bladder cancer patients. © 2024 IEEE.

关键词： Diseases

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Enhancing User Authentication through Keystroke Dynamics Analysis using Isolation Forest algorithm 2

Enhancing User Authentication through Keystroke Dynamics Ana...

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2nd International Conference on Emerging Trends in Information Technology and engineering, ic-ETITE 2024

作者： Iyapparaja, M. Karunanithi, Isvarya Sahana Bhat, U. School of Computer Science Engineering and Information Systems Vellore Institute of Technology Vellore India

ISBN: (纸本)9798350328202

Authentication in modern era, has evolved significantly to address the increasing complexity and security challenges of our digital world. Traditional methods of authentication, such as passwords and PINS have proven to be vulnerable to various forms of attacks. As a result there is a growing need for innovative and robust authentication techniques. Keystroke dynamics involves the analysis of user typing patterns, including the time interval between keystrokes and the key pressed duration, to establish a unique biometric profile for each individual. Unlike traditional authentication methods keystroke dynamics offer several advantages, such as continuous authentication without the need for additional hardware and the ability to adapt to a user's changing typing behavior. This model will additionally analyze users typing patterns have the capability to identify individuals using the system by considering their typing speed. The first premise involves developing a system that can capture the keystroke dynamics of a user during a training phase and create a unique profile for that user. The second premise involves implementing Mahalanobis distance for Dynamic keystroke Authentication with various machine learning algorithms. This model can maximize the strengths of both methods to improve the accuracy and robustness of the authentication system. Authentication using keystroke dynamics is secured and convenient method and can be used wherever there is requirement of authentication such as baking, e-commerce and secured access control system. From the experiment performed below we can attained that the model functions exceptionally well using Isolation Forest with an accuracy of 90%. © 2024 IEEE.

关键词： Support vector machines

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