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Securing Electronic Health Records from Insider Threats in Smart City Healthcare cloud Using Machine Learning Approach 5

Securing Electronic Health Records from Insider Threats in S...

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5th international conference on Intelligent communication Technologies and Virtual Mobile Networks, ICICV 2024

作者： Ramasami, S. Uma Maheswari, P. Bannari Amman Institute of Technology Department of Computer Science and Engineering Sathyamangalam Erode India Anna University Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350385649

In recent years, healthcare in smart cities is considered as significant to create a more resilient and well-informed healthcare ecosystem. The integration of cloud computing in healthcare industry has facilitated the storage and sharing of electronic health records (EHRs), enabling seamless access to medical information. However, this transition to cloud-based systems has introduced new security challenges, particularly the risk of insider threats. Insiders with authorized access to cloud-based EHR systems, such as healthcare professionals and cloud service providers, may exploit vulnerabilities or misuse sensitive patient data, leading to privacy breaches and unauthorized disclosure. This research work presents an innovative approach to securing EHRs from insider threats in the cloud using Gaussian Mixture Model and Classification algorithms. These techniques analyze user behaviour patterns and detect anomalous activities that may indicate insider threats. Here UK hospital electronic patient health record data set is used to conduct the experiments. The proposed approach comprises two key stages. In the initial stage, the unsupervised Gaussian Mixture Model is utilized to find the abnormal patterns in the dataset and label each record in the dataset as normal or anomaly. The second stage involves different supervised classification algorithms namely SVM, KNN, DT, NB and RF are used to classify the new instance. The results demonstrate that the Random Forest (RF) achieves high accuracy in detecting insider threats with an accuracy of 99.97%. The findings of this research contribute to the field of healthcare data security by offering an intelligent and proactive solution for mitigating insider threats to cloud-based EHRs in Smart city environments. © 2024 IEEE.

关键词： Support vector machines

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cloud computing based Smart Traffic Management System with Priority Switching for Health Care Services 2

Cloud Computing based Smart Traffic Management System with P...

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2nd international conference on Applied Artificial Intelligence and computing, ICAAIC 2023

作者： Shiny, X.S. Asha Ravikumar, D. Chinnasamy, A. Hemavathi, S. Department of Computer Science and Engineering Telangana Hyderabad India Kings Engineering College Department of Electronics and Communication Engineering Tamil Nadu Chennai India School of Computing Srm Institute of Science and Technology Department of Data Science and Business Systems Tamil Nadu Chennai India Sri Sairam Engineering College Department of Computer Science Engineering Tamil Nadu Chennai India

ISBN: (纸本)9781665456302

Regular cities can be transformed into intelligent structures by leveraging information and communication technologies. Innovative city development could be significantly impacted by the Internet of Things paradigm, commonly called cloud computing. All urban locations have a lot of traffic. In this study, Internet-of- Things (IoT) based system is proposed for health care services to organize and to establish the traffic signaling and pick up a route under which road congestion can be administrated. Vehicle accident contraventions are identified by the traffic officers using an online service that is hierarchically carefully monitored or constrained. However, the suggested approach is generic and may be utilized in any major metropolis without losing its generality. Traffic lights linked to cameras in metropolitan areas can be upgraded by connecting to IoT. During a pandemic, this approach is precious. The police can easily regulate traffic from their homes using their cell phones and identify defaulters. The suggested technique aids in the separation of ambulance and rescue engines from ordinary traffic. © 2023 IEEE.

关键词： Internet of things

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Systematic Threat Modelling of High-Performance computing Systems: The V:HPCCRI Case Study 14

Systematic Threat Modelling of High-Performance Computing Sy...

引用

14th international conference on cloud computing and Services Science, CLOSER 2024

作者： Elia, Raffaele Granata, Daniele Rak, Massimiliano Department of Engineering University of Campania Luigi Vanvitelli CE AversaVia Roma 9 Italy

ISBN: (纸本)9789897587016

High-Performance computing (HPC) systems play a crucial role in different research and industry tasks, boasting high-intensity computing capacity, high-bandwidth network connections, and extensive storage at each HPC centre. The system’s objectives, coupled with the presence of valuable resources and sensitive data, make it an attractive target for malicious users. Traditionally, HPC systems are considered"trusted" with users having significant rights and limited protective measures in place. Additionally, its heterogeneous nature complicates security efforts. Applying traditional security measures to individual cluster nodes proves insufficient as it neglects the system’s holistic perspective. To address these challenges, this paper presents a methodology for collecting threats affecting HPC environments from the literature analysis using a Systematic Search. Key contributions of this work include the application of the presented methodology to support the HPC domain through the definition of an HPC-specific threat catalogue and, starting from it, the generation of a threat model for a real-world case study: the V:HPCCRI supercomputer. © 2024 by SCITEPRESS – Science and Technology Publications, Lda.

关键词： Supercomputers

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Lattice-based Distributed Broadcast Encryption in Multi-user communication Mechanism 24

Lattice-based Distributed Broadcast Encryption in Multi-user...

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5th international conference on Artificial Intelligence and Computer engineering, ICAICE 2024

作者： He, Junfei Ye, Qing Yang, Zhichao Department of Information Security Naval University of Engineering Hubei Wuhan China

ISBN: (纸本)9798400718007

Nowadays, emerging technologies such as smart terminals, cloud computing, and the Internet of Things are developing rapidly. The"One-to-one" encrypted transmission method is difficult to meet the communication needs in complex network environments due to high computational costs. Broadcast encryption technology can provide data encryption protection during information sharing among multiple users. However, most of the existing schemes are based on bilinear groups, which cannot resist quantum computing attacks. And these schemes also suffer from the key escrow problem. For this reason, a novel distributed broadcast encryption scheme is proposed based on the Learning with Errors (LWE) difficulty assumption on the lattice. The scheme avoids key interaction negotiation among users by introducing a public key bulletin board. Meanwhile, the scheme solves the security problem caused by the authoritative user's complete mastery of the user's private key. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： data security

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Data Placement Strategy of Data-Intensive Workflows in Collaborative cloud-Edge Environment 10

Data Placement Strategy of Data-Intensive Workflows in Colla...

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10th IEEE international conference on Cyber Security and cloud computing and 9th IEEE international conference on Edge computing and Scalable cloud, CScloud-EdgeCom 2023

作者： Liang, Yang Ding, Changsong Hu, Zhigang Hunan University of Chinese Medicine School of Informatics Changsha China Central South University School of Computer Science and Engineering Changsha China

ISBN: (纸本)9798350312461

With the continuous development and integration of mobile communication and cloud computing technology, cloud-edge collaboration has emerged as a promising distributed paradigm to solve data-intensive workflow applications. How to improve the execution performance of data-intensive workflows has become one of the key issues in the collaborative cloud-edge environment. To address this issue, this paper built a data placement model with multiple constraints. Taking deadline and execution budget as the core constraints, the model is solved by minimizing the data access cost of workflow in the cloud-edge clusters. Subsequently, an immune genetic-particle swarm hybrid optimization algorithm (IGPSHO) is proposed to find the optimal replica placement scheme. Through simulation, compared with the classical immune genetic algorithm (IGA) and particle swarm optimization (PSO), the IGPSHO has obvious advantages in terms of workflow default rate, time-consuming ratio, and average execution cost when the workflow scale is large. © 2023 IEEE.

关键词： Budget control

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Internet of Things (IoT) Based Cost Effective Weather Monitoring Station

Internet of Things (IoT) Based Cost Effective Weather Monito...

引用

2023 IEEE international conference on Device Intelligence, computing and communication Technologies, DICCT 2023

作者： Chakraborty, Subhradip Joshi, Tanmay Agarwal, Sajal Rajiv Gandhi Institute of Petroleum Technology Department of Electrical and Electronics Engineering Jais India

ISBN: (纸本)9781665474924

The cost-effective weather station proposed here adopts a new practical approach for monitoring the weather conditions at different places and sharing the meteorological data anywhere across the globe. The main feature of the proposed work is the inclusion of Air Quality Index monitoring, it also sends the information to the cloud server. Internet of Things (IoT) is a network of various devices connected together to a system which extracts data from them and utilizes that data for various purposes. © 2023 IEEE.

关键词： Internet of things

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Mitigating Distributed Denial of Service (DDoS) Attacks in cloud Networks Using Neural Networks 2

Mitigating Distributed Denial of Service (DDoS) Attacks in C...

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2nd international conference on Advanced computing and communication Technologies, ICACCTech 2024

作者： Singh, Jagendra Ali, Jabir Sharma, Preeti Kumar, Vinish Sharma, Meenakshi Singh, Ramendra School of Computer Science Engineering & Technology Bennett University Greater Noida India Ghaziabad India Ghaziabad India Inderprastha Engineering College Department of Electronics & Communication Engineering Ghaziabad India Ghaziabad India

ISBN: (纸本)9798331519056

The research aims to prove the effectiveness of three neural network models the convolutional neural network (CNN) and Long Short-Term Memory (LSTM) Hybrid, Variational Autoencoders, and Bidirectional LSTM in neutralizing DDoS attacks on online shopping websites. The models are ranked using critical performance metrics relevant to cybersecurity. Firstly, the CNN-LSTM Hybrid has demonstrated a very high True positive rate (TPR), with a reading of 0.95, as well as a low False positive rate (FPR) of 0.03, resulting in a precision of 0.93 and a recall of 0.95. The readings show that the model is accurate in distinguishing between regular traffic and DDoS attacks, having an overall Fl-Score of 0.94. On the anomaly detection-based Variational Autoencoders (VAEs), the TPR was 0.92, the FPR was 0.05, the precision was 0.90, and the recall 0.92. The bidirectional LSTM model returned a TPR of 0.94 and an FPR of 0.04, and both precision and recall were also brought to 0.92 with an Fl-score of 0.93. These models improve online shopping website security from cyberattacks by preventing data availability and consistency. As DDoS attack discovery is a major step for continuing institutions, the designs serve administrators and greatly protect online buyers. © 2024 IEEE.

关键词： Convolutional neural networks

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Advancing Patient Care for Autonomous Saline Level Alert System with cloud-Based Isolation Forest Algorithm 5

Advancing Patient Care for Autonomous Saline Level Alert Sys...

引用

5th international conference on Electronics and Sustainable communication Systems, ICESC 2024

作者： Nandhini, R. Sumathi, G. Ramya, S. Thulasi, Saravanan Ishwarya, M.V. Murugan, S. Rajalakshmi Institute of Technology Department of Electronics and Communication Engineering Tamil Nadu Chennai India Department of Information Technology Tamil Nadu Trichy India Paavai Engineering College Department of Cyber Security Tamil Nadu Namakkal India John Deere India Pvt Ltd Customer and Product Support Services Maharashtra Pune India Agni College of Technology Artificial Intelligence and Data Science Department Tamil Nadu Chennai India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Department of Biomedical Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350379945

This work presents a novel method for improving patient care by creating a self-sufficient system to detect saline levels using an Isolation Forest Algorithm (IFA) hosted on the cloud. Standard practices for checking saline levels in IV infusion systems often include human intervention, which might cause important discrepancies to go undetected for longer periods of time. It presents a system that uses machine learning to identify aberrant saline levels in real-time, improving patient safety and relieving healthcare providers of some of their workload. The IFA, a powerful anomaly detection tool that works particularly well with high-dimensional data like that produced by intravenous infusion devices, is at the heart of our strategy. It gains scalability, flexibility, and real-time processing capabilities crucial for early alerting in clinical settings by implementing our algorithm on the cloud. Extensive testing and validation with both synthetic and real-world datasets prove that our suggested approach reliably and effectively detects abnormal saline levels with few false alarms. By providing healthcare practitioners with prompt alerts of possible infusion anomalies and allowing proactive action to avert adverse events, the autonomous saline level alarm system has major implications for patient care. The technology provides smooth interaction with current healthcare infrastructure by moving computing duties to the cloud, which eliminates the need for extra hardware and maintenance burdens. © 2024 IEEE.

关键词： Digital storage

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System for Data Center Environmental Monitoring that Uses Visible Light communication Positioning

System for Data Center Environmental Monitoring that Uses Vi...

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2023 international conference on Mobile Internet, cloud computing and Information Security, MICCIS 2023

作者： Xu, Xinlan Guo, Min'An Zeng, Yu Wang, Tao Zhang, Ziting Al Research Center China Telecom Research Institute Beijing China Beijing University of Posts and Telecommunications School of Information and Communication Engineering Beijing China Big Data and AI Center China Telecom Beijing China

ISBN: (纸本)9798350300932

This paper designs an environment monitoring system for data center rooms based on Visible Light communication positioning, which provides an innovative solution for the management of unattended data centers. Combined with the experience and requirements of manual inspection, the system uses automatic inspection equipment, which can accurately reflect the fault situation and improve the automation level of equipment management. In terms of positioning, this paper uses an indoor positioning method based on fingerprint and visible light communication and estimates the most likely position of the mobile terminal through the nearest neighbor fingerprint algorithm, which greatly reduces the computational complexity of the fingerprint positioning method. The simulation results show that high indoor positioning accuracy is achieved. © 2023 IEEE.

关键词： Visible light communication

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A Meticulous Range of Forensics Tech Advancement in the field of IoT, IIoT and MIoT 5

A Meticulous Range of Forensics Tech Advancement in the fiel...

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5th IEEE international conference on computing, Power, and communication Technologies, IC2PCT 2024

作者： Matta, Priya Kamalraj, R. Saxena, Kumud Tula's Institute Department of Computer Science and Engineering Dehradun India Department of Computer Science and Information Technology Bangalore India Noida Institute of Engineering and Technology Department of Computer Science Engineering Uttar Pradesh Greater Noida India

ISBN: (纸本)9798350383522

Wide application of millions of connected, intelligent, and flexible gadgets in critical infrastructures like medical facilities, public transit, sustainability, and home automation has been driven by latest expansions in intelligence technology and hardware. Clients profit from consistency and accessibility when data is transmitted across the internet deprived of the need for any kind of person to person or person-to-computer communication however this additionally creates new prospects for hackers and increases a number of complicated and challenging issues for the area of online forensics. Regardless of the fact that IoT records may be a valuable evidence source, forensics professionals must deal with a wide range of issues, starting the massive diversity of IoT devices and unrecognized setups to the multi-tenant platforms of cloud and the ensuing multijurisdictional lawsuits. Encryption at all levels, which compromises users' rights regarding confidentiality for the benefit of forensics study, is another difficulty. The aim of this work is to recognize and address the issues connected through the complex procedure of IoT based inquiries, particularly the privacy and security problems. The study also examines the application of IoT forensics across different industries. © 2024 IEEE.

关键词： IoT (Internet of things) IoT forensics privacy issues and digital forensics Security issues

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