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AI-Driven Healthcare cyber-security: Protecting Patient Data and Medical Devices 2

AI-Driven Healthcare Cyber-security: Protecting Patient Data...

引用

2nd international conference on intelligent cyber Physical systems and Internet of Things (ICoICI)

作者： Bonagiri, Krishna Marx, V. S. Nici Gopalsamy, Mani Iyswariya, A. Helan, R. Reni Hena Sultanuddin, S. J. Quadrant Technol Redmond WA 98052 USA Saveetha Engn Coll Dept CSE Chennai Tamil Nadu India Coolsoft 3240 Off Pointe Pl Suite 200 Louisville KY 40220 USA RMK Engn Coll Dept ECE Chennai Tamil Nadu India Dhanalakshmi Coll Engn Dept Comp Sci & Engn Chennai Tamil Nadu India Dhanalakshmi Coll Engn Dept Cyber Secur Chennai Tamil Nadu India

ISBN: (纸本)9798331540661;9798331540678

The use of artificial intelligence (AI) in healthcare has transformed both operational and patient outcomes in the contemporary period. But with these developments comes the crucial problem of cybersecurity. This study explores the relationship between AI-driven technology and cybersecurity in the healthcare industry, with a particular emphasis on patient data and medical device protection. The paper begins by outlining the pivotal role AI plays in healthcare, from enhancing diagnostics to optimizing treatment plans. It then highlights the vulnerabilities that arise as healthcare systems become increasingly interconnected and reliant on AI algorithms. Central to this discussion are the unique cybersecurity challenges posed by AI, such as adversarial attacks and data privacy concerns. Furthermore, the research explores current strategies and technologies employed to safeguard patient data and medical devices. It examines the role of AI itself in bolstering cybersecurity defenses, including anomaly detection and predictive analytics. Case studies and examples from recent cyber incidents highlight the need for addressing these issues comprehensively. Finally, the paper proposes future directions for research and development in AI-driven healthcare cybersecurity.

关键词： AI-driven cyber security Healthcare cyber security Medical device security Data encryption

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Research on a Identifying Maliciously Manipulated Measurement Data Based on Characteristics of cyber-Physical System 12

Research on a Identifying Maliciously Manipulated Measuremen...

引用

12th ieee international conference on Information and Communication Networks, ICICN 2024

作者： Kim, Ka-Kyung Kim, Joon-Seok Euom, Ieck-Chae System Security Research Center Chonnam National University Gwangju Korea Republic of

ISBN: (纸本)9798350355802

intelligent attackers targeting critical infrastructure frequently conceal their attack strategies until their objectives are accomplished. Despite extensive research on detecting manipulated data, much of this research fails to consider the real-world noise inherent in cyber-physical systems. This paper addresses these shortcomings by integratively applying an Unscented Kalman Filter and an Entropy approach. The efficacy of this method is confirmed through its application to a publicly available industrial control system security dataset, demonstrating its capability to accurately detect manipulated data. © 2024 ieee.

关键词： Wiener filtering

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A Roadside Unit Software Platform for intelligent Transportation System Applications 11

A Roadside Unit Software Platform for Intelligent Transporta...

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11th ieee international conference on Consumer Electronics - Taiwan (ICCE-Taiwan) - Empower of Innovative Consumer technology

作者： Su, Chih-Han Cheng, Xue-Yang Wang, Shao-Hua Hsu, Yung-Jen Chang, Da-Wei Tu, Chia-Heng Lee, Wei-Hsun Natl Cheng Kung Univ Tainan Taiwan

ISBN: (纸本)9798350386851;9798350386844

intelligent transportation systems (ITS) play a critical role in modern urban transportation by improving traffic management and enhancing safety. The emergence of various ITS applications demands that roadside units (RSUs) be capable of hosting multiple applications simultaneously. This paper introduces an RSU platform designed for simultaneous hosting of multiple ITS applications. It not only reduces the effort of ITS application development but also resolves conflicts in traffic signal control strategies among different applications. Performance results demonstrate that the platform has the capability of handling 1000 on-board units (OBUs), sufficient for an RSU at a single intersection. The platform is currently deployed at 31 intersections in Tainan City, Taiwan, demonstrating its practical feasibility.

关键词： intelligent Transportation systems Roadside Units Traffic Signal control

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Data processing technology of distribution station area combined with convolutional neural network 12

Data processing technology of distribution station area comb...

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12th international conference on cyber technology in automation, control, and intelligent systems, cyber 2022

作者： Zhang, Kexin Dou, Xiaobo Yu, Hang Hu, Yongming School of Electrical Engineering Southeast University Nanjing China

ISBN: (数字)9781665472678

ISBN: (纸本)9781665472678

As the end of the distribution network closest to the user, the station area is very important to ensure the stability and safety of the station area. But now the station area has more problems in data collection and storage than the Central Asian side. This makes it more difficult to optimize the regulation of the Taiwan area. Aiming at the problems of abnormal sampling period, abnormal sampling reference time, data noise, and missing data in the data of the station area, this paper proposes a data processing method combining convolutional neural network and mathematical methods to solve these problems in the station area, and constructs a station The accurate time series of regional data was obtained, and the feasibility of the method was verified by simulation. © 2022 ieee.

关键词： Convolutional neural networks

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A State Partition Particle Filter based Approach for Detection of Switching Attack

A State Partition Particle Filter based Approach for Detecti...

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2024 international conference on Communications control and Computing Technologies for Smart Grids

作者： Yadav, Seema Kishor, Nand Purwar, Shubhi Rajkumar, Vetrivel Subramaniam Stefanov, Alexandru Motilal Nehru Natl Inst Technol Dept Elect Engn Prayagraj India Osold Univ Coll Dept Engn Fredrikstad Norway Delft Univ Technol Dept Elect Sustainable Energy Delft Netherlands

ISBN: (纸本)9798350318562;9798350318555

The increasing risk of cyber-physical attacks (CPAs) on power infrastructure has led to need for reliable detection technologies. As the landscape of cyber threats evolves, it becomes imperative to continually update and enhance attack detection techniques. This research investigates the formulation of detection algorithm, via combination of State Partition Particle Filter (SP-PF) theories for power system security. The proposed approach applies intelligent partitioning of the state space so as to be accurately represented with fewer particles. This reduction in computational demand enhances the algorithm's efficiency, making it more practical for real-time applications. The detection algorithm based on SP-PF is tested against switching attacks (SAs) launched on the governor and excitation systems associated with the generator. The RTDS platform is utilized for conducting real-time simulations of ieee 9-bus power network in order to demonstrate the efficacy of proposed SP-PF based detection SA in real-time.

关键词： cyber-physical attack detection state-partition particle-filter estimation real-time simulation switching attack

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Exact Reachability of Linear Stochastic System with Partial Information

Exact Reachability of Linear Stochastic System with Partial ...

引用

ieee international conference on cyber technology in automation, control, and intelligent systems

作者： Jiaye Yao Wei Wang Juanjuan Xu School of Control Science and Engineering Shandong University Jinan China

ISBN: (数字)9798331506056

ISBN: (纸本)9798331506063

In this paper, we study the exact reachability of a kind of linear stochastic systems with partial information. The system is described by a class of Itô stochastic differential equation that includes a controller and two independent multiplicative noises, only one of which is available to design the controller. The main contribution is to derive the necessary and sufficient Gramian criterion for the exact reachability of the system with partial information. In particular, the derived result contains the case with complete information as a special case.

关键词： automation Stochastic systems Noise Differential equations control systems intelligent systems

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Improved YOLOv5-based Method for Recognition of Insulator String Pins 12

Improved YOLOv5-based Method for Recognition of Insulator St...

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12th international conference on cyber technology in automation, control, and intelligent systems, cyber 2022

作者： Du, Jingbo Jiang, Yong Shenyang Ligong University Shenyang110158 China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China

ISBN: (数字)9781665472678

ISBN: (纸本)9781665472678

Aiming at the problem that the substation insulator replacement robot cannot accurately identify insulator pins in the complex outdoor light environment, an improved YOLOv5-based insulator pin identification method YOLOv5-CBP is proposed. For the substation insulator pin recognition task, the backbone of the network is replaced by the lightweight EfficientNet-lite0;the Neck of the network is optimized and a more efficient feature fusion module BiFPN combined with an attention mechanism is introduced. The bounding box regression loss function was changed to improve the accuracy of inspection frame detection. Finally, the improved algorithm is compared with the original YOLOv5 algorithm on a self-built dataset for experiments. The results show that the insulator pin recognition accuracy is improved by 8.3%, the size of the algorithm model is reduced to 54% of the original, and the number of parameters is reduced by 49.4%. The improved algorithm model more lightweight. © 2022 ieee.

关键词： Degradation Substations Inspection Insulators control systems Pins Neck

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Advancing Intrusion Detection with Machine Learning: Insights from the UNSW-NB15 Dataset

Advancing Intrusion Detection with Machine Learning: Insight...

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2024 ieee international conference on Information technology, Electronics and intelligent Communication systems, ICITEICS 2024

作者： Kumar, Atul Guleria, Kalpna Chauhan, Rahul Upadhyay, Deepak Chitkara University Chitkara University Institute of Engineering and Technology Punjab India Graphic Era Hill University Computer Science & Engineering Uttarakhand Dehradun248002 India

ISBN: (纸本)9798350382693

This research undertakes a comparative examination of the recall performance of Logistic Regression (LR), Random Forest (RF), and Decision Tree (DT) models for intrusion detection systems (IDS). The analysis is conducted using the UNSW-NB15 dataset, which is a comprehensive compilation of contemporary cyber-attack scenarios. The objective is to assess the effectiveness of these models in their respective roles. According to our investigation, Random Forest has superior performance compared to LR and DT in the detection of network intrusions. It exhibits the greatest recall values, which are of utmost importance in mitigating false negatives in Intrusion Detection systems (IDS). The exceptional efficacy of RF highlights its resilience and versatility in addressing the intricate and diverse array of cyber threats. While LR demonstrated impressive outcomes, particularly when dealing with less complex assault methods, and DT provided simplicity in interpretation, both were somewhat less efficient when compared to RF. The results indicate that Random Forest has great potential for use in modern Intrusion Detection systems (IDS), prompting more investigation into ensemble methods, deep learning, and unsupervised learning approaches to improve threat detection. This work contributes to the progress of machine learning-based security measures and guides the creation of more efficient and adaptable Intrusion Detection systems (IDS) that can effectively address the changing nature of cyber threats. © 2024 ieee.

关键词： Network intrusion

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A Foot-based Wearable Assist Mechanism Based on Tensegrity Structure 12

A Foot-based Wearable Assist Mechanism Based on Tensegrity S...

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12th international conference on cyber technology in automation, control, and intelligent systems, cyber 2022

作者： Sun, Jianwei Wang, Zhenyu School of Mechanical Engineering Changchun University of Technology Changchun China Jilin University Key Laboratory of Bionic Engineering Changchun China

ISBN: (数字)9781665472678

ISBN: (纸本)9781665472678

Assist mechanism applied to the lower limbs is an important requirement in the field of sports research and medical rehabilitation. In this paper, we propose a foot-based wearing assist mechanism with metatarsophalangeal joint (MPJ) flexion assist and force locking function based on the flexibility and self-recovery characteristics of the tensegrity structure. The structural stability of the mechanical members of the joint structure was demonstrated by stiffness matching through analysis of the tensegrity nodes. In addition, simulations of the MPJ flexion states at different stiffness states were performed to discuss the mechanical properties of different stiffnesses in toe flexion. The results indicate that the wearable foot-assist mechanism based on the tensegrity structure provides a uniform solution for the two states of human walking and running. © 2022 ieee.

关键词： Stiffness

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Advancing Security in 5G Core Networks through Unsupervised Federated Time Series Modeling

Advancing Security in 5G Core Networks through Unsupervised ...

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4th ieee Annual international conference on cyber Security and Resilience (ieee CSR)

作者： Sheikhi, Saeid Kostakos, Panos Univ Oulu Fac Informat Technol & Elect Engn Ctr Ubiquitous Comp Oulu 90014 Finland

ISBN: (纸本)9798350375367

The rapid development of fifth-generation (5G) mobile communication technology poses fresh challenges for cyber-security defense systems. Current intrusion detection mechanisms in 5G networks have shortcomings, particularly in identifying sophisticated cyber attacks. Our study presents a novel approach combining Federated Learning with Long Short-Term Memory (LSTM) networks to enhance cyber threat detection on the GTP protocol within 5G infrastructures. Our approach leverages the collective analytical power of multiple devices to identify cyber threats more effectively. The model validated against two major cyber threats, Distributed Packet Forwarding control Protocol (PFCP) and IP address spoofing emulated within a specially constructed 5G test environment that mirrors a complex public network infrastructure. The findings demonstrate that our unsupervised FL-LSTM model effectively identifies 5G cyber threats while preserving individual network traffic privacy, highlighting Federated Learning's potential to strengthen 5G and beyond network security.

关键词： 5G security cyber-security LSTM intrusion detection systems

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