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Unifying Sky and Chain: A Perspective on Blockchain's Role in UAV Swarms 2

Unifying Sky and Chain: A Perspective on Blockchain's Role i...

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2nd International conference on Artificial Intelligence, Blockchain, and Internet of Things, AIBThings 2024

作者： Phadke, Abhishek Sekharan, Chandra N Vasudeva, Karthik Kumar Kar, Dulal Christopher Newport University Department of Physics Computer Science and Engineering Newport NewsVA United States Texas A&m University-Corpus Christi Department of Computer Science Corpus ChristiTX United States Texas Tech University Department of Mathematics and Statistics LubbockTX United States

ISBN: (纸本)9798331529529

UAV (Unoccupied Aerial Vehicle) swarms are coordinated agents working towards accomplishing a common goal in a dynamic environment. The nature of the environment is such that these swarms can always benefit from upgrades to their operation, behavior, and security. Incorporating blockchain technology into UAV swarms presents a transformative approach to enhancing their security, operations, and coordination. Blockchain is a decentralized ledger technology that offers a robust solution to scalability, data integrity, and trust challenges in many modern world systems. It can also be a potentially excellent method to enhance UAV swarm systems. By harnessing its security, transparency, and immutability characteristics, blockchain can offer a range of advantages to current deployments. This study categorizes the various areas of UAV swarm systems that benefit from this integration, briefly reviews current methods and architecture, and discusses three prominent case studies for integration. Thorough an examination of current trends, it is concluded that blockchain technology can significantly boost its target systems' capabilities, paving the way for advanced and reliable aerial swarm operations. © 2024 IEEE.

关键词： Blockchain

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Untangling the Knot: Breaking Access Control in Home Wireless Mesh Networks 24

Untangling the Knot: Breaking Access Control in Home Wireles...

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31st conference on computer and communications security

作者： Zhou, Xin'an Deng, Qing Pu, Juefei Man, Keyu Qian, Zhiyun Krishnamurthy, Srikanth V. Univ Calif Riverside Riverside CA 92521 USA

ISBN: (纸本)9798400706363

Home wireless mesh networks (WMNs) are increasingly gaining popularity for their superior extensibility and signal coverage compared to traditional single-AP wireless networks. In particular, there is a single gateway node and multiple extender nodes that cooperate to provide wireless coverage. We observe that there is no comprehensive research conducted on the security aspects of the control plane of such networks. For example, this decentralized architecture enables each extender node to independently authenticate wireless clients by synchronizing access control policies from the gateway node. However, this synchronization unexpectedly opens an attack surface which has not been scrutinized. In our research, we conduct an empirical study investigating devices and protocols of six popular home wireless mesh network vendors, focusing on the attack surface introduced by the access policy synchronization. Interestingly, we find that the exact protocols used to support such functionalities vary by vendors, despite the existence of the EasyMesh standard that vendors could opt-in. Furthermore, we find a number of serious security flaws, including but not limited to malicious clients retaining their network access indefinitely and direct compromises of gateway and extender nodes in some cases. These issues arise due to the lack of coordination across different layers of protocols that work together to support the control plane. We reported all of our findings to the affected vendors and they have acknowledged the issues and are working towards fixes (most of the vendors have released patches). Finally, we discuss trade-offs in different existing designs, suggest alternative solutions, and summarize lessons learned from the research.

关键词： Wireless mesh network Wi-Fi 802.11 security protocols

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Vulnerability Analysis and Exploitation Attacks on Smart Wearable Devices 2

Vulnerability Analysis and Exploitation Attacks on Smart Wea...

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2nd International conference on Advancement in Computation and computer Technologies, InCACCT 2024

作者： Khan, Shujahat Ali Bajwa, Hasan Raza Sundaram, Jawahar Pritika Shanmugam, Bharanidharan Energy and Resources Institute Faculty of Science and Technology Charles Darwin University Darwin Australia Christ Academy Institute for Advanced Studies Department of Computer Science and Applications Bengluru India

ISBN: (纸本)9798350371314

Wearable devices are becoming more popular these days due to its unique features and its effectiveness. The evolution of Internet of Things (IoT) that combined health care devices and sensors has entirely changed the scenario in the healthcare infrastructure. This innovation will confidently improve the existing healthcare facilities and practices due to the continuous observing of patient's health even in the remote places. Regardless of their effectiveness, IoT devices are insecure and are vulnerable to security threats that should need to be overcome. The main issue is to protect from outside entities or attacks that may obstruct the advancement and put the individual's information at risk. This study focuses on outlining the vulnerabilities focusing on smartwatches in the healthcare IoT domain. Furthermore, it has been observed that a limited Bluetooth Low Energy (BLE) based smartwatches has a very weak or no security defense system making these devices vulnerable to various security threats such as Brute-force attacks, Man-in-The-Middle (MiTM) attacks, Denial of Service (DoS) attacks, and Phishing. Experimental testing has been performed to test the vulnerabilities in smartwatch devices to verify the data integrity concerns. By using Bluetooth sniffing tools, the security of the smart wearable devices has been tested to identify its weaknesses and to target the BLE devices. Attempts have been made to tamper its parameters by gaining access to the devices through Bluetooth connection. The overall result reveals that these devices are vulnerable to different exploits. This study provides the foundation to assess possible vulnerabilities in smart wearable devices. Furthermore, it highlights the loopholes existed in these devices which can be exploited. © 2024 IEEE.

关键词： Bluetooth

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Decentralized Network for Cloud Storage 2

Decentralized Network for Cloud Storage

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2nd Edition of IEEE Delhi Section Owned conference, DELCON 2023

作者： Chirag, N. Kshitij, K. Gupta, Gaurav Sir M Visvesvaraya Institute of Technology Dept. of Information Science Engineering Bangalore India Shoolini University Yogananda School of Artificial Intelligence Computer and Data Sciences H.P Solan India

ISBN: (纸本)9798350322064

The amount of data loss on corporate servers in cloud environments has increased significantly. In the cloud, there are many security compromises and account hijackings, resulting in severe vulnerabilities for the service. Cloud computing is one of the most popular on-demand services. Over the past decade, cloud computing has been incorporated into various industries, including health care and the military. security has, however, been a major concern with cloud computing. There have been many approaches and security implications implemented. However, when it comes to the security and privacy of data, there are loopholes. By decentralizing the cloud, which is currently a centralized entity, the authors attempt to improve cloud security. It is possible to solve these problems by deploying a decentralized cloud. Client software encrypts, fragments data, and then a client engine distributes the data among a number of hosting nodes (servers) spread throughout the world. As a result, the user has complete ownership of his data. In their study, the authors found that decentralizing cloud solved most of the problems of centralized cloud, since it increases the security of data by fragmenting and encrypting fragments. © 2023 IEEE.

关键词： Cloud security

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Smart Emergency Alerting System: A Machine Learning Approach 24

Smart Emergency Alerting System: A Machine Learning Approach

引用

2nd International conference on communications, Computing and Artificial Intelligence, CCCAI 2024

作者： Alrowaily, Majed Abdullah Department of Computer Science College of Computer and Information Sciences Jouf University Sakaka72341 Saudi Arabia

ISBN: (纸本)9798400716898

Recently, Saudi Arabia has hosted significant sports and technology events. Saudi Arabia has also successfully secured the bid to host Expo 2030 and declared its intention to host the FIFA World Cup in 2034. These crowds pertain to the elderly and special needs groups, which constitute the most vulnerable category in general, and they usually require some form of assistance. This study proposes a framework that integrates beacon technology with deep learning and real-time camera feed analysis to help crowds with special needs request emergency assistance by training a prioritization model for a patient based on this labeled dataset of 6962 records that consists of demographic and clinical details. In this, the random forest gives a nearly perfect classification and is the most successful model compared to the logistic regression and the SVM models. Logistic regression and the SVM model were not good with the minority classes. Once again, the model has been used by the application of that integrated application, and the result will be better in giving more priority to the medical emergency request and making a sound response. Another disadvantage could be, for example, accuracy in GPS coordinates, illumination conditions, and crowd density in indoor situations. © 2024 acm.

关键词： Decision trees

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Research on inconsistent consecutive DNS responses from DNS resolvers 2

Research on inconsistent consecutive DNS responses from DNS ...

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2nd Asia-Pacific conference on communications Technology and computer Science, ACCTCS 2022

作者： Li, Lengwenting Liu, Yang Lu, Keyu Li, Chao Zhang, Zhaoxin Harbin Institute of Technology Faculty of Computing Harbin China

ISBN: (纸本)9781665400343

As the core infrastructure of the Domain Name System (DNS), DNS resolvers play a vital role on the Internet. DNS responses are used for message transmission between DNS resolvers and clients. Their correctness and normalization directly affect whether clients can access the Internet safely and accurately. Therefore, the research on DNS responses returned by DNS resolvers is significant to ensure Internet security. We found that when some DNS resolvers received multiple consecutive identical DNS queries, they returned DNS responses with inconsistent headers. We believe that research on this phenomenon can provide a more comprehensive understanding of the behavior of DNS resolvers. This paper proposes a method to comprehensively discover the phenomenon by collecting and analyzing the DNS responses. In addition, this paper also proposes a method to verify our two speculations about the reasons for the phenomenon. The experimental results confirmed the credibility of one of the speculations that a specific configuration of the DNS resolvers caused them to add header sections with a specific meaning when responding to the DNS queries from the cache. © 2022 IEEE.

关键词： computer science Internet security communications technology Behavioral sciences IP networks Servers security

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Anomaly-Based Intrusion Detection in Network Traffic using Machine Learning: A Comparative Study of Decision Trees and Random Forests 2

Anomaly-Based Intrusion Detection in Network Traffic using M...

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2nd IEEE International conference on Networking and communications, ICNWC 2024

作者： Sah, Anil Kumar Venkatesh, K. SRM Institute of Science and Technology Department of Networking and Communications Chennai India

ISBN: (纸本)9798350365269

With advancements in information and virtualization technologies, the volume and growth of security threats from cyber attacks targeting networked systems are increasing. Protecting these networked systems is crucial in today's interconnected digital world. Detecting anomalies in network behavior is crucial to preventing fraud or unauthorized access and ensuring the integrity of data transmission over the internet. This highlights the crucial role of intrusion detection systems (IDS) in network security by identifying malicious attacks in network traffic. However, relying solely on data encryption, authentication, and firewalls isn't always sufficient, especially when dealing with fragmented packets that evade traditional security measures. Moreover, attackers are adept at adapting their tactics, making it increasingly challenging to stay ahead of potential threats. This study examines Anomaly-Based Intrusion Detection in Network Traffic utilizing machine learning methods such as Decision Trees and Random Forests leveraging the MachineLearningCSV data of the CICIDS-2017 dataset from ISCX Consortium to test and compare how well these two multiclass classifier algorithms work. Out of 79 features, including one feature as a label, 50 were obtained from the feature engineering step. The detection accuracy and F1 score of more than 99% were achieved using both Decision Tree and Random forest algorithms at a split ratio of 80:20. The results of two algorithms are compared, and it is observed from the ROC that the Random Forest algorithm is more effective than the Decision Tree for the multiclass classification. Additionally, the Decision Tree classifier achieved an accuracy score of 0.99867 with an execution time of 44.3 seconds, while the Random Forest classifier achieved an accuracy score of 0.99888 with an execution time of 8 minutes and 35 seconds. These results demonstrate the effectiveness of both algorithms in achieving high accuracy in intrusion detection tasks, w

关键词： Decision trees

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On the Detectability of ChatGPT Content: Benchmarking, Methodology, and Evaluation Through the Lens of Academic Writing 24

On the Detectability of ChatGPT Content: Benchmarking, Metho...

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31st conference on computer and communications security

作者： Liu, Zeyan Yao, Zijun Li, Fengjun Luo, Bo Univ Kansas EECS I2S Lawrence KS 66045 USA

ISBN: (纸本)9798400706363

With ChatGPT under the spotlight, utilizing large language models (LLMs) to assist academic writing has drawn a significant amount of debate in the community. In this paper, we aim to present a comprehensive study of the detectability of ChatGPT-generated content within the academic literature, particularly focusing on the abstracts of scientific papers, to offer holistic support for the future development of LLM applications and policies in academia. Specifically, we first present GPABench2, a benchmarking dataset of over 2.8 million comparative samples of human-written, GPT-written, GPT-completed, and GPT-polished abstracts of scientific writing in computer science, physics, and humanities and social sciences. Second, we explore the methodology for detecting ChatGPT content. We start by examining the unsatisfactory performance of existing ChatGPT detecting tools and the challenges faced by human evaluators (including more than 240 researchers or students). We then test the hand-crafted linguistic features models as a baseline and develop a deep neural framework named CheckGPT to better capture the subtle and deep semantic and linguistic patterns in ChatGPT written literature. Last, we conduct comprehensive experiments to validate the proposed CheckGPT framework in each benchmarking task over different disciplines. To evaluate the detectability of ChatGPT content, we conduct extensive experiments on the transferability, prompt engineering, and robustness of CheckGPT.

关键词： AIGC Detection Responsible AI Large Language Models

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Telehealth Data security and Privacy Solutions for Sensitive Health Records using Cloud Computing and Isolation Forest Algorithm 2

Telehealth Data Security and Privacy Solutions for Sensitive...

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2nd International conference on Self Sustainable Artificial Intelligence Systems, ICSSAS 2024

作者： Prathik, A. Banu, S. Parveen Sagar, B.S. Prakash, A. John Felix Thamizhamuthu, R. Velmurugan, S. Vel Tech Rangarajan Dr.Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Tamil Nadu Chennai India Saveetha College of Liberal Arts and Sciences Department of Commerce Tamil Nadu Chennai India Reva University Department of Electrical and Electronics Engineering Karnataka Bengaluru India Chennai Institute of Technology Department of Computer Science and Engineering Tamil Nadu Chennai India Srm Institute of Science and Technology Department of Computing Technologies Kattankulathur Campus-Chengalpattu Tamil Nadu Chennai India T.J.S. Engineering College Department of Electronics and Communication Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350368413

Protecting the confidentiality of patient's personal health information as it is sent and kept in the cloud is of the utmost importance due to the increasing number of telehealth services. This research provides a new healthcare data security approach using cloud computing and the Isolation Forest method. To identify important challenges and provide a novel technique, a thorough literature study on telehealth security, privacy issues, and cloud-based solutions. It uses the Isolation Forest method for anomaly detection in combination with encryption and access restriction systems to identify intrusion attempts. It uses simulated telehealth data in trials to test the system's work. Findings show substantial gains in privacy and data security with computational burden. Healthcare practitioners and legislators will find results useful in their pursuit of solutions to the problem of securing patients' private health information throughout the rise of telemedicine. © 2024 IEEE.

关键词： Electronic health record

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2nd International conference on Algorithms, Network and computer Technology

2nd International Conference on Algorithms, Network and Comp...

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2nd International conference on Algorithms, Network and computer Technology, ICANCT 2023

The proceedings contain 16 papers. The topics discussed include: a design pattern of IAPVS platform based on distributed edge computing;side-channel attack security risk assessment model based on mutual information game;research and application of power grid data anomaly tracing method based on time series correlation;military unmanned equipment image target recognition method based on improved deep learning;analysis of the influence of adjacent new pile foundation construction on the structural deformation of the in-service subway tunnels;a numerical study on smoke propagation in metro tunnel fires with different door opening scenarios;effect of door openings on train fire scenarios within a subway depot;numerical simulation study on the embedding depth of anti-slip piles in fully weathered granite landslides;analysis and optimization of brace system in scaffold;and an intelligent fault diagnosis method that combines operating condition attribute encoding and multi-scale cascading concept.

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