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检索条件"任意字段=Proceedings of the 5th ACM Conference on Data and Application Security and Privacy"

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the First Early Evidence of the Use of Browser Fingerprinting for Online Tracking 25

The First Early Evidence of the Use of Browser Fingerprintin...

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34th acm Web conference, WWW 2025

作者： Liu, Zengrui Dani, Jimmy Cao, Yinzhi Wu, Shujiang Saxena, Nitesh Nanjing University of Finance and Economics Nanjing China Texas A&M University College StationTX United States Johns Hopkins University BaltimoreMD United States F5.Inc SeattleWA United States

ISBN: (纸本)9798400712746

While advertising has become commonplace in today’s online interactions, there is a notable dearth of research investigating the extent to which browser fingerprinting is harnessed for user tracking and targeted advertising. Prior studies only measured whether fingerprinting-related scripts are being run on the websites but that in itself does not necessarily mean that fingerprinting is being used for the privacy-invasive purpose of online tracking because fingerprinting might be deployed for the defensive purposes of bot/fraud detection and user authentication. It is imperative to address the mounting concerns regarding the utilization of browser fingerprinting in the realm of online advertising. this paper introduces "FPTrace" (fingerprinting-based tracking assessment and comprehensive evaluation framework), a framework to assess fingerprinting-based user tracking by analyzing ad changes from browser fingerprinting adjustments. Using FPTrace, we emulate user interactions, capture ad bid data, and monitor HTTP traffic. Our large-scale study reveals strong evidence of browser fingerprinting for ad tracking and targeting, shown by bid value disparities and reduced HTTP records after fingerprinting changes. We also show fingerprinting can bypass GDPR/CCPA opt-outs, enabling privacy-invasive tracking. In conclusion, our research unveils the widespread employment of browser fingerprinting in online advertising, prompting critical considerations regarding user privacy and data security within the digital advertising landscape. © 2025 Copyright held by the owner/author(s).

关键词： Sensitive data

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Analysis of Information Quality and data security in the KPU (General Elections Commission) SIDALIH (Voter data Information System) application 5th

Analysis of Information Quality and Data Security in the KPU...

引用

5th International conference on HCI for Cybersecurity, privacy and Trust, HCI-CPT 2023, held as part of the 25th International conference on Human-Computer Interaction, HCII 2023

作者： Raharja, Jaka Nurmandi, Achmad Misran Subekti, Dimas Department of Government Affairs and Administration Yogyakarta Muhammadiyah University Yogyakarta Indonesia Department of Government Affairs and Administration Jusuf Kalla School of Government Muhammadiyah University Yogyakarta Indonesia

ISBN: (纸本)9783031358210

the purpose of this study was to determine the quality of services provided and data security in the use of the KPU’s SIDALIH (Voter data Information System) application. this research uses qualitative methods by analyzing online news media. the news is collected using the NCapture feature and then the Nvivo 12 plus software is used to manage and analyze the data. the results show that the accurate indicator in the SIDALIH application service has the highest percentage of 33.33%, then the relevant indicator with a percentage of 29.17%, the completeness indicator with a percentage of 22.92%, and the timeliness indicator with a percentage of 14.58%. Infrastructure indicators have a percentage of 53.33% and management indicators have a percentage of 46.67%. the SIDALIH application can provide accurate information, but the delivery of information on the SIDALIH application takes time to be accessed. security infrastructure needs to be improved so that it is not easy to be hacked and it is necessary to establish guidelines, rules, and task forces that play a role in tackling information technology disasters or data leaks. the limitation of this research is that the data obtained is only from online news media, so it still needs to be explored further regarding its truth and legitimacy. the findings in this study can be used as a reference for improving the quality of information and guaranteeing the security of user data in the future. © 2023, the Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Information systems

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A homomorphic encryption-based leakage prevention method for cross-domain circulation of sensitive network data 5

A homomorphic encryption-based leakage prevention method for...

引用

5th International conference on Computer Communication and Network security, CCNS 2024

作者： Bao, Liang Li, Zhiqi Luo, Fucai Sun, Wangshu Yang, Yang The Third Research Institute of Ministry of Public Security Pudong New Area Shanghai200120 China Co. Ltd. Changping District Beijing102200 China State Grid Fujian Electric Power Co. Ltd. Fujian Fuzhou350001 China State Grid Zhejiang Electric Power Co. Ltd. Zhejiang Hangzhou311500 China

ISBN: (纸本)9781510681842

After the application of anti leakage methods, it is easy to re encrypt, resulting in poor anti leakage performance of data flow across domains. therefore, it is necessary to design a new cross domain cyclic anti leakage method for sensitive network data based on homomorphic encryption. We have constructed a model for cross domain flow and leakage prevention of sensitive data, and designed a cross domain flow and leakage prevention algorithm for sensitive network data using homomorphic encryption, thereby achieving cross domain flow and leakage prevention of data. the experimental results show that the designed anti leakage method for cross domain data flow has high accuracy and detection rate, as well as low false positive rate, false negative rate, memory consumption, and CPU execution time. this proves that the method has good performance, reliability, and certain application value, and has made a certain contribution to reducing the security risk of sensitive data transmission. © 2024 SPIE.

关键词： Information leakage

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Virtual Board based data Sharing application Using Cloud Computing 5

Virtual Board based Data Sharing Application Using Cloud Com...

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5th IEEE International conference on Advances in Computing, Communication Control and Networking, ICAC3N 2023

作者： Gupta, Meenu Kumar, Rakesh Kumar, Abhishake Chaurasia, Prateek Chandigarh University Department Of Cse Punjab Mohali India

ISBN: (纸本)9798350330861

the concept of cloud computing becomes the more popular solution for managing data in recent years. Cloud computing provides several other advantages over traditional on-premises databases along with the ability to store and access data through the internet. this review is about the Virtual Board System, which is a cloud-based Android application that aims to enhance data management and file handling. In today's fast-paced world, managing and tracing data is a tedious task that consumes a lot of time. thus, this paper presents the Virtual Board System, which offers an easy-to-use platform with a predefined process for logging and searching through old files. Virtual Board was developed to address the challenges faced by students and professionals in managing large volumes of data efficiently. By utilizing skills in computer engineering and combining them with consulting services, a user-friendly application has been created that stores records safely in a cloud database. the system is designed to minimize threats of data loss and record misplacement by providing encrypted data to both sides in a more organized form under privacy policies. Hence, this research paper focuses on developing and optimizing the Virtual Board System, which provides a reliable and efficient way to handle and manage data. © 2023 IEEE.

关键词： Optimization

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Secure data Transmission Based on Artificial Intelligence Using IoT in security Systems 5

Secure Data Transmission Based on Artificial Intelligence Us...

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5th IEEE International conference on Computing, Power, and Communication Technologies, IC2PCT 2024

作者： Senthil Kumar, S. Maruthaveni, R. Jayanthi, N. Yadav, Ajay Kumar Kalaiarasan, T.R. Sri Ramakrishna Mission Vidyalaya College of Arts and Science Department of Information Technology Coimbatore India Dr.S N S Rajalakshmi College of Arts and Science Department of Computer Science Coimbatore India Deemed to Be University Periyar Maniammai Institute of Science and Technology Department of Commerce Thanjavur India United Institute of Management Department of Computer Application U.P. Prayagraj India Sri Krishna College of Engineering and Technology Dept of Information Technology Coimbatore India

ISBN: (纸本)9798350383522

the Internet of things (IoT), a rapidly expanding and constant technology today, enables the efficient exchange of information and control of electronic equipment. As technology grows more and more integrated into our daily lives, IoT serves as a bridge between human intelligence and artificial intelligence. Although the Internet of things (IoT) presents numerous benefits for efficiency and creativity, it also poses serious privacy and security concerns. the main topic of the research is the enormous challenges in protecting IoT environments caused by the sheer number and variety of connected devices. this study's main goal is to look into how machine learning methods may be used to lessen the ongoing security vulnerabilities in IoT environments. We intend to create more resilient and intelligent security systems that can adapt to the changing threat environment by utilising machine learning's capabilities. the proposed study provides a thorough examination of the various elements and traits that make up IoT systems, with a focus on the current security measures. By taking a look at these elements, we may determine which strategies and techniques stand the highest chance of improving IoT security. this makes it possible for IoT deployments to be safer and more dependable in a technological setting that is quickly changing. © 2024 IEEE.

关键词： Camera Drowsiness Eye Face detection Hardware device Opencv Python

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Enhanced Agricultural Decision-Making: Merging Climatic data with Machine Learning Algorithms 5

Enhanced Agricultural Decision-Making: Merging Climatic Data...

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5th International conference on data Intelligence and Cognitive Informatics, ICDICI 2024

作者： Rathi, Snehal Wamanacharya, Shubham Shah, Samkit Khedkar, Vijayshri BTACT'S Vishwakarma Institute of Information Technology Department of Computer Engineering Pune India Symbiosis Institute of Technology Department of Computer Science & Engineering Pune India

ISBN: (纸本)9798350389609

Climate change still implies risks for economic security, such as for agriculture and its productivity and, therefore, national economic potential. Although similar approaches have been used in publications concerning individual crops or soil types, the application of climatology parameters in agriculture and it limited indices have not been optimal. Owing to the recognized limitations of traditional linear productivity models, this thesis subjects' agricultural productivity to a Cobb-Douglas multi-factorial modeling approach through intensive levels of data decomposition. the proposed approach enabled the researchers to adjust the impact of climate parameters during students' evaluations in the secondary education curricula. Additionally, frameworks which relate temperature variations and crop growth do exist, and therefore the temperature and agriculture performance model effects determinants were determined using complex analysis of temperature relations and crop outputs. this highlights the various factors affecting production, its structure, and the relative importance of some conditions in agriculture and explains their dynamics depending on the changes in growth factors. Hence, a set of factors employed in the modeling resulted mainly from economic conditions, production system structures and advanced agricultural technology applications in the economy as prediction © 2024 IEEE.

关键词： Agricultural data Analysis Climate Impact on Agriculture Crop Growth Days Growth Degree Days (GDD) R Programming

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Experimental Evaluation of Blockchain Based Drug Supply Chain Management System to Ensure Transparency and Traceability 5

Experimental Evaluation of Blockchain Based Drug Supply Chai...

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5th International conference on Sustainable Communication Networks and application, ICSCNA 2024

作者： Manoharan, Jayapreethi Suguna, T. Ahmed, Shakeb Patnaik, K.G.K. Gopinath, D. Penyameen, K. Saveetha School of Law Saveetha Institute of Medical and Technical Sciences Chennai77 India Vignans Institute of Engineering for women Department of management studies Andhrapradesh India MGVs Arts Commerce and Science College Maharashtra Malegaon India Department of Management Studies Visakhapatnam India Department of Computer Science Karnataka Bengaluru India Velammal College of Engineering and Technology Madurai India

ISBN: (纸本)9798331530013

the pharmaceutical industry faces significant challenges in maintaining the transparency and traceability of drugs throughout the supply chain, leading to issues such as counterfeit drugs and inefficiencies in drug distribution. this study proposes a blockchain-based drug supply chain management system designed to ensure enhanced transparency, traceability, and security. By integrating Hyperledger blockchain with IoT sensors and smart contracts, the system provides real-time tracking of drug shipments and automates key processes, reducing the risk of human error and improving compliance with regulatory standards. the proposed model was benchmarked against nine existing models, demonstrating superior performance across several key metrics. the model achieved an accuracy of 97.1%, the highest among the evaluated systems, indicating its robustness in detecting anomalies and maintaining data integrity. Additionally, the model exhibited the lowest energy consumption of 3.8 J/transaction and the highest data integrity score of 9.8. these results highlight the model's efficiency, scalability, and reliability, making it a promising solution for the pharmaceutical industry's supply chain challenges. © 2024 IEEE.

关键词： data integrity

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Query Method of Multi-Source data in Distribution Network 5

Query Method of Multi-Source Data in Distribution Network

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5th International conference on Decision Science and Management, ICDSM 2023

作者： Huang, Lei Tian, Hanlin Yang, Daixi Mao, Xiaoyi Long, Li Tongren Power Supply Bureau of Guizhou Power Grid Co. Ltd Guizhou China

ISBN: (纸本)9798350325010

this paper provides a query method and system for multi-source data, which belongs to the database field, including receiving data access requests from business applications, forwarding the access requests to the data access component, which judges the transfer parameters in the access request;When the judgment result indicates that the data access is a cross-database data request, the data access request is forwarded to the distributed data query engine;Connect to the multiple data sources corresponding to the data access request, obtain the query results corresponding to the data access request from the multiple data sources, and forward the query results to the data access component, so that the data forwarding component can send the query results to the business application. Establish a logical database to isolate the direct connection between business applications and databases, thus improving the security of data access;Provide abstract development services to simplify data management and application development;Support the associated query between tables that physically cross databases, and realize the multi-source data query across databases. © 2023 IEEE.

关键词： Information management

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Preventing Fraud in E-tickets Validation Using the 2FA Approach 5

Preventing Fraud in E-tickets Validation Using The 2FA Appro...

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5th International conference on Computer and applications, ICCA 2023

作者： Alnuaimi, Lolwa Hassan Jaam, Jihad Al John Moores University School of Computing and Data Sciences Dept. of Computer Science Oryx Universal College in Partnership with Liverpool Doha Qatar

ISBN: (纸本)9798350303254

Electronic ticketing (e-ticket) systems employing QR codes or barcodes are essential in the digital era but come with cybersecurity risks like fraud, counterfeiting, and ticket scalping. this study explores the cybersecurity implications of large-scale event e-ticketing, with a focus on comprehending these technologies and improving security. It introduces the Ticket_Events application, which combines online registration and the secure generation of QR-coded electronic tickets. the app mandates QR code scanning at the event venue and encourages the use of location services for enhanced verification, preventing ticket swapping and potential fraud. the primary objective is to create a dependable e-ticketing application centered on ownership verification. In conclusion, the study delves into the intricacies of e-ticketing and barcode scanning, pinpoints challenges, and proposes solutions to fortify the security of digital ticket delivery. © 2023 IEEE.

关键词： Bar codes

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application of Machine Learning Techniques for Heavy Rainfall Prediction using Satellite data 5

Application of Machine Learning Techniques for Heavy Rainfal...

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5th International conference on Smart Electronics and Communication, ICOSEC 2024

作者： Balram, Gujjari Poornachandrarao, N. Ganesh, D. Nagesh, Banavath Basi, Reddy.A Kumar, M.Sunil Anurag University Ghatkesar Rd Venkatapur Telangana Hyderabad500088 India Geethanjali College of Engineering and Technology Hyderabad Telangana Cheeryal India Andhra Pradesh Tirupati India Marri Laxman Reddy Institute of Technology and Management Department of Cyber Security Hyderabad Telangana Dundigal500043 India

ISBN: (纸本)9798331504403

this study presents a large-scale lunar dataset with the goal of utilizing machine learning techniques to forecast periods of intense rain. the dataset includes features from the lunar surface such as slope, height and depth of craters, types of boulders, patterns of distribution, and the presence of shadows. the study uses well-known machine learning techniques Random Forest, AdaBoost, Support Vector Machine (SVM), and k-Nearest Neighbors (KNN), with an emphasis on the Heavy Rain Prediction target variable, which indicates the chance of heavy rain events (Yes/No). In order to provide insights into efficient heavy rain event prediction on the moon's surface, the algorithms are trained and assessed to identify patterns and linkages within the lunar dataset. the results further lunar exploration plans and provide useful recommendations for planning lunar missions and safety precautions against potentially unfavorable weather circumstances. © 2024 IEEE.

关键词： Rain

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