Enhancing Data Privacy: A Comprehensive Survey of Privacy-Enabling Technologies

被引:0
|
作者
Razi, Qaiser [1 ]
Piyush, Raja [2 ]
Chakrabarti, Arjab [2 ]
Singh, Anushka [2 ]
Hassija, Vikas [2 ]
Chalapathi, G. S. S. [1 ]
机构
[1] Birla Inst Technol & Sci BITS Pilani, Dept Elect & Elect Engn, Pilani Campus, Pilani 333031, Rajasthan, India
[2] Kalinga Inst Ind Technol KIIT, Sch Comp Engn, Bhubaneswar 75102, Odisha, India
来源
IEEE ACCESS | 2025年 / 13卷
关键词
Data privacy; Privacy; Information integrity; Information filtering; Encryption; Synthetic data; Differential privacy; Surveys; Bayes methods; Protection; Privacy engineering; data anonymization; data encryption; synthetic data; differential privacy; privacy preservation; privacy technologies; DIFFERENTIAL PRIVACY; TARGET CLASSIFICATION; MANAGEMENT SCHEME; DE-ANONYMIZATION; BIG DATA; ENCRYPTION; UTILITY; MICROAGGREGATION; ALGORITHM; EFFICIENT;
D O I
10.1109/ACCESS.2025.3546618
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Privacy is a fundamental human right, especially crucial in our modern digital age. With the rapid advancement of technology, ensuring individuals' privacy has become increasingly complex. Our survey paper aims to shed light on various privacy engineering technologies that play a crucial role in protecting personal data. We delve into four key areas: data anonymization, data encryption, synthetic data generation, and differential privacy. These technologies serve as essential tools in safeguarding online privacy. Data anonymization, for instance, includes removing or modifying identifiable information from datasets to protect individuals' identities. Encryption secures data by converting it into a code that can only be decoded by authorized parties. Synthetic data generation creates artificial data that closely resembles real data but doesn't contain any identifiable information. Differential privacy adds a small amount of controlled noise to protect sensitive information. Throughout our exploration, we not only explain the principles and techniques behind these technologies but also the tools used for each of these techniques and evaluation criteria and also examine their practical applications. By understanding their strengths, limitations, and real-world implementations, we gain valuable insights into how they contribute to the broader goal of ensuring privacy in our digital world.
引用
收藏
页码:40354 / 40385
页数:32
相关论文
共 50 条
  • [1] PaDS: An adaptive and privacy-enabling Data Pipeline for Smart Cars
    Li, Yunxuan
    Stach, Christoph
    Mitschang, Bernhard
    PROCEEDINGS OF THE 2024 25TH IEEE INTERNATIONAL CONFERENCE ON MOBILE DATA MANAGEMENT, MDM 2024, 2024, : 41 - 50
  • [2] Privacy-Enabling Social Networking Over Untrusted Networks
    Anderson, Jonathan
    Diaz, Claudia
    Bonneau, Joseph
    Stajano, Frank
    2ND ACM SIGCOMM WORKSHOP ON ONLINE SOCIAL NETWORKS (WOSN 09), 2009, : 1 - 6
  • [3] A survey of privacy enhancing technologies for smart cities
    Curzon, James
    Almehmadi, Abdulaziz
    El-Khatib, Khalil
    PERVASIVE AND MOBILE COMPUTING, 2019, 55 : 76 - 95
  • [4] Privacy enhancing technologies for solving the privacy-personalization paradox: Taxonomy and survey
    Kaaniche, Nesrine
    Laurent, Maryline
    Belguith, Sana
    JOURNAL OF NETWORK AND COMPUTER APPLICATIONS, 2020, 171
  • [5] Privacy enhancing technologies
    Ivan, Szekely
    INFORMACIOS TARSADALOM, 2008, 8 (01): : 20 - +
  • [6] Public Private Data Partnerships enabling Privacy Technologies
    Anant, Aaloka
    Prasad, Ramjee
    2022 25TH INTERNATIONAL SYMPOSIUM ON WIRELESS PERSONAL MULTIMEDIA COMMUNICATIONS (WPMC), 2022,
  • [7] Privacy-Enabling Framework for Cloud-Assisted Digital Healthcare Industry
    Ansari, Aman Ahmad
    Mishra, Bharavi
    Gera, Poonam
    Khan, Muhammad Khurram
    Chakraborty, Chinmay
    Mishra, Dheerendra
    IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2022, 18 (11) : 8316 - 8325
  • [8] PrimeLife Checkout - A Privacy-Enabling e-Shopping User Interface
    Koenig, Ulrich
    PRIVACY AND IDENTITY MANAGEMENT FOR LIFE, 2011, 352 : 325 - 337
  • [9] Privacy-Enhancing Face Biometrics: A Comprehensive Survey
    Meden, Blaz
    Rot, Peter
    Terhoerst, Philipp
    Damer, Naser
    Kuijper, Arjan
    Scheirer, Walter J.
    Ross, Arun
    Peer, Peter
    Struc, Vitomir
    IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, 2021, 16 : 4147 - 4183
  • [10] Comprehensive Survey on Big Data Privacy Protection
    Binjubeir, Mohammed
    Ahmed, Abdulghani Ali
    Bin Ismail, Mohd Arfian
    Sadiq, Ali Safaa
    Khan, Muhammad Khurram
    IEEE ACCESS, 2020, 8 : 20067 - 20079