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Journal articles on the topic 'Data security and Data privacy'

Author: Grafiati

Published: 1 June 2024

Last updated: 31 July 2025

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1

Yerbulatov, Sultan. "Data Security and Privacy in Data Engineering." International Journal of Science and Research (IJSR) 13, no. 4 (2024): 232–36. http://dx.doi.org/10.21275/es24318121241.

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2

Hennessy, S. D., G. D. Lauer, N. Zunic, B. Gerber, and A. C. Nelson. "Data-centric security: Integrating data privacy and data security." IBM Journal of Research and Development 53, no. 2 (2009): 2:1–2:12. http://dx.doi.org/10.1147/jrd.2009.5429044.

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3

Sandeep Agrawal, Tanay. "Blockchain Applications in Data Security and Privacy." International Journal of Science and Research (IJSR) 13, no. 12 (2024): 22–23. https://doi.org/10.21275/sr241127154835.

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4

Arjun, Mantri. "Ensuring Data Security and Privacy During Data Migration." European Journal of Advances in Engineering and Technology 6, no. 3 (2019): 111–15. https://doi.org/10.5281/zenodo.13354011.

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Data migration is a critical process for transferring data between different storage systems, formats, or computing environments, often driven by technological upgrades, cloud adoption, and organizational restructuring. Ensuring data security and privacy during this process is paramount to prevent data breaches and comply with regulatory requirements. This paper discusses comprehensive strategies, including encryption, access control, adherence to data protection regulations, and effective data governance, to mitigate risks associated with data migration. By implementing these techniques, orga

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Suleiman, James, and Terry Huston. "Data Privacy and Security." International Journal of Information Security and Privacy 3, no. 2 (2009): 42–53. http://dx.doi.org/10.4018/jisp.2009040103.

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6

Gaff, Brian M., Thomas J. Smedinghoff, and Socheth Sor. "Privacy and Data Security." Computer 45, no. 3 (2012): 8–10. http://dx.doi.org/10.1109/mc.2012.102.

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7

Adam, J. A. "Data security-cryptography=privacy?" IEEE Spectrum 29, no. 8 (1992): 29–35. http://dx.doi.org/10.1109/6.144533.

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8

S, Surya Prasad, and Gobi Natesan. "Ensuring Data Security and Privacy in Cloud Infrastructure." International Journal of Research Publication and Reviews 5, no. 3 (2024): 5012–16. http://dx.doi.org/10.55248/gengpi.5.0324.0817.

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Chadha, Jai, Amit Chadha Naveen, Shweta Shubhdarashini, Saraswati Kasi, Ritu Mishra, and Prof (Dr) Shailesh Mishra. "Privacy Paradox: Data Security in IoT-Driven Telemedicine." International Journal of Research Publication and Reviews 6, no. 4 (2025): 11603–9. https://doi.org/10.55248/gengpi.6.0425.15143.

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10

Zeel, B. Dabhi, and Kulkarni Akanksha. "Data Security in Cloud Computing." International Journal of Innovative Science and Research Technology 7, no. 12 (2023): 982–86. https://doi.org/10.5281/zenodo.7505036.

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The importance of data security has been a significant problem in information technology. Because the data is spread out all over the place in the field of technology, it becomes extremely problematic. Users' primary worries regarding cloud computing are related to data security and privacy security. Despite the fact that numerous approaches to the issue of cloud computing have been studied in academic research and clinical trials, data security and privacy protection are becoming increasingly crucial for the future use of cloud computing technology in business, industry, and government. I

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Gaikwad, Ranjana Rajiv. "Data Security and Privacy in Data Engineering." Journal of Research in Science and Engineering 6, no. 8 (2024): 1–6. http://dx.doi.org/10.53469/jrse.2024.06(08).01.

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Due to the increased amount of data, it has become a key resource for strategic decision - making, data security and privacy issues are becoming more relevant than ever. In the context of Data Engineering, where vast amounts of information are collected, processed and stored, ensuring reliable data protection and maintaining their confidentiality becomes a top priority. Effective data management involves not only their technical processing, but also a guarantee that the entire information lifecycle is accompanied by appropriate security measures. The purpose of the work is to consider such an

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12

Kapil, Gayatri, Alka Agrawal, and R. A. Khan. "Big Data Security and Privacy Issues." Asian Journal of Computer Science and Technology 7, no. 2 (2018): 128–32. http://dx.doi.org/10.51983/ajcst-2018.7.2.1861.

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Big data gradually become a hot topic of research and business and has been growing at exponential rate. It is a combination of structured, semi-structured & unstructured data which is generated constantly through various sources from different platforms like web servers, mobile devices, social network, private and public cloud etc. Big data is used in many organisations and enterprises, big data security and privacy have been increasingly concerned. However, there is a clear contradiction between the large data security and privacy and the widespread use of big data. In this paper, we hav

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Hassan, Jamal, A. Algeelani Nasir, and Al-Sammarraie Najeeb. "Advance Data-Privacy by Using Artificial Intelligence." International Journal of Computer Science and Information Technology Research 10, no. 4 (2022): 38–45. https://doi.org/10.5281/zenodo.7398762.

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<strong>Abstract:</strong> With the progression utilize of computers broadly, utilization of the information has moreover developed to a huge level. Nowadays information is collected without any reason, and each action of a machine or a human being is recorded, On the off chance that required in the future, at that point, the information will be dissected but here the address of believe emerges as the information will go through numerous stages for the investigation by distinctive parties. The information may contain a few touchy or private data which can be mutualized by the organizations inc

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14

Al-Museelem, Waleed, and Chun Lin Li. "Data Security and Data Privacy in Cloud Computing." Advanced Materials Research 905 (April 2014): 687–92. http://dx.doi.org/10.4028/www.scientific.net/amr.905.687.

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Cloud computing has led to the development of IT to more sophisticated levels by improving the capacity and flexibility of data storage and by providing a scalable computation and processing power which matches the dynamic data requirements. Cloud computing has many benefits which has led to the transfer of many enterprise applications and data to public and hybrid clouds. However, many organizations refer to the protection of privacy and the security of data as the major issues which prevent them from adopting cloud computing. The only way successful implementation of clouds can be achieved i

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15

Danish, Muhammad. "Big Data Security And Privacy." International Journal of Computer Trends and Technology 67, no. 5 (2019): 20–26. http://dx.doi.org/10.14445/22312803/ijctt-v67i5p104.

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Martucci, William C., and Jennifer K. Oldvader. "Workplace privacy and data security." Employment Relations Today 37, no. 2 (2010): 59–66. http://dx.doi.org/10.1002/ert.20299.

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Kumar.R, Dr Prasanna, Porselvan G, Prem Kumar S, and Robinlash F. "Security and Privacy Based Data Sharing in Cloud Computing." International Journal of Innovative Research in Engineering & Management 5, no. 1 (2018): 42–49. http://dx.doi.org/10.21276/ijirem.2018.5.1.9.

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18

George, Jomin, and Takura Bhila. "Security, Confidentiality and Privacy in Health of Healthcare Data." International Journal of Trend in Scientific Research and Development Volume-3, Issue-4 (2019): 373–77. http://dx.doi.org/10.31142/ijtsrd23780.

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Kumar Mittapelly, Arun. "Salesforce and GDPR Compliance: Ensuring Data Privacy and Security." International Journal of Science and Research (IJSR) 11, no. 5 (2022): 2147–53. https://doi.org/10.21275/sr220511110820.

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20

Amarendra Reddy, P., Sheikh Gouse, and P. Bhaskara Reddy. "Security and Privacy Mechanisms of Big Data." International Journal of Engineering & Technology 7, no. 4.39 (2018): 730–33. http://dx.doi.org/10.14419/ijet.v7i4.39.26264.

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Big Data advances in three key areas like storage, processing and analysis. Hadoop architecture is produced to store extensive measure of data through adaptable parallel handling with speed to get the outcomes. Organizations must guarantee that every single big data bases are resistant to security dangers and vulnerabilities. Amid data gathering, all the important security assurances, for example, continuous administration should to be satisfied. Remembering the big size of big data, Organizations should to recollect the way that overseeing such data could be troublesome and requires uncommon

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A.Vineela, A., N. Kasiviswanath, and L. Sudha Ran. "Survey on Data Security and Privacy Preserving in Big Data." International Journal of Engineering & Technology 7, no. 4.39 (2018): 734–36. http://dx.doi.org/10.14419/ijet.v7i4.39.26265.

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With the rapid growth of IT industry, big data needs the improvement in storage, computation and network field. This enhancement also brings the new security and privacy issues to the big data. The researchers are attracted towards to solve the security and privacy issues. This paper made a survey on characteristics of big data along with security issues. The traditional security methods of cloud computing are not appropriate to the big data. Privacy preserving is also one major issue in big data. This survey also provides complete study on research issues and challenges of privacy preserving

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Eghmazi, Ali, Mohammadhossein Ataei, René Jr Landry, and Guy Chevrette. "Enhancing IoT Data Security: Using the Blockchain to Boost Data Integrity and Privacy." IoT 5, no. 1 (2024): 20–34. http://dx.doi.org/10.3390/iot5010002.

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The Internet of Things (IoT) is a technology that can connect billions of devices or “things” to other devices (machine to machine) or even to people via an existing infrastructure. IoT applications in real-world scenarios include smart cities, smart houses, connected appliances, shipping, monitoring, smart supply chain management, and smart grids. As the number of devices all over the world is increasing (in all aspects of daily life), huge amounts of data are being produced as a result. New issues are therefore arising from the use and development of current technologies, regarding new appli

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23

Anil, Kumar G., and C. P. Shantala. "An extensive research survey on data integrity and deduplication towards privacy in cloud storage." International Journal of Electrical and Computer Engineering (IJECE) 10, no. 2 (2020): 2011–22. https://doi.org/10.11591/ijece.v10i2.pp2011-2022.

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Owing to the highly distributed nature of the cloud storage system, it is one of the challenging tasks to incorporate a higher degree of security towards the vulnerable data. Apart from various security concerns, data privacy is still one of the unsolved problems in this regards. The prime reason is that existing approaches of data privacy doesn't offer data integrity and secure data deduplication process at the same time, which is highly essential to ensure a higher degree of resistance against all form of dynamic threats over cloud and internet systems. Therefore, data integrity, as well

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24

Hussain, Abdulatif Ali, Ismael Khaleel, and Tahsien Al-Quraishi. "Using Data Anonymization in big data analytics security and privacy." Mesopotamian Journal of Big Data 2024 (August 10, 2024): 118–27. http://dx.doi.org/10.58496/mjbd/2024/009.

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Big Data and Analytics mean an enormous and complex collection of very diverse information, which is processed with various technologies and methods to produce and deliver useful and valuable insights. Analytics is the science of using data, or information to extract useful and actionable insights, facts and knowledge from a collection of data it could be stated that Big Data Analytics is the best thing since every commercial data system ever built, although everybody with a more optimistic vision of technology would like to take note that there is a fine line where Everything Data crosses the

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25

Mrs., M. S. Lakshmi Devi. "Privacy-Preserving Data Fragmentation and Aggregation." Journal of Scholastic Engineering Science and Management 2, no. 9 (2023): 23–30. https://doi.org/10.5281/zenodo.8311026.

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<strong>Privacy-preserving data fragmentation and aggregation techniques aim to preserve the privacy of individual data points while still allowing for the aggregation of data for analysis. This is important for applications such as medical research, where it is necessary to share data without compromising the privacy of the patients. This paper surveys the state-of-the-art in privacy-preserving data fragmentation and aggregation techniques. We discuss the different challenges that need to be addressed in this area, and we present a number of different techniques that have been proposed. We al

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26

Ali, Gholami, and Laure Erwin. "BIG DATA SECURITY AND PRIVACY ISSUES IN THE CLOUD." International Journal of Network Security & Its Applications (IJNSA) 8, no. 1 (2016): 59 to 79. https://doi.org/10.5281/zenodo.3345302.

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Many organizations demand efficient solutions to store and analyze huge amount of information. Cloud computing as an enabler provides scalable resources and significant economic benefits in the form of reduced operational costs. This paradigm raises a broad range of security and privacy issues that must be taken into consideration. Multi-tenancy, loss of control, and trust are key challenges in cloud computing environments. This paper reviews the existing technologies and a wide array of both earlier and state-ofthe-art projects on cloud security and privacy. We categorize the existing researc

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27

V, Sridhar Reddy, Jayanthi N, Sharon Rose Victor Juvvanapudi, Srinivas Bachu, and Sumalatha Madipalli. "Multi Objective Data Transformation in Hybrid Clouds Networks for Offloading Data." Scalable Computing: Practice and Experience 25, no. 5 (2024): 3691–700. http://dx.doi.org/10.12694/scpe.v25i5.3099.

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Recently hybrid cloud solutions integrating public and private cloud is proposed to address the privacy and security concerns faced by Enterprises in their data offloading decisions. In these solutions, the transformed data is kept in public cloud while transformation keys are kept in private cloud. The existing works for data transformation used in hybrid clouds does not address multiple objectives of privacy, security, fine grained access control, utility preservation for mining and data retrieval efficiency. This work proposes a multi objective data transformation technique for hybrid cloud

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28

Vijayachandran, Vipin, and Suchithra R. "Local differential privacy for data security in key value pair data." Journal of Computational Methods in Sciences and Engineering 24, no. 3 (2024): 1955–70. http://dx.doi.org/10.3233/jcm-230016.

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Data collection using local differential privacy (LDP) has mainly been studied for homogeneous data. Several data categories, including key-value pairs, must be estimated simultaneously in real-world applications, including the frequency of keys and the mean values within each key. It is challenging to achieve an acceptable utility-privacy tradeoff using LDP for key-value data collection since the data has two aspects, and a client could have multiple key-value pairs. Current LDP approaches are not scalable enough to handle large and small datasets. When the dataset is small, there is insuffic

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Kapoh, Harson, Putri Aprilyana, Yeremia Sumampow, Marsya Mailake, Farel Manimpurung, and Hafizhan Pakaya. "Data Security and Data Protection in Cloud Privacy Systems." Jurnal Syntax Admiration 5, no. 11 (2024): 4801–9. http://dx.doi.org/10.46799/jsa.v5i11.1768.

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In this modern world, the internet has become very influential in our daily lives. The Internet has many uses to solve various problems, one of which is full hardware storage, therefore the Internet provides software-based data, for example, cloud storage applications. The study aims to analyze and evaluate various data security techniques and protection methods used in the cloud computing framework, focusing on vulnerability identification, risk mitigation strategy assessment, and user security awareness improvement. In addition, this study aims to analyze data security techniques and data pr

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Kartheek, Pamarthi. "Application of Big Data Platform for Secure Sensitive Data Sharing." Journal of Scientific and Engineering Research 8, no. 7 (2021): 265–73. https://doi.org/10.5281/zenodo.15055080.

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Big data has been utilised by a variety of businesses in order to simplify the delivery of products and to improve consumer insights by utilising predictions made possible by technologies such as artificial intelligence. Big data is a field that focuses primarily on the extraction and systematic analysis of big data sets with the goal of assisting businesses in identifying patterns using this information. With the advent of Big Data, numerous businesses are able to expand their capacity to manage enormous client datasets and allow growth in a variety of functional areas. Many software corporat

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Anshu, Sharma*1 Mrs. Chitvan Gupta2 &. Mr. Mayank Deep Khare3. "ENHANCING DATA SECURITY ON CLOUD USING SPLIT TECHNIQUE." INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY 7, no. 6 (2018): 564–72. https://doi.org/10.5281/zenodo.1299131.

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Data security has consistently been a major issue in information technology. In the cloud computing environment, it becomes particularly serious because the data is located in different places even in all the globe. Data security and privacy protection are the two main factors of user’s concerns about the cloud technology. Though many techniques on the topics in cloud computing have been investigated in both academics and industries, data security and privacy protection are becoming more important for the future development of cloud computing technology in government, industry, and busin

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Smith, J. H., and JS Horne. "Data privacy and DNA data." IASSIST Quarterly 47, no. 3-4 (2023): 1–3. http://dx.doi.org/10.29173/iq1094.

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The letter to the Editor is in response to the manuscript by Hertzog et al. (2023) titled "Data management instruments to Protect the personal information of Children and Adolescents in sub-Saharan Africa." The letter elaborates on personal data protection, particularly the POPI Act's data management requirements; the DNA Act mandates specific measures to ensure the data integrity and security of the NFDD's information. In addition, it criminalises the misuse or compromise of the data's integrity within the NFDD. In addition, the DNA Act established the National Forensic Oversight and Ethical

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33

Bourvil and Levi. "Multi-Level Trust Privacy Preserving Data Mining to Enhance Data Security and Prevent Leakage of the Sensitive Data." Bonfring International Journal of Industrial Engineering and Management Science 7, no. 2 (2017): 21–25. http://dx.doi.org/10.9756/bijiems.8327.

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34

Srikanth, Kandragula. "Security and Privacy Challenges." Journal of Scientific and Engineering Research 6, no. 10 (2019): 315–17. https://doi.org/10.5281/zenodo.14050056.

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Cloud computing has revolutionized the way businesses operate, offering a paradigm shift from on-premise infrastructure to a virtualized, on-demand environment. However, security and privacy concerns remain a significant hurdle for some businesses considering cloud adoption. This white paper delves into the key challenges associated with cloud security and privacy, empowering businesses of all sizes to make informed decisions and navigate the potential risks involved. We begin by exploring the concept of data security threats in the cloud environment. Data breaches are a major concern, as clou

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Mandal, Sanjeev Kumar, Amit Sharma, Santosh Kumar Henge, Sumaira Bashir, Madhuresh Shukla, and Asim Tara Pathak. "Secure data encryption key scenario for protecting private data security and privacy." Journal of Discrete Mathematical Sciences and Cryptography 27, no. 2 (2024): 269–81. http://dx.doi.org/10.47974/jdmsc-1881.

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Cryptography, specifically encryption, plays a pivotal role in protecting data from unauthorized access. However, not all encryption methods are equally effective, as some exhibit vulnerabilities. This research proposing a novel encryption method that builds upon established techniques to enhance data security. The proposed method combines the strengths of the Festial encryption method and the Advanced Encryption Standard (AES) to create an algorithm that exhibits superior resistance against attacks. The proposed encryption method successfully mitigates vulnerabilities, demonstrating enhanced

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Yang, Jing, Lianwei Qu, and Yong Wang. "Multidomain Fusion Data Privacy Security Framework." Wireless Communications and Mobile Computing 2021 (December 20, 2021): 1–26. http://dx.doi.org/10.1155/2021/8492223.

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With the collaborative collection of the Internet of Things (IoT) in multidomain, the collected data contains richer background knowledge. However, this puts forward new requirements for the security of data publishing. Furthermore, traditional statistical methods ignore the attributes sensitivity and the relationship between attributes, which makes multimodal statistics among attributes in multidomain fusion data set based on sensitivity difficult. To solve the above problems, this paper proposes a multidomain fusion data privacy security framework. First, based on attributes recognition, cla

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Kumar, Raj, and Sushma Pal. "Data security and privacy through stenography." Global Sci-Tech 10, no. 2 (2018): 98. http://dx.doi.org/10.5958/2455-7110.2018.00017.4.

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Taitsman, Julie K., Christi Macrina Grimm, and Shantanu Agrawal. "Protecting Patient Privacy and Data Security." New England Journal of Medicine 368, no. 11 (2013): 977–79. http://dx.doi.org/10.1056/nejmp1215258.

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Yan, Zheng, Willy Susilo, Elisa Bertino, Jun Zhang, and Laurence T. Yang. "AI-driven data security and privacy." Journal of Network and Computer Applications 172 (December 2020): 102842. http://dx.doi.org/10.1016/j.jnca.2020.102842.

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40

Xiang, Yang, Man Ho Au, and Miroslaw Kutylowsky. "Security and privacy in big data." Concurrency and Computation: Practice and Experience 28, no. 10 (2016): 2856–57. http://dx.doi.org/10.1002/cpe.3796.

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41

Manikanta kumar Kakarala and Sateesh Kumar Rongali. "Data Privacy and Security in AI." World Journal of Advanced Research and Reviews 25, no. 3 (2025): 555–61. https://doi.org/10.30574/wjarr.2025.25.3.0555.

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The advancement of artificial intelligence (AI) technology has created both opportunities and risks in data protection and safeguarding. Given that numerous organizations are now employing AI systems in various industries, the goal of using data to drive innovation has never been urgent. This paper will review the relationship between AI, data privacy, and security and discuss the current issues and possible recommendations. Furthermore, this study introduces new approaches, including federated learning and homomorphic encryption, which preserve data integrity while still using the data. Using

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Bhoomi, Shukla. "DATA PRIVACY, DATA PROTECTION: "The Unprecedented Challenges of Ambient Intelligence"." Indian Journal of Law and Society I, no. 8 (2024): 25–31. https://doi.org/10.5281/zenodo.10644515.

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<strong>ABSTRACT</strong> <em>Privacy has emerged as a basic human right across the globe and in India too it has been recognized as a Fundamental Right under Article 21 of the Indian Constitution. Right to Privacy is closely related to the protection of data which in this technological and globalized world, has become very difficult to achieve. Further, violation of privacy rights by the ruling majority through discriminatory legislation has also become possible due to lack of legal protection to this Right. In India, this Right was not initially recognized as a Fundamental Right, neither any

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Suyog, Gatkal, Dhage Vinayak, Kalekar Dhanashree, and Ghadge Sanket. "Survey on Medical Data Storage Systems." International Journal of Soft Computing and Engineering (IJSCE) 11, no. 1 (2021): 44–48. https://doi.org/10.35940/ijsce.A3528.0911121.

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Nowadays digital data storage and digital communication are widely used in the healthcare sector. Since data in the digital form significantly easier to store, retrieve, manipulate, analyses, and manage. Also, digital data eliminate the threat of data loss considerably. These advantages pushing many hospitals to store their data digitally. But, as the patients reveal their private and important information to the doctor, it is very crucial to maintain the privacy, security, and reliability of the healthcare data. In this process of handling the data securely, several technologies are being use

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Mr., A. Mustagees Shaikh *., and Nitin B. Raut Prof. "INFORMATION SECURITY AND SECURE SEARCH OVER ENCRYPTED DATA IN CLOUD STORAGE SERVICES." INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY 5, no. 4 (2016): 450–53. https://doi.org/10.5281/zenodo.49753.

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Cloud computing is most widely used as the next generation architecture of IT enterprises, that provide convenient remote access to data storage and application services. This cloud storage can potentially bring great economical savings for data owners and users, but due to wide concerns of data owners that their private data may be exposed or handled by cloud providers. Hence end-to-end encryption techniques and fuzzy fingerprint technique have been used as solutions for secure cloud data storage. In this project we use searchable encryption techniques, which allows encrypted data to be searc

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45

Purnamaningsih, Sari Nur Indahty, Joko Ismono, Ichwani Siti Utami, Vernando Parlindungan, and Salma Nur Hanifah. "The Challenges of Data Privacy Laws in the Age of Big Data: Balancing Security, Privacy, and Innovation." Join: Journal of Social Science 1, no. 6 (2024): 455–65. http://dx.doi.org/10.59613/gny8bq82.

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This study explores the complexities and challenges of implementing data privacy laws in the era of big data, where security, privacy, and innovation frequently intersect. The exponential growth of data collection, driven by advancements in technology and the widespread adoption of digital services, has intensified the need for effective data privacy regulations. However, balancing the protection of individual privacy with the demands of innovation and security presents considerable challenges for policymakers. Utilizing a qualitative approach, this study employs a literature review and librar

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46

Seema, Rai, and Sharma Ashok. "Research Perspective on Security Based Algorithm in Big Data Concepts." International Journal of Engineering and Advanced Technology (IJEAT) 9, no. 3 (2020): 2138–43. https://doi.org/10.35940/ijeat.C5407.029320.

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Providing a robust security for large data is one in all the first concern for most of the researchers. This paper makes an attempt to uncover all the protection solutions associated with unstructured, structured and semi structured data. also, the main aim of this paper is to cover the information related with the several encryption algorithms used to provide confidentiality, integrity, privacy and data silos. Different algorithmic program and tools play an efficient role in playacting significant analysis on huge volume, variety of big data.

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A., Yashwanth Reddy, Krishna A., and Rakesh Chowdary M. "DESIGN AND RECTIFICATION OF PRIVACY RELATED ISSUES TOWARDS CLOUD ENVIRONMENT." International Journal of Advanced Trends in Engineering and Technology 2, no. 2 (2017): 126–29. https://doi.org/10.5281/zenodo.1034463.

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Cloud computing changed the world around us. Nowpeople are moving their data to the cloud since data is gettingbigger and needs to be accessible from many devices. Therefore, storing the data on the cloud becomes a norm. However, thereare many issues that counter data stored in the cloud startingfrom virtual machine which is the mean to share resources incloud and ending on cloud storage itself issues. In this paper,wepresent those issues that are preventing people from adoptingthe cloud and give a survey on solutions that have been done tominimize risks of these issues. For example, the data

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48

Lei Xu, Chunxiao Jiang, Jian Wang, Jian Yuan, and Yong Ren. "Information Security in Big Data: Privacy and Data Mining." IEEE Access 2 (2014): 1149–76. http://dx.doi.org/10.1109/access.2014.2362522.

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Wu, Xuanting, and Yi Chen. "Research on Personal Data Privacy Security in the Era of Big Data." Journal of Humanities and Social Sciences Studies 4, no. 3 (2022): 228–35. http://dx.doi.org/10.32996/jhsss.2022.4.3.24.

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Abstract:

Big data privacy security has become a hot research topic in contemporary society. Based on the data relevance and life-cycle in the era of big data, this paper analyzes the causes of security problems in China’s data privacy. It puts forward suggestions from three aspects to provide references for subsequent research. Based on the current research progress, this paper first sorts out the definitions of data privacy and data privacy protection, then summarizes the causes of privacy security from the perspectives of technology and management and reveals the consequences of data privacy security

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Tanvir Rahman Akash, Nusrat Jahan Sany, Lamia Akter, and Sanjida Akter Sarna. "Privacy - Preserving Technique in cybersecurity: Balancing Data Protection and User Rights." Journal of Computer Science and Technology Studies 7, no. 4 (2025): 248–63. https://doi.org/10.32996/jcsts.2025.7.3.90.

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Increasing technological complexity of cyber threats creates a major challenge between securing data privacy and maintaining potent cybersecurity practices. The paper examines privacy-protecting security methods in cybersecurity by detailing organizational approaches to defend private information throughout the cyber threat detection and mitigation process. Organizations need to establish the appropriate levels of data security because implementations that limit privacy too much threaten their security capabilities but weak protection measures create vulnerabilities to data breaches. The resea

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