Relevant bibliographies by topics / Privacy threats

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Privacy threats'

Author: Grafiati
Published: 3 June 2025
Last updated: 31 July 2025

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Journal articles on the topic "Privacy threats"

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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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Kunz, Immanuel, Konrad Weiss, Angelika Schneider, and Christian Banse. "Privacy Property Graph: Towards Automated Privacy Threat Modeling via Static Graph-based Analysis." Proceedings on Privacy Enhancing Technologies 2023, no. 2 (2023): 171–87. http://dx.doi.org/10.56553/popets-2023-0046.

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Privacy threat modeling should be done frequently throughout development and production to be able to quickly mitigate threats. Yet, it can also be a very time-consuming activity. In this paper, we use an enhanced code property graph to partly automate the privacy threat modeling process: It automatically generates a data flow diagram from source code which exhibits privacy properties of data flows, and which can be analyzed semi-automatically via queries. We provide a list of such reusable queries that can be used to detect various privacy threats. To enable this analysis, we integrate a tain
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Park, Sungchae, and Heung-Youl Youm. "Security and Privacy Threats and Requirements for the Centralized Contact Tracing System in Korea." Big Data and Cognitive Computing 6, no. 4 (2022): 143. http://dx.doi.org/10.3390/bdcc6040143.

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As COVID-19 became a pandemic worldwide, contact tracing technologies and information systems were developed for quick control of infectious diseases in both the private and public sectors. This study aims to strengthen the data subject’s security, privacy, and rights in a centralized contact tracing system adopted for a quick response to the spread of infectious diseases due to climate change, increasing cross-border movement, etc. There are several types of contact tracing systems: centralized, decentralized, and hybrid models. This study demonstrates the privacy model for a centralized cont
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Barash, C. I. "Threats to Privacy Protection." Science 318, no. 5852 (2007): 913c—914c. http://dx.doi.org/10.1126/science.318.5852.913c.

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Vemou, Konstantina, and Maria Karyda. "Requirements for private communications over public spheres." Information & Computer Security 28, no. 1 (2019): 68–96. http://dx.doi.org/10.1108/ics-01-2019-0002.

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Purpose In the Web 2.0 era, users massively communicate through social networking services (SNS), often under false expectations that their communications and personal data are private. This paper aims to analyze privacy requirements of personal communications over a public medium. Design/methodology/approach This paper systematically analyzes SNS services as communication models and considers privacy as an attribute of users’ communication. A privacy threat analysis for each communication model is performed, based on misuse scenarios, to elicit privacy requirements per communication type. Fin
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Rodrigues, Andrey, Maria Lúcia Villela, and Eduardo Feitosa. "Exploring how experienced and unexperienced professionals use a privacy threat modeling methodology." Journal on Interactive Systems 14, no. 1 (2023): 274–91. http://dx.doi.org/10.5753/jis.2023.3235.

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Online Social Networks (OSNs) have become one of the principal technological phenomena of the Web, gaining an eminent popularity among its users. With the growing worldwide expansion of OSN services, people have devoted time and effort to maintaining and manipulating their online identity on these systems. However, the processing of personal data through these networks has exposed users to various privacy threats. Consequently, new solutions need to be developed for addressing the threat scenarios to which a user is potentially exposed. In this sense, this paper proposes PTMOL (Privacy Threat
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Renee Staton, A., and Michele Kielty. "A Lurking Threat: Counselor Practices to Guard Against Cyber Threats." Journal of Mental Health Counseling 45, no. 1 (2023): 20–33. http://dx.doi.org/10.17744/mehc.45.1.02.

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As a result of shifts in global power, the growth of cyber capabilities worldwide, and the impact of COVID-19 on the increasing use of technology in varied workplaces, the potential for threat and disruption to mental health facilities is expected to increase. Counselors and their clients are vulnerable to these threats any time they share data online with each other, with third-party payers, and with allied health professionals. In fact, any private information stored digitally is potentially at risk for exploitation or theft. This current environment highlights the need for an intentional pr
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Olarinde, Mobolaji Olusola`, Akeem Adekunle Abiona, and Micheal Olalekan Ajinaja. "Adaptive and Privacy-Preserving Security for Federated Learning Using Biological Immune System Principles." Asian Journal of Computer Science and Technology 13, no. 2 (2024): 67–72. https://doi.org/10.70112/ajcst-2024.13.2.4303.

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The increasing frequency and sophistication of cyber threats pose significant challenges to the security of distributed systems handling sensitive data. Federated learning, a decentralized machine learning framework, enables collaborative model training without sharing raw data, offering privacy advantages. However, ensuring the security and resilience of federated learning systems remains a pressing concern due to potential vulnerabilities, such as data poisoning and model inversion attacks. This study aims to enhance the security of federated learning systems for website threat intelligence
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Sleem, Ahmed, and Ibrahim Elhenawy. "Enhancing Cyber Threat Intelligence Sharing through a Privacy-Preserving Federated Learning Approach." Journal of Cybersecurity and Information Management 9, no. 2 (2022): 51–59. http://dx.doi.org/10.54216/jcim.090205.

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This paper proposes a privacy-preserving federated learning approach to enhance cyber threat intelligence sharing. Cyber threats are becoming more sophisticated and are posing serious security risks to organizations. Sharing threat intelligence information can help to detect and mitigate these threats quickly. However, privacy concerns and data protection regulations hinder the sharing of sensitive information. Federated learning is a promising approach that allows multiple parties to collaborate in building a global model while preserving data privacy. We propose a framework that utilizes fed
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Sridevi Kakolu, Muhammad Ashraf Faheem, and Muhammad Aslam. "Privacy-preserving AI for cybersecurity: Balancing threat intelligence collection with user data protection." International Journal of Science and Research Archive 2, no. 2 (2021): 280–92. http://dx.doi.org/10.30574/ijsra.2021.2.2.0071.

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This paper explores the case of using privacy-preserving artificial intelligence in cybersecurity by analyzing the importance of effective threat intelligence in the conflict with potential invasions and high user data protection standards. With the increased articulation of cyber threats, AI is crucial in fortifying detection, reaction, and prevention measures for cyber threats in CSFs. However, such large-scale information feeding these systems raises many privacy issues, and hence, strong privacy preservation mechanisms that ensure user anonymity and protect the information from misuse are
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Dissertations / Theses on the topic "Privacy threats"

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BERTOLAJA, LETIZIA. "LOCATION SHARING: PRIVACY THREATS AND PROTECTION." Doctoral thesis, Università degli Studi di Milano, 2015. http://hdl.handle.net/2434/265334.

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In recent years there has been a growing increase in the number of users that use smartphones,tablets, wearable technologies and other devices that users have with them constantly. The capability of these latest generation mobile devices to detect the position of the users has led to the emergence of ad-hoc services as well as geo-aware social networks (GeoSN). Even if the sharing of our locations can enhance many useful services, there are several practical cases that unveil the danger of sharing location indiscriminately. For instance, let’s suppose that a user has just told everyone tha
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Bhalotiya, Anuj Arun. "Brain Computer Interface (BCI) Applications: Privacy Threats and Countermeasures." Thesis, University of North Texas, 2017. https://digital.library.unt.edu/ark:/67531/metadc984122/.

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In recent years, brain computer interfaces (BCIs) have gained popularity in non-medical domains such as the gaming, entertainment, personal health, and marketing industries. A growing number of companies offer various inexpensive consumer grade BCIs and some of these companies have recently introduced the concept of BCI "App stores" in order to facilitate the expansion of BCI applications and provide software development kits (SDKs) for other developers to create new applications for their devices. The BCI applications access to users' unique brainwave signals, which consequently allows them t
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Spolaor, Riccardo. "Security and Privacy Threats on Mobile Devices through Side-Channels Analysis." Doctoral thesis, Università degli studi di Padova, 2018. http://hdl.handle.net/11577/3426796.

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In recent years, mobile devices (such as smartphones and tablets) have become essential tools in everyday life for billions of people all around the world. Users continuously carry such devices with them and use them for daily communication activities and social network interactions. Hence, such devices contain a huge amount of private and sensitive information. For this reason, mobile devices become popular targets of attacks. In most attack settings, the adversary aims to take local or remote control of a device to access user sensitive information. However, such violations are n
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Schwittmann, Lorenz [Verfasser], and Torben [Akademischer Betreuer] Weis. "Privacy Threats in the Mobile Web & Social Media / Lorenz Schwittmann ; Betreuer: Torben Weis." Duisburg, 2019. http://d-nb.info/1191691373/34.

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Birgisdottir, Johanna, and Hiral Amin. "Personalized Marketing : An invasion of privacy or an approved phenomenon? An empirical study of how organizations can respond to consumers’ concern over the threats of online privacy." Thesis, Uppsala universitet, Företagsekonomiska institutionen, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-176677.

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The authors of this study analysed the increasing use of personalized marketing and consumer concerns regarding the access to personal information. The purpose was to find out how companies could react to these concerns. Several theoretical concepts were explored, such as Personal Data, Personalized Marketing, Privacy Concerns, Privacy Policies, Consumer Trust and Consumer Behaviour. Facebook Inc. was analysed as an example to address the problem. An online survey was conducted on university students and two interviews were performed with representatives from the Data Inspection Board in Swede
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Almajed, Yasser M. "A framework for an adaptive early warning and response system for insider privacy breaches." Thesis, De Montfort University, 2015. http://hdl.handle.net/2086/11129.

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Organisations such as governments and healthcare bodies are increasingly responsible for managing large amounts of personal information, and the increasing complexity of modern information systems is causing growing concerns about the protection of these assets from insider threats. Insider threats are very difficult to handle, because the insiders have direct access to information and are trusted by their organisations. The nature of insider privacy breaches varies with the organisation’s acceptable usage policy and the attributes of an insider. However, the level of risk that insiders pose d
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Varshney, Rimpu. "Towards Designing Open Secure IoT System - Insights for practitioners." Thesis, Malmö universitet, Fakulteten för teknik och samhälle (TS), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-20199.

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IoT industry is growing at a rapid pace since everyone wants to connect everything to internet in order to use various services and applications using shared data. Openness is observed as an emerging trend in IoT industry. Security & privacy of the data are very important aspects in the design and deployment of the connected devices or Internet of Things. Fast growth in number of connected devices, heterogeneity, constrained resources, privacy, software upgrades and operational environment create important security related challenges in this domain. It is difficult to address challenges even w
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Bernal, Paul Alexander. "Do deficiencies in data privacy threaten our autonomy and, if so, can informational privacy rights meet this threat?" Thesis, London School of Economics and Political Science (University of London), 2011. http://etheses.lse.ac.uk/321/.

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This thesis sets out a model to examine how the internet functions. 'The symbiotic web' suggests a symbiotic relationship between corporations that have built business models dependent upon the gathering of personal data from people, and the individuals themselves who have begun to rely on apparently 'free' services (from search to email, social networking to YouTube). Having set out the model, the thesis looks at its implications: how it has contributed to many, both the positive and negative, developments on the internet in recent years, but also driven the mass gathering, use and holding of
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Dotsenko, O. "COVID-19 Tracing Applications:is There any Privacy Threat?" Thesis, National Aviation University, 2021. https://er.nau.edu.ua/handle/NAU/48810.

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The COVID-19 pandemic is one of the most serious challenges of present world. With the increasing number of infected people to millions and the long process of vaccine creation, the latest information technologies are becoming the means of combating the spread of the disease. Thus, in many countries to combat the virus mobile applications for monitoring compliance with the regime of self-isolation and observation have become popular. But in order to counteract the disease, it is necessary to find out with whom virus carriers came into contact and what places they visited, that causes the poss
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Mitroff, Melanie. "Privacy : a constitutional right that threatens democracy /." Lynchburg, VA : Liberty University, 2007. http://digitalcommons.liberty.edu.

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Books on the topic "Privacy threats"

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Mahalle, Parikshit N., Gitanjali R. Shinde, Nilanjan Dey, and Aboul Ella Hassanien, eds. Security Issues and Privacy Threats in Smart Ubiquitous Computing. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-4996-4.

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Chesbro, Michael E. The privacy handbook: Proven countermeasures for combating threats to privacy, security, and personal freedom. Paladin Press, 2002.

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Akrivopoulou, Christina. Protecting the genetic self from biometric threats: Autonomy, identity, and genetic privacy. Information Science Reference, 2015.

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Services, ACM IV Security, ed. Surveillance countermeasures: A serious guide to detecting, evading, and eluding threats to personal privacy. Paladin Press, 1994.

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Reform, United States Congress House Committee on Government. Overexposed: The threats to privacy and security on filesharing networks : hearing before the Committee on Government Reform, House of Representatives, One Hundred Eighth Congress, first session, May 15, 2003. U.S. G.P.O., 2003.

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United States. Forest Service. Northern Research Station and United States. State and Private Forestry, eds. Threats to at-risk species in America's private forests. U.S. Dept. of Agriculture, Forest Service, Northern Research Station, 2010.

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Davis, Elaine R. The problem with power: Public threats to private utilities. Washington Institute for Policy Studies, 1997.

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Hugo, McPherson, Wood W. Duncan, and Robinson Derek M, eds. Emerging threats to energy security and stability. Springer, 2005.

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Dawson, Janet. A credible threat: A Jeri Howard mystery. Fawcett Columbine, 1996.

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Miston, Kimberly K. The DNA database: A feeling of security or a threat to one's privacy. National University, 2015.

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Book chapters on the topic "Privacy threats"

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Mattsson, Ulf. "Privacy, Risks, and Threats." In Controlling Privacy and the Use of Data Assets. CRC Press, 2022. http://dx.doi.org/10.1201/9781003189664-2.

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Zhou, Dan, and Shiu-Kai Chin. "Verifying privacy enhanced mail functions with higher order logic." In Network Threats. American Mathematical Society, 1997. http://dx.doi.org/10.1090/dimacs/038/02.

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Li, Jin, Ping Li, Zheli Liu, Xiaofeng Chen, and Tong Li. "Threats in Open Environment." In Privacy-Preserving Machine Learning. Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-9139-3_7.

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Singhal, Anoop, and Peng Liu. "Advanced Persistent Threats." In Encyclopedia of Cryptography, Security and Privacy. Springer Berlin Heidelberg, 2023. http://dx.doi.org/10.1007/978-3-642-27739-9_1765-1.

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Singhal, Anoop, and Peng Liu. "Advanced Persistent Threats." In Encyclopedia of Cryptography, Security and Privacy. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-030-71522-9_1765.

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Ghosh, Sutanu Kumar, and Rigel Gjomemo. "Detection and Threat-Hunting Approaches for Advanced Persistent Threats." In Encyclopedia of Cryptography, Security and Privacy. Springer Berlin Heidelberg, 2024. http://dx.doi.org/10.1007/978-3-642-27739-9_1821-1.

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Ghosh, Sutanu Kumar, and Rigel Gjomemo. "Detection and Threat-Hunting Approaches for Advanced Persistent Threats." In Encyclopedia of Cryptography, Security and Privacy. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-030-71522-9_1821.

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Buchmann, Johannes A. "Privacy Threats and Their Impact on the Core Values." In Internet Privacy. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-37913-0_5.

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Zhang, Zhongwen, Yuewu Wang, Jiwu Jing, Qiongxiao Wang, and Lingguang Lei. "Once Root Always a Threat: Analyzing the Security Threats of Android Permission System." In Information Security and Privacy. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-08344-5_23.

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Ayday, Erman, and Jean-Pierre Hubaux. "Threats and Solutions for Genomic Data Privacy." In Medical Data Privacy Handbook. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-23633-9_18.

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Conference papers on the topic "Privacy threats"

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Rani, Nanda, Bikash Saha, Ravi Kumar, and Sandeep Kumar Shukla. "Genesis of Cyber Threats: Towards Malware-based Advanced Persistent Threat (APT) Attribution." In 2024 IEEE 6th International Conference on Trust, Privacy and Security in Intelligent Systems, and Applications (TPS-ISA). IEEE, 2024. https://doi.org/10.1109/tps-isa62245.2024.00052.

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Bokde, Rohit, and Prasanna Phutane. "Blockchain Technology in Healthcare for Patient Privacy: Advances and Threats." In 2024 International Conference on Healthcare Innovations, Software and Engineering Technologies (HISET). IEEE, 2024. http://dx.doi.org/10.1109/hiset61796.2024.00093.

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Tang, Bing-Han, I.-Hsien Liu, Hou-Hua Chen, and Jung-Shian Li. "Security and Privacy Threats of O-RAN for Home Healthcare." In 2024 IEEE 6th Eurasia Conference on Biomedical Engineering, Healthcare and Sustainability (ECBIOS). IEEE, 2024. https://doi.org/10.1109/ecbios61468.2024.10885451.

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Gu, Yacong, Lingyun Ying, Huajun Chai, Yingyuan Pu, Haixin Duan, and Xing Gao. "More Haste, Less Speed: Cache Related Security Threats in Continuous Integration Services." In 2024 IEEE Symposium on Security and Privacy (SP). IEEE, 2024. http://dx.doi.org/10.1109/sp54263.2024.00138.

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Dimova, Yana, Mrunmayee Kode, Shirin Kalantari, Kim Wuyts, Wouter Joosen, and Jan Tobias Mühlberg. "From Privacy Policies to Privacy Threats: A Case Study in Policy-Based Threat Modeling." In CCS '23: ACM SIGSAC Conference on Computer and Communications Security. ACM, 2023. http://dx.doi.org/10.1145/3603216.3624962.

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Mylrea, Michael, Sri Nikhil Gupta Gourisetti, Curtis Larimer, and Christine Noonan. "Insider Threat Cybersecurity Framework Webtool & Methodology: Defending Against Complex Cyber-Physical Threats." In 2018 IEEE Security and Privacy Workshops (SPW). IEEE, 2018. http://dx.doi.org/10.1109/spw.2018.00036.

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Bella, Giampaolo, Francesco Librizzi, and Salvatore Riccobene. "Realistic Threats to Self-Enforcing Privacy." In 2008 Fourth International Conference on Information Assurance and Security (IAS). IEEE, 2008. http://dx.doi.org/10.1109/ias.2008.23.

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Hochheiser, Harry. "Indirect threats to freedom and privacy." In the tenth conference. ACM Press, 2000. http://dx.doi.org/10.1145/332186.332294.

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Singh, Shirish. "Surprising Privacy Threats from Innocuous Sensors." In MobiSys '21: The 19th Annual International Conference on Mobile Systems, Applications, and Services. ACM, 2021. http://dx.doi.org/10.1145/3469261.3469407.

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Ghemri, Lila. "Session details: Privacy and Threats Session." In CODASPY '17: Seventh ACM Conference on Data and Application Security and Privacy. ACM, 2017. http://dx.doi.org/10.1145/3252732.

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Reports on the topic "Privacy threats"

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Harriss, Lydia, and Clare West. Cyber Security of Consumer Devices. Parliamentary Office of Science and Technology, 2019. http://dx.doi.org/10.58248/pn593.

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Weaknesses in the cyber security of internet-connected consumer devices can undermine the privacy and safety of individual users and can be used for large-scale cyber-attacks. This briefing looks at the cyber threats associated with consumer devices and their causes, as well as initiatives to improve device security, and the related challenges.
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Pasupuleti, Murali Krishna. Securing AI-driven Infrastructure: Advanced Cybersecurity Frameworks for Cloud and Edge Computing Environments. National Education Services, 2025. https://doi.org/10.62311/nesx/rrv225.

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Abstract: The rapid adoption of artificial intelligence (AI) in cloud and edge computing environments has transformed industries by enabling large-scale automation, real-time analytics, and intelligent decision-making. However, the increasing reliance on AI-powered infrastructures introduces significant cybersecurity challenges, including adversarial attacks, data privacy risks, and vulnerabilities in AI model supply chains. This research explores advanced cybersecurity frameworks tailored to protect AI-driven cloud and edge computing environments. It investigates AI-specific security threats,
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Pulivarti, Ron. Privacy Threat Modeling. National Institute of Standards and Technology, 2025. https://doi.org/10.6028/nist.cswp.47.

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Durovic, Mateja, and Franciszek Lech. A Consumer Law Perspective on the Commercialization of Data. Universitätsbibliothek J. C. Senckenberg, Frankfurt am Main, 2021. http://dx.doi.org/10.21248/gups.64577.

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Commercialization of consumers’ personal data in the digital economy poses serious, both conceptual and practical, challenges to the traditional approach of European Union (EU) Consumer Law. This article argues that mass-spread, automated, algorithmic decision-making casts doubt on the foundational paradigm of EU consumer law: consent and autonomy. Moreover, it poses threats of discrimination and under- mining of consumer privacy. It is argued that the recent legislative reaction by the EU Commission, in the form of the ‘New Deal for Consumers’, was a step in the right direction, but fell shor
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Pasupuleti, Murali Krishna. Automated Smart Contracts: AI-powered Blockchain Technologies for Secure and Intelligent Decentralized Governance. National Education Services, 2025. https://doi.org/10.62311/nesx/rrv425.

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Abstract: Automated smart contracts represent a paradigm shift in decentralized governance by integrating artificial intelligence (AI) with blockchain technologies to enhance security, scalability, and adaptability. Traditional smart contracts, while enabling trustless and automated transactions, often lack the flexibility to adapt to dynamic regulatory frameworks, evolving economic conditions, and real-time security threats. AI-powered smart contracts leverage machine learning, reinforcement learning, and predictive analytics to optimize contract execution, detect fraudulent transactions, and
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Maddocks, Sophie. Image-Based Abuse: A Threat to Privacy, Safety, and Speech. MediaWell, Social Science Research Council, 2023. http://dx.doi.org/10.35650/mw.3051.d.2023.

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Stein, Susan M., Mary A. Carr, Ronald E. McRoberts, Lisa G. Mahal, and Sara J. Comas. Threats to at-risk species in America's private forests: a Forests on the Edge report. U.S. Department of Agriculture, Forest Service, Northern Research Station, 2010. http://dx.doi.org/10.2737/nrs-gtr-73.

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Efflandt, Scott L. Under Siege: How Private Security Companies Threaten the Military Profession. Defense Technical Information Center, 2013. http://dx.doi.org/10.21236/ada589194.

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Olson, Nate, Brian Finlay, and Esha Mufti. A Go-to-Market Strategy: Promoting Private Sector Solutions to the Threat of Proliferation. Defense Technical Information Center, 2013. http://dx.doi.org/10.21236/ada584066.

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Lu, Xianfu. Accelerating Private Sector Engagement in Adaptation in Asia and the Pacific. Asian Development Bank, 2022. http://dx.doi.org/10.22617/wps220513-2.

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This working paper outlines how to scale up the private sector’s involvement in climate adaptation and harness its financial clout, technical know-how, and ingenuity to help build climate resilient economies in the Asia and Pacific region. It assesses the role businesses currently play and looks at the technical, financial, and institutional hurdles they face. It explores financing options and underscores the importance of companies becoming “solution providers”. Analyzing climate threats and adaptation opportunities for businesses, it shows how organizations such as ADB can accelerate and gui
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