User-centric privacy preserving models for a new era of the Internet of Things

Rivadeneira, Jorge Eduardo; Silva, Jorge Sá; Colomo‐Palacios, Ricardo; Rodrigues, André; Boavida, Fernando

doi:10.1016/j.jnca.2023.103695

Cited by 16 publications

(1 citation statement)

References 76 publications

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“…Implementing privacy-preserving techniques such as anonymization, pseudonymization, and secure data aggregation helps minimize the risk of unauthorized disclosure of sensitive details. Additionally, incorporating user-friendly interfaces for privacy settings and providing clear communication about data usage practices fosters a more transparent and user-centric approach [176]- [180]. Striking a balance between data utility and privacy concerns is essential to building trust among users, promoting ethical data handling practices, and ensuring that big data analytics can deliver valuable insights without compromising individual privacy rights.…”

Section: User-centric Privacy Solutionsmentioning

confidence: 99%

Tackling security and privacy challenges in the realm of big data analytics

Janet Ngesa

2023

World J. Adv. Res. Rev.

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As organizations increasingly harness the power of big data analytics to derive insights and drive decision-making, the paramount concerns of security and privacy have come to the forefront. This paper presents a comprehensive framework for addressing the multifaceted challenges of big data security and privacy. Drawing on a synthesis of cutting-edge technologies, encryption methods, and access control mechanisms, our approach aims to fortify the entire big data lifecycle. The paper delves into innovative strategies for secure data storage, transmission, and processing, ensuring that sensitive information is shielded from unauthorized access or malicious attacks. Additionally, the framework incorporates robust privacy-preserving techniques, including anonymization and differential privacy, to uphold individual confidentiality. Through a meticulous analysis of current trends, emerging threats, and regulatory landscapes, this paper not only provides theoretical insights but also practical guidelines for organizations seeking to navigate the intricate landscape of big data while safeguarding the integrity, security, and privacy of the vast datasets at their disposal.

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Section: User-centric Privacy Solutionsmentioning

confidence: 99%

Tackling security and privacy challenges in the realm of big data analytics

Janet Ngesa

2023

World J. Adv. Res. Rev.

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Exploring security and privacy enhancement technologies in the Internet of Things: A comprehensive review

Ataullah,

Chauhan

2024

Security and Privacy

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In the era heavily influenced by Internet of Things (IoT), prioritizing strong security and the protection of user privacy is of utmost importance. This comprehensive review paper embarks on a meticulous examination of the multifaceted challenges and risks facing IoT security and privacy. It encompasses the hardware, software, and data‐in‐transit domains, shedding light on potential vulnerabilities and associated threats. In response to these concerns, this paper puts forth recommendations for effective strategies to mitigate these risks. Providing a road‐map for enhancing security and privacy in IoT environments. Furthermore, this review thoroughly assesses a multitude of solutions proposed by various authors, with the primary aim of enhancing security and privacy within the IoT landscape. The analysis provides insights into the strengths and limitations of these solutions. This is aiding in the development of a holistic comprehension of the existing status of IoT security and privacy. Moreover, the paper delves into the complexities surrounding integrating emerging technologies into the IoT framework. It explores the obstacles and challenges inherent in this process and proposes potential strategies to address these hurdles. By doing so, the review provides a holistic perspective on existing security and privacy enhancement technologies and offers guidance on navigating the dynamic landscape of emerging technologies within the IoT domain. Publications included in the review consist of journal articles, conference papers, and book chapters from reputable sources indexed in SCI (Science Citation Index), Scopus, and Web of Science.

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