The Internet of Things (IoT) and its impact on individual privacy: An Australian perspective

doi:10.1016/j.clsr.2015.12.001

Computer Law & Security Review

Volume 32, Issue 1, February 2016, Pages 4-15

https://doi.org/10.1016/j.clsr.2015.12.001 Get rights and content

Abstract

The Internet of Things (IoT) heralds a new era of computing whereby every imaginable object is equipped with, or connected to a smart device allowing data collection and communication through the Internet. The IoT challenges individual privacy in terms of the collection and use of individuals' personal data. This study assesses the extent to which the Australian Privacy Principles protect individual privacy associated with data collection through the IoT. A systematic literature review identified four key privacy themes that represent issues related to the collection of individuals' data through the IoT: unauthorised surveillance, uncontrolled data generation and use, inadequate authentication and information security risks. These four themes are used to critically analyse the Australian Privacy Principle's (APPs) protection of individual data. Findings indicate that (1) the APPs do not adequately protect individual privacy of data collected through the IoT, and (2) future privacy legislation must consider the implications of global reach of IoT services, and ubiquity and security of IoT data collection with respect to individual privacy.

Section snippets

The Internet of Things

The Internet of Things (IoT) represents one of the most significant disruptive technologies of this century, consisting of an emerging global Internet-based technical architecture (Gubbi et al, 2013, Weber, 2010). Described by Atzori et al. (2010) as a novel technology that is rapidly gaining ground, the major enabling element of the IoT is the integration of several collaborative and communication technologies allowing for comprehensive data collection. Examples include tracking and

Research approach

This research followed two phases. In Phase 1 a systematic literature review was conducted following two activities: (1) a literature search process to identify and select relevant articles, and (2) a content analysis of the literature to identify themes that represent key concerns related to individual privacy from the perspective of the IoT. In Phase 2, a critical analysis followed that compared themes that emerged from Phase 1 with the APPs. The two phases are outlined below.

Findings

Findings are reported in two sections that follow: (1) the four key themes that emerged from the literature review and content analysis activities, and (2) a critical comparison of the resulting privacy themes with the 13 APPs.

Discussion

In reflection of the research question: To what extent does the Australian Privacy Principles protect an Australian individual's privacy in relation to data collected via the Internet of Things?, findings of this study found that the current APPs has limitations in terms of individual privacy and data collection through the IoT. These limitations impact on the ways in which individual data are collected, used and handled. In the sections that follow, APP limitations are first outlined, followed

Conclusion

This paper analyses the impact of data collected through the IoT by highlighting its impact on the Australian Privacy Principle legal framework. Even though the technology itself is more than five years away from its plateau of productivity (Gartner, 2014a), there are concerns that the IoT is bound to disrupt the idea of information control that forms an integral part of information privacy. The thirteen APPs were used to illustrate gaps in the current APP framework and highlights four key

References (0)

Cited by (100)

Using data mining techniques to explore security issues in smart living environments in Twitter
2021, Computer Communications
Citation Excerpt :
In this respect, Lin and Bergmann [25] and Chow [26] highlighted the concerns about user privacy and security of users, which is an important topic to thoroughly explore in the future [27]. It is important to note that, to date, several contributions analyzed how IoT sensors are added to the home networks when connecting new devices to the Internet [28]; similarly, other studies investigated the ways to make these devices safer from the technical point of view [29]. Overall, connected devices are linked to platforms that manage the data [30], which implies that security of these cloud-based devices should be a priority [31].
In present-day in consumers’ homes, there are millions of Internet-connected devices that are known to jointly represent the Internet of Things (IoT). The development of the IoT industry has led to the emergence of connected devices and home assistants that create smart living environments. However, the continuously generated data accumulated by these connected devices create security issues and raise user’s privacy concerns. The present study aims to explore the main security issues in smart living environments using data mining techniques. To this end, we applied a three-sentence data mining analysis of 938,258 tweets collected from Twitter under the user-generated data (UGD) framework. First, sentiment analysis was applied using Textblob which was tested with support vector classifier, multinomial naïve bayes, logistic regression, and random forest classifier; as a result, the analyzed tweets were divided into those expressing positive, negative, and neutral sentiment. Next, a Latent Dirichlet Allocation (LDA) algorithm was applied to divide the sample into topics related to security issues in smart living environments. Finally, the insights were extracted by applying a textual analysis process in Python validated with the analysis of frequency and weighted percentage variables and calculating the statistical measure known as mutual information (MI) to analyze the identified n-grams (unigrams and bigrams). As a result of the research 10 topics were identified in which we found that the main security issues are malware, cybersecurity attacks, data storing vulnerabilities, the use of testing software in IoT, and possible leaks due to the lack of user experience. We discussed different circumstances and causes that may affect user security and privacy when using IoT devices and emphasized the importance of UGC in the processing of personal data of IoT device users.
Setting Privacy “by Default” in Social IoT: Theorizing the Challenges and Directions in Big Data Research
2021, Big Data Research
The social Internet of Things (SIoT) shares large amounts of data that are then processed by other Internet of Thing (IoT) devices, which results in the generation, collection, and treatment of databases to be analyzed afterwards with Big Data techniques. This paradigm has given rise to users' concerns about their privacy, particularly with regard to whether users have to use a smart handling (self-establishment and self-management) in order to correctly install the SIoT, ensuring the privacy of the SIot-generated content and data. In this context, the present study aims to identify and explore the main perspectives that define user privacy in the SIoT; our ultimate goal is to accumulate new knowledge on the adoption and use of the concept of privacy “by default” in the scientific literature. To this end, we undertake a literature review of the main contributions on the topic of privacy in SIoT and Big Data processing. Based on the results, we formulate the following five areas of application of SIoT, including 29 key points relative to the concept of privacy “by default”: (i) SIoT data collection and privacy; (ii) SIoT security; (iii) threats for SIoT devices; (iv) SIoT devices mandatory functions; and (v) SIoT and Big Data processing and analytics. In addition, we outline six research propositions and discuss six challenges for the SIoT industry. The results are theorized for the future development of research on SIoT privacy by “default” and Big Data processing.
The effect of technological context on smart home adoption in Jordan
2024, Indonesian Journal of Electrical Engineering and Computer Science
The applications of Internet of Things (IoT) in industrial management: a science mapping review
2024, International Journal of Production Research
Introduction to IoT
2023, arXiv
Smart cities as a testbed for experimenting with humans? - Applying psychological ethical guidelines to smart city interventions
2023, Ethics and Information Technology

View all citing articles on Scopus

View full text