Promoting Information Privacy Protection Awareness for Internet of Things (IoT) (original) (raw)
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Indian Journal of Natural Sciences, 2023
The Internet of Things (IoT) is a systemic organization of smart devices, intelligent things, information, and data as well as safe and secured access of internet by people using them. It is very important to have a deep understanding on several gadgets connected to the internet, the issues of safeguarding the data to be accessed and retrieved for communicating a variety of users. Introduction of several number of IoT platforms and devices over the years has led to the use of smart physical objects among the users from the societies and businesses. Nevertheless, IoT ecosystem is vulnerable which needs to be built for a safe and secured use of the devices and objects. The IoT service providers like Amazon's Echo devices and Alexa Voice Service. Google, Microsoft, and Apple should ensure security, privacy and trust while providing seamless services to the people using them. This empirical paper contributes to the elimination and mitigation of risks associated with access and use of IoT as well as provides increasing body of knowledge on this transformative topic by investigating the challenges and problems involved in accessing the internet for a variety of purposes using devices, technologies and applications over a platform and of IoT landscape.
Information Privacy Concerns in the Age of Internet of Things
2018
Internet of things (IoT) offer new opportunities for advancement in many domains including healthcare, home automation, manufacturing and transportation. In recent years, the number of IoT devices have exponentially risen and this meteoric rise is poised to continue according to the industry. Advances in the IoT integrated with ambient intelligence are intended to make our lives easier. Yet for all these advancements, IoT also has a dark side. Privacy and security were already priorities when personal computers, devices and work stations were the only point of vulnerability to personal information, however, with the ubiquitous nature of smart technologies has increased data collection points around us exponentially. Beyond that, the massive amount of data collected by IoT devices is relatively unknown and uncontrolled by users thereby exacerbating privacy issues and concerns. This study aims to create better understanding of privacy concerns stemming from most popular smart technolo...
A Survey on Understanding and Representing Privacy Requirements in the Internet-of-Things
Journal of Artificial Intelligence Research
People are interacting with online systems all the time. In order to use the services being provided, they give consent for their data to be collected. This approach requires too much human effort and is impractical for systems like Internet-of-Things (IoT) where human-device interactions can be large. Ideally, privacy assistants can help humans make privacy decisions while working in collaboration with them. In our work, we focus on the identification and representation of privacy requirements in IoT to help privacy assistants better understand their environment. In recent years, more focus has been on the technical aspects of privacy. However, the dynamic nature of privacy also requires a representation of social aspects (e.g., social trust). In this survey paper, we review the privacy requirements represented in existing IoT ontologies. We discuss how to extend these ontologies with new requirements to better capture privacy, and we introduce case studies to demonstrate the appli...
TURP: Managing Trust for Regulating Privacy in Internet of Things
IEEE Internet Computing, 2020
Internet of Things [IoT] applications, such as smart home or ambient assisted living systems, promise useful services to end users. Most of these services rely heavily on sharing and aggregating information among devices; many times raising privacy concerns. Contrary to traditional systems, where privacy of each user is managed through well-defined policies, the scale, dynamism, and heterogeneity of the IoT systems make it impossible to specify privacy policies for all possible situations. Alternatively, this paper argues that handling of privacy has to be reasoned by the IoT devices, depending on the norms, context, as well as the trust among entities. We present a technique, where an IoT device collects information from others, evaluates the trustworthiness of the information sources to decide the suitability of sharing information with others. We demonstrate the applicability of the technique over an IoT pilot study.
Security, privacy and trust in Internet of Things: The road ahead
Computer Networks, 2015
Internet of Things (IoT) is characterized by heterogeneous technologies, which concur to the provisioning of innovative services in various application domains. In this scenario, the satisfaction of security and privacy requirements plays a fundamental role. Such requirements include data confidentiality and authentication, access control within the IoT network, privacy and trust among users and things, and the enforcement of security and privacy policies. Traditional security countermeasures cannot be directly applied to IoT technologies due to the different standards and communication stacks involved. Moreover, the high number of interconnected devices arises scalability issues; therefore a flexible infrastructure is needed able to deal with security threats in such a dynamic environment. In this survey we present the main research challenges and the existing solutions in the field of IoT security, identifying open issues, and suggesting some hints for future research.
Zenodo (CERN European Organization for Nuclear Research), 2022
The Internet of Things (IoT) is a self-configuring, intelligent system in which autonomous things connect to the Internet and communicate with each other. As 'things' are autonomous, it may raise privacy concerns. In this study, the authors describe the background of IoT systems and privacy and security measures, including (a) approaches to preserving privacy in IoT-based systems, (b) existing privacy solutions, and (c) recommending privacy models for different layers of IoT applications. Based on the results of our study, it is clear that new methods such as Blockchain, Machine Learning, Data Minimisation, and Data Encryption can greatly impact privacy issues to ensure security and privacy. Moreover, it makes sense that users can protect their personal information easier if there is fewer data to collect, store, and share by smart devices. Thus, this study proposes a machine learning-based data minimisation method that, in these networks, can be very beneficial for privacy-preserving.
Encouraging User-Trust to Internet-of-Things Implementations
2016
In several scientific studies, it is stated that the foremost challenge in proliferation of internet-of-things (IoT) applications is the security. Trust is more notable than the other security dimensions in the acceptance and spread of IoT. In this study, with an emphasis on the security problem in IoT applications, the effective factors on establishing and flourishing user-trust in IoT applications are reported in a classification and the measures to consolidate trust and willingness-to-take-risk in IoT users are proposed.
Beyond the convenience of the internet of things: Security and privacy concerns
2017 IST-Africa Week Conference (IST-Africa), 2017
The significant growth of the Internet of Things (IoT) is revolutionizing the way people live by transforming everyday Internet-enabled objects into an interconnected ecosystem of digital and personal information accessible anytime and anywhere. As more objects become Internet-enabled, the security and privacy of the personal information generated, processed and stored by IoT devices become complex and challenging to manage. This paper details the current security and privacy challenges presented by the increasing use of the IoT. Furthermore, investigate and analyze the limitations of the existing solutions with regard to addressing security and privacy challenges in IoT and propose a possible solution to address these challenges. The results of this proposed solution could be implemented during the IoT design, building, testing and deployment phases in the real-life environments to minimize the security and privacy challenges associated with IoT.
Safety, Security, and Privacy Threats Posed by Accelerating Trends in the Internet of Things
arXiv (Cornell University), 2020
The Internet of Things (IoT) is already transforming industries, cities, and homes. The economic value of this transformation across all industries is estimated to be trillions of dollars and the societal impact on energy efficiency, health, and productivity are enormous. Alongside potential benefits of interconnected smart devices comes increased risk and potential for abuse when embedding sensing and intelligence into every device. One of the core problems with the increasing number of IoT devices is the increased complexity that is required to operate them safely and securely. This increased complexity creates new safety, security, privacy, and usability challenges far beyond the difficult challenges individuals face just securing a single device. We highlight some of the negative trends that smart devices and collections of devices cause and we argue that issues related to security, physical safety, privacy, and usability are tightly interconnected and solutions that address all four simultaneously are needed. Tight safety and security standards for individual devices based on existing technology are needed. Likewise research that determines the best way for individuals to confidently manage collections of devices must guide the future deployments of such systems.
Privacy is the Boring Bit": User Perceptions and Behaviour in the Internet-of-Things
arXiv (Cornell University), 2018
In opinion polls, the public frequently claim to value their privacy. However, individuals often seem to overlook the principle, contributing to a disparity labelled the 'Privacy Paradox'. The growth of the Internet-of-Things (IoT) is frequently claimed to place privacy at risk. However, the Paradox remains underexplored in the IoT. In addressing this, we first conduct an online survey (N = 170) to compare public opinions of IoT and less-novel devices. Although we find users perceive privacy risks, many still decide to purchase smart devices. With the IoT rated less usable/familiar, we assert that it constrains protective behaviour. To explore this hypothesis, we perform contextualised interviews (N = 40) with the public. In these dialogues, owners discuss their opinions and actions with a personal device. We find the Paradox is significantly more prevalent in the IoT, frequently justified by a lack of awareness. We finish by highlighting the qualitative comments of users, and suggesting practical solutions to their issues. This is the first work, to our knowledge, to evaluate the Privacy Paradox over a broad range of technologies.