Privacy-Aware in the IoT Applications: A Systematic Literature Review (original) (raw)
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Reference Architectures for Privacy Preservation in Cloud-based IoT Applications
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As the promise of the Internet of Things (IoT) materializes in our everyday lives, we are often challenged with a number of concerns regarding the efficacy of the current data privacy solutions that support the pervasive components at play in IoT. The privacy and security concerns surrounding IoT applications often manifests themselves as a threat to end-user adoption and negatively impacts trust among end-users. In this paper, we present a reference software architectures for building cloud-enabled IoT applications in support of collaborative pervasive systems aimed at achieving trustworthiness among end-users in IoT scenarios. We describe a case study that leverages this reference architecture to protect sensitive user data in IoT application implementation. We then evaluate the response data from our end-user survey. In addition we present a Secure, Private and Trustworthy protocol (named SPTP) that was prototyped for addressing critical security, privacy and trust concerns surrounding mobile, pervasive and cloud services in Collective Intelligence (CI) scenarios. We present our evaluation criteria for the proposed protocol, our results and future work.
Preserving privacy in internet of things: a survey
International journal of information technology, 2018
Internet of things (IOT) paradigm is changing day to day lives towards sophisticated automation and enhancing living standards of our societies. The most of ''Things'' in IOT are having limited power, storage, and computational capabilities. Therefore data is collected, manipulated and stored in the clouds. The benefit of ''anytime and anywhere'' access of data gives rise to serious security and privacy issues and lead to many problems like exposure of user's personal and sensitive information and loss of the trust between parties. These challenges need to be addressed with adequately with utmost care. From an operational point of view, the major concern for IOT is ''Privacy''. In this article, we discuss difference between privacy and security. Further, and present several approaches and techniques that are being used to fulfill the privacy requirements. This comparative study also contains advantages and disadvantages of the mentioned approaches. Finally, we discuss the future opportunities, trends, and provide recommendations about the privacy for IOT based applications and services.
Living in the Internet of Things (IoT 2019), 2019
One of the main obstacles to the widespread adoption of IoT devices and services is consumers' privacy concerns related to personal data collection, processing and sharing with third parties. Indeed, many IoT devices have been found collecting consumers' personal data without their knowledge or consent. While frameworks for identifying and mitigating security concerns of IoT devices and services are available, there is a lack of frameworks that address privacy issues for IoT applications. In this paper we lay the foundations for the future development of such a framework, based on both the experimental analysis of data flows on an IoT Smart Home testbed and a systematic analysis of other frameworks.
Strategies for Internet of Things data privacy and security using systematic review
European Conference on Cyber Warfare and Security
The Internet of Things (IoT) now referend to as the Internet of Everything (IoE) has been in existence long before it was identified as a concept. It was introduced with the emergence of the Fourth Industrial Revolution and was aimed at improving people’s lives and economies across the globe by connecting physical items to the internet so they can be able to deliver specific services implicitly. The nature of IoT requires that all the systems ensure data privacy and security because much of data that is uploaded into and used by the system is personal and private. Thus, the aim of this research was to identify the tools and strategies that can be used for IoT data privacy and security while also providing a brief but intensive understanding of the concept of IoT and data privacy and security challenges faced by IoT systems. This qualitative research study utilised a pragmatic paradigm and data was collected and analysed using text-based secondary data sources and a PRISMA protocol t...
Journal of Network and Computer Applications
IoT data markets in public and private institutions have become increasingly relevant in recent years because of their potential to improve data availability and unlock new business models. However, exchanging data in markets bears considerable challenges related to the disclosure of sensitive information. Despite considerable research that has focused on different aspects of privacyenhancing data markets for the IoT, none of the solutions proposed so far seems to find considerable practical adoption. Thus, this study aims to organize the state-of-the-art solutions, analyze and scope the technologies that have been suggested in this context, and structure the remaining challenges to determine areas where future research is required. To accomplish this goal, we conducted a systematic literature review on privacy enhancement in data markets for the IoT, covering 50 publications dated up to July 2020. Our results indicate that most research in this area has emerged only recently, and no IoT data market architecture has established itself as canonical. Existing solutions frequently lack the required combination of anonymization and secure computation technologies. Furthermore, there is no consensus on the appropriate use of blockchain technology for IoT data markets and a low degree of leveraging existing libraries or reusing generic data market architectures. We also identified significant remaining challenges such as the copy problem and the recursive enforcement problem that-while solutions have been suggested to some extent-are often not sufficiently addressed in proposed designs.
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...
Towards Privacy Preserving IoT Environments: A Survey
Wireless Communications and Mobile Computing, 2018
The Internet of Things (IoT) is a network of Internet-enabled devices that can sense, communicate, and react to changes in their environment. Billions of these computing devices are connected to the Internet to exchange data between themselves and/or their infrastructure. IoT promises to enable a plethora of smart services in almost every aspect of our daily interactions and improve the overall quality of life. However, with the increasing wide adoption of IoT, come significant privacy concerns to lose control of how our data is collected and shared with others. As such, privacy is a core requirement in any IoT ecosystem and is a major concern that inhibits its widespread user adoption. The ultimate source of user discomfort is the lack of control over personal raw data that is directly streamed from sensors to the outside world. In this survey, we review existing research and proposed solutions to rising privacy concerns from a multipoint of view to identify the risks and mitigatio...
The Internet of Things (IoT) is the latest web evolution that incorporates billions of devices that are owned by different organizations and people who are deploying and using them for their own purposes. IoT-enabled harnessing of the information that is provided by federations of such IoT devices (which are often referred to as IoT things) provides unprecedented opportunities to solve internet-scale problems that have been too big and too difficult to tackle before. Just like other web-based information systems, IoT must also deal with the plethora of Cyber Security and privacy threats that currently disrupt organisations and can potentially hold the data of entire industries and even countries for ransom. To realize its full potential, IoT must deal effectively with such threats and ensure the security and privacy of the information collected and distilled from IoT devices. However, IoT presents several unique challenges that make the application of existing security and privacy techniques difficult. This is because IoT solutions encompass a variety of security and privacy solutions for protecting such IoT data on the move and in store at the device layer, the IoT infrastructure/platform layer, and the IoT application layer. Therefore, ensuring end-to-end privacy across these three IoT layers is a grand challenge in IoT. In this paper, we tackle the IoT privacy preservation problem. In particular, we propose innovative techniques for privacy preservation of IoT data, introduce a privacy preserving IoT Architecture, and also describe the implementation of an efficient proof of concept system that utilizes all these to ensure that IoT data remains private. The proposed privacy preservation techniques utilise multiple IoT cloud data stores to protect the privacy of data collected from IoT. The proposed privacy preserving IoT Architecture and proof of concept implementation are based on extensions of OpenIoT -a widely used open source platform for IoT application development. Experimental evaluations are also provided to validate the efficiency and performance outcomes of the proposed privacy preserving techniques and architecture.
Towards Privacy Preserving IoT Environments A Survey.pdf
The Internet of Things (IoT) is a network of Internet-enabled devices that can sense, communicate, and react to changes in their environment. Billions of these computing devices are connected to the Internet to exchange data between themselves and/or their infrastructure. IoT promises to enable a plethora of smart services in almost every aspect of our daily interactions and improve the overall quality of life. However, with the increasing wide adoption of IoT, it comes significant privacy concerns to lose control of how our data is collected and shared with others. As such, privacy is a core requirement in any IoT ecosystem and is a major concern that inhibits its widespread user adoption. The ultimate source of user discomfort is the lack of control over personal raw data that is directly streamed from sensors to the outside world. In this survey, we review existing research and proposed solutions to rising privacy concerns from a multi-point of view to identify the risks and mitigations. First, we provide an evaluation of privacy issues and concerns in IoT systems due to resource constraints. Second, we describe proposed IoT solutions that embrace a variety of privacy concerns such as identification, tracking, monitoring and profiling. Lastly, we discuss the mechanisms and architectures for protecting IoT data in case of mobility/permanence at the device layer, infrastructure/platform layer, and application layer.
International Journal for Research in Applied Science and Engineering Technology
Internet of things (IoT) is quickly gaining popularity due to its necessity and effectiveness in the computer realm. The provision of wireless connectivity as well as the emergence of gadgets alleviates its practice essentially in governing systems in various fields. Nevertheless, these systems are universal, seamless and pervasive, an issue regarding consumers' privacy remains debatable. This is valid in almost all the sectors. In this paper, we discuss related concepts and methods for data privacy in IoT, and recognize research challenges that must be addressed by comprehensive solutions to data privacy.