Privacy in Internet of Things (original) (raw)
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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.
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.
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...
Privacy Challenges and Their Solutions in IoT
Internet of Things (IoT)
IoT (Internet of Things) is connecting interrelated computing devices and the main idea for this concept is to connect each device via internet so that it will be easy for the devices to communicate and share info among them. These days IoT has grown up to a massive extent and new and emerging topic in research. IoT is the new and vast technology for the upcoming future as almost all devices will be connected to each other and share data among them via internet. This chapter identifies various privacy challenges in IoT, and their respective solutions presented by several researches over the time. It presents various issues related to privacy and security in IoT like standardization, networking and addressing ones. The chapter also deals within solutions provided for academic, technical and industrial aspects for IoT enabled environment. The importance of data security and protection to overcome the vulnerabilities which can come for an IoT based environment and can reduce the risk for IoT infrastructure.
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.
Towards Information Privacy for the Internet of Things
ArXiv, 2016
In an Internet of Things network, multiple sensors send information to a fusion center for it to infer a public hypothesis of interest. However, the same sensor information may be used by the fusion center to make inferences of a private nature that the sensors wish to protect. To model this, we adopt a decentralized hypothesis testing framework with binary public and private hypotheses. Each sensor makes a private observation and utilizes a local sensor decision rule or privacy mapping to summarize that observation independently of the other sensors. The local decision made by a sensor is then sent to the fusion center. Without assuming knowledge of the joint distribution of the sensor observations and hypotheses, we adopt a nonparametric learning approach to design local privacy mappings. We introduce the concept of an empirical normalized risk, which provides a theoretical guarantee for the network to achieve information privacy for the private hypothesis with high probability wh...
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.
2019
Internet of things (IOT) is growing and relatively new technology using wireless Sensor Networks (WSN) and IP based communication. Participation of large number of devices and there mobility make it more and more challenging in term of connectivity, security and user privacy. In this paper we are going to analyze the technological aspect regarding network technologies, security and user privacy issues and suggest measures for improvements of user privacy in such ubiquitous networks. Because of unattended nature of IOT devices regular connectivity and security related issues always will be there and these are of our major concerns to make the network more secure. This paper is going to focus specially user privacy in this wireless nature of the networks, where user is not fully aware with the data collection and its usage. Normally, data is collected more than required, it must be according to actual needs and its usage should be accordance with collection purpose to maintain the use...
An Improvised Framework for Privacy Preservation in IoT
International Journal of Information Security and Privacy
Data privacy is now-a-days a special issue in era of Internet of Things because of the big data stored and transmitted by the public/private devices. Different types and levels of privacy can be provided at different layers of IoT architecture, also different mechanisms operate at different layers of IoT architecture. This article presents the work being done towards the design of a generic framework to integrate these privacy preserving mechanisms at different layers of IoT architecture and can ensure privacy preservation in a heterogeneous IoT environment. The data is classified into different levels of secrecy and appropriate rules and mechanisms are applied to ensure this privacy. The proposed framework is implemented and evaluated for its performance with security and execution time or primary parameters. Various scenarios are also evaluated, and a comparison is done with an existing mechanism ABE (Attribute Based Encryption). It has been found that the proposed work takes less...
Big Data Privacy in the Internet of Things Era
Over the last few years, we've seen a plethora of Internet of Things (IoT) solutions, products, and services make their way into the industry's marketplace. All such solutions will capture large amounts of data pertaining to the environment as well as their users. The IoT's objective is to learn more and better serve system users. Some IoT solutions might store data locally on devices ("things"), whereas others might store it in the cloud. The real value of collecting data comes through data processing and aggregation on a large scale, where new knowledge can be extracted. However, such procedures can lead to user privacy issues. This article discusses some of the main challenges of privacy in the IoT as well as opportunities for research and innovation. The authors also introduce some of the ongoing research efforts that address IoT privacy issues.