Privacy Guidelines for Internet of Things: A Cheat Sheet (original) (raw)
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Privacy-by-Design Framework for Assessing Internet of Things Applications and Platforms
The Internet of Things (IoT) systems are designed and developed either as standalone applications from the ground-up or with the help of IoT middleware platforms. They are designed to support different kinds of scenarios, such as smart homes and smart cities. Thus far, privacy concerns have not been explicitly considered by IoT applications and middleware platforms. This is partly due to the lack of systematic methods for designing privacy that can guide the software development process in IoT. In this paper, we propose a set of guidelines, a privacy-by-design framework, that can be used to assess privacy capabilities and gaps of existing IoT applications as well as middleware platforms. We have evaluated two open source IoT middleware platforms, namely OpenIoT and Eclipse SmartHome, to demonstrate how our framework can be used in this way.
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.
Designing privacy-aware internet of things applications
Information Sciences, 2019
Internet of Things (IoT) applications typically collect and analyse personal data that can be used to derive sensitive information about individuals. However, thus far, privacy concerns have not been explicitly considered in software engineering processes when designing IoT applications. The advent of behaviour driven security mechanisms, failing to address privacy concerns in the design of IoT applications can have security implications. In this paper, we explore how a Privacy-by-Design (PbD) framework, formulated as a set of guidelines, can help software engineers integrate data privacy considerations into the design of IoT applications. We studied the utility of this PbD framework by studying how software engineers use it to design IoT applications. We also explore the challenges in using the set of guidelines to influence the IoT applications design process. In addition to highlighting the benefits of having a PbD framework to make privacy features explicit during the design of IoT applications, our studies also surfaced a number of challenges associated with the approach. A key finding of our research is that the PbD framework significantly increases both novice and expert software engineers' ability to design privacy into IoT applications.
Privacy-Aware in the IoT Applications: A Systematic Literature Review
Lecture Notes in Computer Science, 2017
The Internet of Things (IoT) emerged as a paradigm in which smart things collaborate among them and with other physical and virtual objects using the Internet in order to perform high level tasks. These things appear in a variety of application domains, including smart grid, health care and smart spaces where several parties share data in order to tackle specific tasks. Data in such domains are rich in sensitive data and data owner-specific habits. Thus, IoT raises concerns about privacy and data protection. This paper reports on a systematic literature review of privacy preserving solutions used in Cooperative Information Systems (CIS) in the IoT field. To do so, and after retrieving scientific productions on the subject, we classify the results according to several facets. In this paper, we consider a subset of them: (i) data life cycle, (ii) privacy preserving techniques and (iii) ISO privacy principles. We combine the facets then express and analyze the results as bubble charts. We analyze the proposed solutions in terms of the techniques they deployed and the privacy principles they covered according to the ISO standard and the data privacy laws and regulations of the European Commission on the Protection of Personal Data. Finally, we identifies recommendations to involve privacy principle coverage and security requirement fulfillment in the IoT applications.
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...
Privacy and Security Best Practices for IoT Solutions
IEEE Access
The rapid increase in Internet of Things (IoT) applications has raised security and privacy issues due to the huge amount of data acquired by IoT devices and transmitted through the Internet. Therefore, there is a need to understand what strategies should be applied to make IoT systems robust to security flaws and privacy weaknesses. In this paper, we first identify and discuss the best practices for IoT privacy and security, which include a set of procedures that can be taken as the guidelines to determine and solve privacy and security issues of IoT systems. Then, we follow and apply the identified best practices to two real IoT-based use cases: a crowding monitoring system and a vehicular mobility system. Finally, we computed the risk assessment score to evaluate the impact of the application of the identified best practices on the implemented IoT systems. We observe that following the proposed best practices the implemented IoT systems achieve an overall risk score of 1.3, which is from 215% to 361% lower than that achieved by comparable IoT systems proposed in the literature studies. INDEX TERMS Internet of Things, IoT security, best practices, non-personal data, privacy by design, risk assessment.
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.
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.
Journal of Sensor and Actuator Networks, 2019
As Internet of Things (IoT) involvement increases in our daily lives, several security and privacy concerns like linkability, unauthorized conversations, and side-channel attacks are raised. If they are left untouched, such issues may threaten the existence of IoT. They derive from two main reasons. One is that IoT objects are equipped with limited capabilities in terms of computation power, memory, and bandwidth which hamper the direct implementation of traditional Internet security techniques. The other reason is the absence of widely-accepted IoT security and privacy guidelines and their appropriate implementation techniques. Such guidelines and techniques would greatly assist IoT stakeholders like developers and manufacturers, paving the road for building secure IoT systems from the start and, thus, reinforcing IoT security and privacy by design. In order to contribute to such objective, we first briefly discuss the primary IoT security goals and recognize IoT stakeholders. Seco...
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.