Data provenance to audit compliance with privacy policy in the Internet of Things

Managing privacy in the IoT presents a significant challenge. We make the case that information obtained by auditing the flows of data can assist in demonstrating that the systems handling personal data satisfy regulatory and user requirements. Thus, components handling personal data should be audited to demonstrate that their actions comply with all such policies and requirements. A valuable side-effect of this approach is that such an auditing process will highlight areas where technical enforcement has been incompletely or incorrectly specified. There is a clear role for technical assistance in aligning privacy policy enforcement mechanisms with data protection regulations. The first step necessary in producing technology to accomplish this alignment is to gather evidence of data flows. We describe our work producing, representing and querying audit data and discuss outstanding challenges.Engineering and Applied Science

Viewpoint | Personal Data and the Internet of Things: It is time to care about digital provenance

The Internet of Things promises a connected environment reacting to and addressing our every need, but based on the assumption that all of our movements and words can be recorded and analysed to achieve this end. Ubiquitous surveillance is also a precondition for most dystopian societies, both real and fictional. How our personal data is processed and consumed in an ever more connected world must imperatively be made transparent, and more effective technical solutions than those currently on offer, to manage personal data must urgently be investigated.Comment: 3 pages, 0 figures, preprint for Communication of the AC

Big Ideas paper: Policy-driven middleware for a legally-compliant Internet of Things.

Internet of Things (IoT) applications, systems and services are subject to law. We argue that for the IoT to develop lawfully, there must be technical mechanisms that allow the enforcement of speci ed policy, such that systems align with legal realities. The audit of policy enforcement must assist the apportionment of liability, demonstrate compliance with regulation, and indicate whether policy correctly captures le- gal responsibilities. As both systems and obligations evolve dynamically, this cycle must be continuously maintained. This poses a huge challenge given the global scale of the IoT vision. The IoT entails dynamically creating new ser- vices through managed and exible data exchange . Data management is complex in this dynamic environment, given the need to both control and share information, often across federated domains of administration. We see middleware playing a key role in managing the IoT. Our vision is for a middleware-enforced, uni ed policy model that applies end-to-end, throughout the IoT. This is because policy cannot be bound to things, applications, or administrative domains, since functionality is the result of composition, with dynamically formed chains of data ows. We have investigated the use of Information Flow Control (IFC) to manage and audit data ows in cloud computing; a domain where trust can be well-founded, regulations are more mature and associated responsibilities clearer. We feel that IFC has great potential in the broader IoT context. However, the sheer scale and the dynamic, federated nature of the IoT pose a number of signi cant research challenges

Big Ideas paper: Policy-driven middleware for a legally-compliant Internet of Things.

Internet of Things (IoT) applications, systems and services are subject to law. We argue that for the IoT to develop lawfully, there must be technical mechanisms that allow the enforcement of speci ed policy, such that systems align with legal realities. The audit of policy enforcement must assist the apportionment of liability, demonstrate compliance with regulation, and indicate whether policy correctly captures le- gal responsibilities. As both systems and obligations evolve dynamically, this cycle must be continuously maintained. This poses a huge challenge given the global scale of the IoT vision. The IoT entails dynamically creating new ser- vices through managed and exible data exchange . Data management is complex in this dynamic environment, given the need to both control and share information, often across federated domains of administration. We see middleware playing a key role in managing the IoT. Our vision is for a middleware-enforced, uni ed policy model that applies end-to-end, throughout the IoT. This is because policy cannot be bound to things, applications, or administrative domains, since functionality is the result of composition, with dynamically formed chains of data ows. We have investigated the use of Information Flow Control (IFC) to manage and audit data ows in cloud computing; a domain where trust can be well-founded, regulations are more mature and associated responsibilities clearer. We feel that IFC has great potential in the broader IoT context. However, the sheer scale and the dynamic, federated nature of the IoT pose a number of signi cant research challenges.Engineering and Physical Sciences Research Council (Grant ID: EP/K011510 CloudSafetyNet: End-to-End Application Security in the Cloud), Microsoft (through the Microsoft Cloud Computing Research Centre

Consumer Centric Data Control, Tracking and Transparency - A Position Paper

Personal data related to a user's activities, preferences and services, is considered to be a valuable commodity not only for a wide range of technology-oriented companies like Google, Amazon and Apple but also for more traditional companies like travel/transport, banking, entertainment and marketing industry. This has resulted in more targeted and to a great extend personalised services for individuals -- in most cases at a minimal financial cost to them. The operational reality upon which a user authorises companies to collect his/her personal data to receive, in return, more personalised/targeted/context-aware services and hassle-free activities (for users) is widely deployed. It becomes evident that the security, integrity and accessibility of the collected data are of paramount importance. These characteristics are becoming more entrenched in the era of Internet-of-Things (IoT), autonomous vehicles and seamless travel. In this position paper, we examine the challenges faced by both users and organisations in dealing with the Personal Identifiable Information (PII). Furthermore, we expand on the implications of the General Data Protection Regulation (GDPR) specifically for the management of the PII. Subsequently, we extend the discussion to future technologies, especially the IoT and integrated transport systems for better customer experience -- and their ramification on the data governance and PII management. Finally, we propose a framework that balances user's privacy and data control with an organisation's objective of delivering quality, targeted and efficient services to their customers using the "collected user data". This framework is referred to as "Consumer Oriented Data Control \& Auditability" (CODCA) and defines the technologies that are adapted to privacy concerns and legal/regulation-frameworks.Comment: 10 Pages, 2 Figures, Conferenc

Information Flow Audit for Transparency and Compliance in the Handling of Personal Data

This is the author accepted manuscript. The final version is available from IEEE via http://dx.doi.org/10.1109/IC2EW.2016.29The adoption of cloud computing is increasing and its use is becoming widespread in many sectors. As the proportion of services provided using cloud computing increases, legal and regulatory issues are becoming more significant. In this paper we explore how an Information Flow Audit (IFA) mechanism, that provides key data regarding provenance, can be used to verify compliance with regulatory and contractual duty, and survey potential extensions. We explore the use of IFA for such a purpose through a smart electricity metering use case derived from a French Data Protection Agency recommendation.This work was supported by UK Engineering and Physical Sciences Research Council grant EP/K011510 CloudSafetyNet: End-to-End Application Security in the Cloud. We acknowledge the support of Microsoft through the Microsoft Cloud Computing Research Centre

Information flow audit for PaaS clouds

© 2016 IEEE. With the rapid increase in uptake of cloud services, issues of data management are becoming increasingly prominent. There is a clear, outstanding need for the ability for specified policy to control and track data as it flows throughout cloud infrastructure, to ensure that those responsible for data are meeting their obligations. This paper introduces Information Flow Audit, an approach for tracking information flows within cloud infrastructure. This builds upon CamFlow (Cambridge Flow Control Architecture), a prototype implementation of our model for data-centric security in PaaS clouds. CamFlow enforces Information Flow Control policy both intra-machine at the kernel-level, and inter-machine, on message exchange. Here we demonstrate how CamFlow can be extended to provide data-centric audit logs akin to provenance metadata in a format in which analyses can easily be automated through the use of standard graph processing tools. This allows detailed understanding of the overall system. Combining a continuously enforced data-centric security mechanism with meaningful audit empowers tenants and providers to both meet and demonstrate compliance with their data management obligations.This work was supported by UK Engineering and Physical Sciences Research Council grant EP/K011510 CloudSafetyNet: End-to-End Application Security in the Cloud. We acknowledge the support of Microsoft through the Microsoft Cloud Computing Research Centre