Search

Global financial crime activity is driving demand for machine learning solutions in fraud prevention. However, prevention systems are commonly serviced to financial institutions in isolation, and few provisions exist for data sharing due to fears of unintentional leaks and adversarial attacks. Collaborative learning advances in finance are rare, and it is hard to find real-world insights derived from privacy-preserving data processing systems. In this paper, we present a collaborative deep learning framework for fraud prevention, designed from a privacy standpoint, and awarded at the recent PETs Prize Challenges. We leverage latent embedded representations of varied-length transaction sequences, along with local differential privacy, in order to construct a data release mechanism which can securely inform externally hosted fraud and anomaly detection models. We assess our contribution on two distributed data sets donated by large payment networks, and demonstrate robustness to popular inference-time attacks, along with utility-privacy trade-offs analogous to published work in alternative application domains.

Most of the existing models for deploying IoT ecosystem involves the vendor being in the loop of the command and control of IoT devices hence users' privacy and security is one of the main challenges. Despite these concerns, users are often faced with a choice between limiting the device functionality or enabling internet access to the IoT devices by signing up to the vendor centralized model in order to access their device from outside their home. In this paper, we argue that although IoT is promising a revolutionary way of offering services to users, most of these devices shouldn't be allowed to have Internet access due to the increased risks to privacy and security. We present an alternative home networking design model which limits the exposure of IoT devices, and enable seamless access to their functionality from outside the home using WireGuard (WG), a state-of-the-art Virtual Private Network (VPN) protocol. We built a test-bed using off-the-shelf IoT devices for testing our proposed network design under various conditions; including access from Home, 4G, Office and Public Wifi networks. We show that our VPN-based remote access to the IoT device offers a better performance in terms of end-to-end delay in all scenarios when using Hypertext Transport Protocol (HTTP) and comparable performance when using double encryption Hypertext Transport Protocol Secure (HTTPS) over the VPN.

This chapter draws from across the foregoing chapters discussing many core HDI approaches and disciplinary perspectives to consider the specific application of HDI in home network security. While much work has considered the challenges of securing in home IoT devices and their communications, especially for those with limited power or computational capacity, scant attention has been paid by the research community to home network security, and its acceptability and usability, from the viewpoint of ordinary citizens. It will be clear that we need a radical transformation in our approach to designing domestic networking infrastructure to guard against widespread cyber-attacks that threaten to counter the benefits of the IoT. Our aim has to be to defend against enemies inside the walls, to protect critical functionality in the home against rogue devices and prevent the proliferation of disruptive wide-scale IoT DDOS attacks that are already occurring [1]., Comment: Preprint of Chapter 9 of Privacy by Design for the Internet of Things: Building accountability and security

A common approach to securing end-to-end connectivity between devices on the Internet is to utilise a cloud-based intermediary. With this reliance upon a third-party comes a set of security and privacy concerns that are difficult to mitigate. A promising new protocol, Wireguard, dispenses with the middleman to provide secure peer-to-peer communication. However, support for initial key exchange falls outside Wireguard's scope, making it potentially vulnerable to insecure out-of-band key exchange. The design of secure and usable key exchange methods is challenging, not least in domestic spaces, as they're often characterised by technically naive users in multi-occupancy environments, making them susceptible to insider and passer-by attacks (i.e.: theft, observation attacks, relay and impersonation attacks). We describe and present the results from a design ideation study that probes the use of tangible, multi-factor approaches for securing key exchange in domestic spaces. The study suggests that a home's semi-fixed features (e.g.: lamps, shelves, chairs) can be instrumented to support a promising three-factor authentication approach ('what you have, what you know and where you are') to enable key exchange solutions that are i. more secure than commonly used naive approaches and ii. desirable for end users.

With hundreds of thousands of individuals using social media to discuss health concerns, sensitive personal data is self-disclosed on these platforms every day. Previous research indicates an understanding of social privacy concerns by patients with chronic illnesses, but there is a lack of understanding in the perception of information privacy concerns. Qualitative interviews were conducted with 38 patients with inflammatory bowel disease (IBD) using social media platforms to engage with online communities. Using thematic analysis, we identified that patients typically demonstrate the privacy and risk dual calculus for perceived social privacy concerns. Patients demonstrate mixed knowledge of what data is collected and how it is used by social media platforms and often described their platform use as a trade-off between the unknown information privacy risks and the therapeutic affordances of engaging with the online community (the privacy calculus). Our findings illustrate the different levels of understanding between social and information privacy and the impacts on how individuals take agency over their personal data. We conclude with the suggestion for future research to further understand the relationship between knowledge, information privacy concerns and mitigating actions in the online health community context.

To date, cloud applications have used datacenter resources through manual configuration and deployment of virtual machines and containers. Current trends see increasing use of microservices, where larger applications are split into many small containers, to be developed and deployed independently. However, even with the rise of the devops movement and orchestration facilities such as Kubernetes, there is a tendency to separate development from deployment. We present an exploration of a more extreme point on the devops spectrum: Fractal. Developers embed orchestration logic inside their application, fully automating the processes of scaling up and down. Providing a set of extensions to and an API over the Jitsu platform, we outline the design of Fractal and describe the key features of its implementation: how an application is self-replicated, how replica lifecycles are managed, how failure recovery is handled, and how network traffic is transparently distributed between replicas. We present evaluation of a self-scaling website, and demonstrate that Fractal is both useful and feasible.

In this paper, we introduce Zest (REST over ZeroMQ), a middleware technology in support of an Internet of Things (IoT). Our work is influenced by the Constrained Application Protocol (CoAP) but emphasises systems that can support fine-grained access control to both resources and audit information, and can provide features such as asynchronous communication patterns between nodes. We achieve this by using a hybrid approach that combines a RESTful architecture with a variant of a publisher/subscriber topology that has enhanced routing support. The primary motivation for Zest is to provide inter-component communications in the Databox, but it is applicable in other contexts where tight control needs to be maintained over permitted communication patterns.

Security incidents such as targeted distributed denial of service (DDoS) attacks on power grids and hacking of factory industrial control systems (ICS) are on the increase. This paper unpacks where emerging security risks lie for the industrial internet of things, drawing on both technical and regulatory perspectives. Legal changes are being ushered by the European Union (EU) Network and Information Security (NIS) Directive 2016 and the General Data Protection Regulation 2016 (GDPR) (both to be enforced from May 2018). We use the case study of the emergent smart energy supply chain to frame, scope out and consolidate the breadth of security concerns at play, and the regulatory responses. We argue the industrial IoT brings four security concerns to the fore, namely: appreciating the shift from offline to online infrastructure; managing temporal dimensions of security; addressing the implementation gap for best practice; and engaging with infrastructural complexity. Our goal is to surface risks and foster dialogue to avoid the emergence of an Internet of Insecure Industrial Things

There is an increasing role for the IT design community to play in regulation of emerging IT. Article 25 of the EU General Data Protection Regulation (GDPR) 2016 puts this on a strict legal basis by establishing the need for information privacy by design and default (PbD) for personal data-driven technologies. Against this backdrop, we examine legal, commercial and technical perspectives around the newly created legal right to data portability (RTDP) in GDPR. We are motivated by a pressing need to address regulatory challenges stemming from the Internet of Things (IoT). We need to find channels to support the protection of these new legal rights for users in practice. In Part I we introduce the internet of things and information PbD in more detail. We briefly consider regulatory challenges posed by the IoT and the nature and practical challenges surrounding the regulatory response of information privacy by design. In Part II, we look in depth at the legal nature of the RTDP, determining what it requires from IT designers in practice but also limitations on the right and how it relates to IoT. In Part III we focus on technical approaches that can support the realisation of the right. We consider the state of the art in data management architectures, tools and platforms that can provide portability, increased transparency and user control over the data flows. In Part IV, we bring our perspectives together to reflect on the technical, legal and business barriers and opportunities that will shape the implementation of the RTDP in practice, and how the relationships may shape emerging IoT innovation and business models. We finish with brief conclusions about the future for the RTDP and PbD in the IoT.

The Internet of Things (IoT) is expected to generate large amounts of heterogeneous data from diverse sources including physical sensors, user devices, and social media platforms. Over the last few years, significant attention has been focused on personal data, particularly data generated by smart wearable and smart home devices. Making personal data available for access and trade is expected to become a part of the data driven digital economy. In this position paper, we review the research challenges in building personal Databoxes that hold personal data and enable data access by other parties, and potentially thus sharing of data with other parties. These Databoxes are expected to become a core part of future data marketplaces., Comment: Accepted for Transactions on Emerging Telecommunications Technologies

The increasing generation and collection of personal data has created a complex ecosystem, often collaborative but sometimes combative, around companies and individuals engaging in the use of these data. We propose that the interactions between these agents warrants a new topic of study: Human-Data Interaction (HDI). In this paper we discuss how HDI sits at the intersection of various disciplines, including computer science, statistics, sociology, psychology and behavioural economics. We expose the challenges that HDI raises, organised into three core themes of legibility, agency and negotiability, and we present the HDI agenda to open up a dialogue amongst interested parties in the personal and big data ecosystems.