Richard Mortier

• PhD
• Lecturer at University of Cambridge

Software services are increasingly migrating to the cloud, requiring trust in actors with direct access to the hardware, software and data comprising the service. A distributed datastore storing critical data sits at the core of many services; a prime example being etcd in Kubernetes. Trusted execution environments can secure this data from cloud p...

Application tail latency is a key metric for many services, with high latencies being linked directly to loss of revenue. Modern deeply-nested micro-service architectures exacerbate tail latencies, increasing the likelihood of users experiencing them. In this work, we show how CPU overcommitment by OS threads leads to high tail latencies when appli...

As the prevalence of Internet-of-Things (IoT) devices becomes more and more dominant, so too do the associated management and security challenges. One such challenge is the exploitation of vulnerable devices for recruitment into botnets, which can be used to carry out Distributed Denial-of-Service (DDoS) attacks. The recent Manufacturer Usage Descr...

The report describes the digital architecture developed for the West Cambridge Digital Twin, particularly focussed on real-time sensor data collection and analysis with a privacy framework allowing occupants of the buildings to be first-class participants in the system. The implementation has some notable characteristics. In particular 'push' techn...

In this chapter we turn to another indispensable tool in data analysis: statistics. Statistical analysis enables us to gain insight from data, and we group the statistical functions in Owl into three topics: descriptive statistics, distributions, and hypothesis testing. In this chapter we introduce how these basic statistics are supported in OCaml.

Regression is an important topic in statistical modelling and machine learning. It’s about modelling problems which include one or more variables (also called “features” or “predictors”) and require us to make predictions of another variable (“output variable”) based on previous values of the predictors. Regression analysis includes a wide range of...

Dominant media types on the Internet include images, audio, video, and text. Many day-to-day tasks involve analysis of text and Natural Language Processing (NLP) is a powerful tool for extracting insights from text corpora. NLP is a very large topic with many interesting challenges. In this chapter we focus on information retrieval and specifically...

Differentiation is core to many scientific applications including maximising or minimising functions, solving systems of ODEs, and non-linear optimisation such as KKT optimality conditions. Algorithmic differentiation (AD) is a computerfriendly technique for performing differentiation that is both efficient and accurate. A recent important applicat...

We begin our journey into the world of scientific computing. The most basic building block of any numerical computing library is a series of mathematical calculation functions. In this chapter, we introduce implementing two key mathematical techniques when working with functions: interpolation and integration. We present some key techniques, and sh...

The N-dimensional array is the fundamental building block in numerical computing libraries e.g., NumPy and SciPy. It is the core dense data structure and many advanced numerical functions are built on top of it, including linear algebra, optimisation, and algorithmic differentiation. In fact, the rest of this book is built upon it. In this chapter,...

A differential equation is an equation that contains a function and one or more of its derivatives. They have been studied ever since the invention of calculus, driven by applications in fields including mechanics [1], astronomy [2], geometry [3], biology [4], engineering [5], economics [6], and many more. If the function and its derivatives in a d...

In this chapter, we will build a search engine Sofia using latent semantic analysis. Sofia is a content-based filtering system that captures the semantics contained in the unstructured web text. Sofia looks for similar articles in a text corpus when a query document arrives. You will find that much of the basic theory has been covered in Chap. 12....

Optimisation is one of the most fundamental areas of numerical computing. From simple root finding to advanced machine learning, optimisation is everywhere. In this chapter, we will give you a brief overview of this topic and how the OCaml numerical library, Owl, supports basic optimisation methods.

Howcan a computer take an image and answer questions like “is there a cat or a dog in this picture?” In recent years the machine learning community has made tremendous progress in tackling this problem. In particular, Deep Neural Networks (DNN) are able to achieve extraordinary performance on visual recognition tasks, matching or even exceeding hum...

Computer vision is a field that automates tasks such as ascribing highlevel descriptions to images and videos. It has been applied to a wide variety of domains ranging from the highly technical such as automatic tagging of satellite images or analysis of medical imaging [1] [2], to the more mundane such as categorising pictures in your phone or cre...

We rely on signals such as sound and images to convey information. Signal processing is the field concerned with analysing, generating, and transforming signals. Its applications can be found in a wide range of fields: audio processing, speech recognition, image processing, communication system, data science, etc. In this chapterwe focus on Fourier...

Linear algebra is an important area of mathematics and has many applications in numerical computing. In this chapter we first present an overview, and then focus on how to use OCaml to solve concrete problems and develop a thorough understanding of the key concepts in linear algebra. This chapter covers the classic topics in linear algebra, includi...

Originally conceived as far back as the 1940s, neural networks have received a lot of attention in recent years due to frequently astounding results. In this chapter, we will demonstrate step by step how to build up a practical neural network module with what we have learned so far, especially algorithmic differentiation, optimisation, and regressi...

Neural Style Transfer (NST) is an exciting DNN-based application that creates arts. In this chapter we introduce this application in detail: its theory, the implementation, and examples of its use. NST is has been extended in many ways, one of which is the fast style transfer, and we also introduce how this application works with examples.

Machine Learning (ML) techniques have begun to dominate data analytics applications and services. Recommendation systems are a key component of online service providers. The financial industry has adopted ML to harness large volumes of data in areas such as fraud detection, risk-management, and compliance. Deep Learning is the technology behind voi...

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...

With the massive amount of data generated from mobile devices and the increase of computing power of edge devices, the paradigm of Federated Learning has attracted great momentum. In federated learning, distributed and heterogeneous nodes collaborate to learn model parameters. However, while providing benefits such as privacy by design and reduced...

Internet-of-Things (IoT) devices are known to be the source of many security problems, and as such, they would greatly benefit from automated management. This requires robustly identifying devices so that appropriate network security policies can be applied. We address this challenge by exploring how to accurately identify IoT devices based on thei...

Building Management Systems (BMSs) have evolved in recent years, in ways that require changes to existing network architectures that follow the store-then-analyse approach. The primary cause is the increasing deployment of a diverse range of cost-effective sensors and actuators in smart buildings that generate real-time streaming data. Any in-build...

Legacy Building Information Modelling (BIM) systems are not designed to process the high-volume, high-velocity data emitted by in-building Internet-of-Things (IoT) sensors. Historical lack of consideration for the real-time nature of such data means that outputs from such BIM systems typically lack the timeliness necessary for enacting decisions as...

The extant Information Management literature highlights the asymmetric distribution of power between users and online platforms, while the issues related to the stewardship of personal data on such platforms remain problematic and largely unresolved. To address that lacuna, we propose a conceptual design that can help to overcome many of the challe...

Internet-of-Things (IoT) devices are known to be the source of many security problems, and as such they would greatly benefit from automated management. This requires robustly identifying devices so that appropriate network security policies can be applied. We address this challenge by exploring how to accurately identify IoT devices based on their...

Edge computing and Federated Learning (FL) can work in tandem to address issues related to privacy and collaborative distributed learning in untrusted IoT environments. However, deployment of FL in resource-constrained IoT devices faces challenges including asynchronous participation of such devices in training, and the need to prevent malicious de...

Edge computing and Federated Learning (FL) can work in tandem to address issues related to privacy and collaborative distributed learning in untrusted IoT environments. However, deployment of FL in resource-constrained IoT devices faces challenges including asynchronous participation of such devices in training, and the need to prevent malicious de...

Internet-of-things (IoT) enabled smart build environments are an accurate representation of complex and dynamical systems. The diversity and heterogeneity of components in the IoT, not only make the ecosystem extremely difficult to analyse and validate but also make it hard to build both secure and accountable. To address these issues, the Internet...

As more and more devices are connected to the Internet-of-Things, often made by non-specialist companies or short-lived startups, the likelihood that these devices will be hacked and used for nefarious activity online increases. We seek to support non-expert users in managing the network behaviour of their IoT devices, and assisting them in handlin...

Compiling applications as unikernels allows them to be tailored to diverse execution environments. Dependency on a monolithic operating system is replaced with linkage against libraries that provide specific services. Doing so in practice has revealed a major barrier: managing the configuration matrix across heterogenous execution targets. A realis...

Code executing on the edge needs to run on hardware platforms that feature different memory architectures, virtualization extensions, and using a range of security features. Forcing application code to conform to a monolithic API such as POSIX, or ABI such as Linux, ties developers into large, complex platforms that make it difficult to use such ha...

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...

We continue to see increasingly widespread deployment of IoT devices, with apparent intent to embed them in our built environment likely to accelerate if smart city and related programmes succeed. In this paper we are concerned with the ways in which current generation IoT devices are being designed in terms of their ill-considered dependencies on...

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 commu...

Emerging Machine Learning (ML) techniques, such as Deep Neural Network, are widely used in today's applications and services. However, with social awareness of privacy and personal data rapidly rising, it becomes a pressing and challenging societal issue to both keep personal data private and benefit from the data analytics power of ML techniques a...

Occupancy modelling for efficient energy management of indoor spaces has gained significant recent attention. Unfortunately, many such models rely on copying sensor data to the cloud for third-party services to process, creating risks of privacy breach. Such matters have become particularly pertinent for companies handling data of EU citizens due t...

Data analytics on edge devices has gained rapid growth in research, industry, and different aspects of our daily life. This topic still faces many challenges such as limited computation resource on edge devices. In this paper, we further identify two main challenges: the composition and deployment of data analytics services on edge devices. We pres...

Access control is central to interfacing with personal data, however most systems today are too coarse and disconnected from the privacy context of the data. Granular access control rarely goes beyond limiting sample rates or enforcing time limits. In this paper, we present a system for tuning a data consumer's access to personal data based on real...

Data analytics on edge devices has gained rapid growth in research, industry, and different aspects of our daily life. This topic still faces many challenges such as limited computation resource on edge devices. In this paper, we further identify two main challenges: the composition and deployment of data analytics services on edge devices. We pres...

This paper outlines the IoT Databox model as a means of making the Internet of Things (IoT) accountable to individuals. Accountability is a key to building consumer trust and is mandated by the European Union’s General Data Protection Regulation (GDPR). We focus here on the ‘external’ data subject accountability requirement specified by GDPR and ho...

Internet-connected devices are increasingly present in our homes, and privacy breaches, data thefts, and security threats are becoming commonplace. In order to avoid these, we must first understand the behaviour of these devices. In this work, we analyse network traces from a testbed of common IoT devices, and describe general methods for fingerpri...

Machine Learning (ML) techniques, such as Neural Network, are widely used in today's applications. However, there is still a big gap between the current ML systems and users' requirements. ML systems focus on the improve the performance of models in training, while individual users cares more about response time and expressiveness of the tool. Many...

2017 ACM. everyday artefacts. This involves adorning them with decorative patterns that enhance their beauty while triggering digital interactions when scanned with cameras. These are realized using an existing augmented reality technique that embeds computer readable codes into the topological structures of hand-drawn patterns. We describe a resea...

...While current industry solutions largely put emphasis on encryption as a privacy-preserving measure, there is more to privacy than the confidentiality of data at rest or in motion [7]. Furthermore, encryption often will not stop industry accessing personal data [13], and metadata can be as or more revealing than data itself [1]. Thus, in conside...

The long-heralded Internet of Things (IoT) is finally becoming a reality. From factories and the ubiquitous Internet-connected fridge, we now see heating control systems, cars, dishwashers, and all manner of common-place devices being connected. While this has certainly realized new capabilities, such as the ability to control one’s domestic heatin...

As locative media and augmented reality spread into the everyday world so it becomes important to create aesthetic visual markers at scale. We explore a designer-centred approach in which skilled designers handcraft seed designs that are automatically recombined to create many markers as subtle variants of a common theme. First, we extend the d-tou...

The capacity and programmability of reconfigurable hardware such as FPGAs has improved steadily over the years, but they do not readily provide any mechanisms for monitoring or debugging running programs. Such mechanisms need to be written into the program itself. This is done using ad hoc methods and primitive tools when compared to CPU programmin...

The capacity and programmability of reconfigurable hardware such as FPGAs has improved steadily over the years, but they do not readily provide any mechanisms for monitoring or debugging running programs. Such mechanisms need to be written into the program itself. This is done using ad hoc methods and primitive tools when compared to CPU programmin...

The Internet of Things, alongside existing mobile digital technologies, heralds a world in which pervasive sensing constantly captures data about us. Simultaneous with this technology programme are moves by policymakers to shore up the digital economy through the legislating of new trust-building models of data management. These moves seek to give...

This paper outlines the IoT Databox model as a means of making the Internet of Things (IoT) accountable to individuals. Accountability is a key to building consumer trust and mandated in data protection legislation. We briefly outline the ‘external’ data subject accountability requirement specified in actual legislation in Europe and proposed legis...

Many current Internet services rely on inferences from models trained on user data. Commonly, both the training and inference tasks are carried out using cloud resources fed by personal data collected at scale from users. Holding and using such large collections of personal data in the cloud creates privacy risks to the data subjects, but is curren...

We explore the crafting of interactive decoration for everyday artefacts. This involves adorning them with decorative patterns that enhance their beauty while triggering digital interactions when scanned with cameras. These are realised using an existing augmented reality technique that embeds computer readable codes into the topological structures...

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 da...

We are all increasingly the subjects of data collection and processing systems that use data generated both about and by us to provide and optimise a wide range of services. Means for others to collect and process data that concerns each of us -- often referred to possessively as "your data" -- are only increasing with the long-heralded advent of t...

We are all increasingly the subjects of data collection and processing systems that use data generated both about and by us to provide and optimise a wide range of services. Means for others to collect and process data that concerns each of us – often referred to possessively as “your data” – are only increasing with the long-heralded advent of the...

We focus on the challenges and issues associated with Big Data, and propose a novel architecture that uses the principles of Separation of Concerns and distributed computing to overcome many of the challenges associated with storage, analysis and integrity. We address the issue of asymmetrical distribution of power between the originators of data a...

This paper offers a sociological perspective on data protection regulation and its relevance to design. From this perspective, proposed regulation in Europe and the USA seeks to create a new economic actor—the consumer as personal data trader—through new legal frameworks that shift the locus of agency and control in data processing towards the indi...

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 da...

We have moved from a world where computing is siloed and specialised, to a world where computing is ubiquitous and everyday. In many, if not most, parts of the world, networked computing is now mundane as both foreground (e.g., smartphones, tablets) and background (e.g., road tra c management, financial systems) technologies. This has permitted, an...

In recent times, we have seen a proliferation of personal data. This can be attributed not just to a larger proportion of our lives moving online, but also through the rise of ubiquitous sensing through mobile and IoT devices. Alongside this surge, concerns over privacy, trust, and security are expressed more and more as different parties attempt t...

Data centre networks are increasingly programmable, with $\textit{application-specific}$ network services proliferating, from custom load-balancers to middleboxes providing caching and aggregation. Developers must currently implement these services using traditional low-level APIs, which neither support natural operations on application data nor pr...

We present a research-through-design exploration of transforming large-scale public illustrations into interactive media. We collaborated with creative practitioners to extend an existing visual marker technology to support spatial and layered interaction with wall-sized images. We document how these techniques were used to design interactive illus...

Online copyright law is a major issue for many in the creative industries. Independent artists often rely on sharing their work across social media and content-sharing sites, leaving them open to having their work stolen or misused. This paper discusses a series of 11 semi-structured interviews that examined attitudes towards copyright and attribut...

Drawing on the experiences of a novel collaborative project between sociologists and computer scientists, this paper identifies a set of challenges for fieldwork that are generated by this wild interdisciplinarity. Public Access Wi-Fi Service was a project funded by an ‘in-the-wild’ research programme, involving the study of digital technologies wi...

User tracking has become de facto practice of the Web, however, our understanding of the scale and nature of this practice remains rudimentary. In this paper, we explore the connections amongst all parties of the Web, especially focusing on how trackers share user IDs. Using data collected from both browsing histories of 129 users and active experi...

We present a research-through-design exploration of transforming large-scale public illustrations into interactive media. We collaborated with creative practitioners to extend an existing visual marker technology to support spatial and layered interaction with wall-sized images. We document how these techniques were used to design interactive illus...

This paper investigates the playful photo taking behaviour of teenagers during group visits to two touristic public events (an airshow and a guided tour of a museum). These studies provide the feedback for the iterative development of a smartphone based anonymous image annotation and sharing application. The resulting implications for the design of...

Human Data Interaction (HDI) is an emerging field of research that seeks to support end-users in the day-to-day management of their personal digital data. This is a programmatic paper that seeks to elaborate foundational challenges that face HDI from an interactional perspective. It is rooted in and reflects foundational lessons from social studies...

We argue that the current approaches to online social networking give rise to numerous challenges regarding the management of the multiple facets of people’s digital identities within and around social networking sites (SNS). We propose an architecture for enabling people to better manage their SNS identities that is informed by the way the core In...

We argue that the current approaches to online social networking give rise to numerous challenges regarding the management of the multiple facets of people’s digital identities within and around social networking sites (SNS). We propose an architecture for enabling people to better manage their SNS identities that is informed by the way the core In...

This is the author accepted manuscript. The final version is available from USENIX via https://www.usenix.org/conference/nsdi15/technical-sessions/presentation/madhavapeddy

Online social networks are complex systems that can be variously construed as websites, platforms and communities but relatively rarely are they considered from the perspective of a goal-directed user. A mixed methods study consisting of questionnaires and in-depth interviews was carried out in order to examine the use of social networking within t...

We propose there is a need for a technical platform enabling people to engage with the collection, management and consumption of personal data; and that this platform should itself be personal, under the direct control of the individual whose data it holds. In what follows, we refer to this platform as the Databox, a personal, networked service tha...

We draw on ethnographic studies to understand the collaborative nature of network policies or rules in domestic settings. We outline the technical nature of network policy in enterprise domains and how this contrasts with the social or collaborative nature of rules in everyday life. We then consider the deployment of network control and policy syst...

Universal Internet access has become critical to modern life, leading to many explorations of approaches to increase its availability. In this paper we report on a study of one such approach, PAWS, that seeks to understand the technical and social constraints of providing Internet access, free at the point of use, by sharing existing broadband subs...

Universal Internet access has become critical to modern life, leading to many explorations of approaches to increase its availability. In this paper we report on a study of one such approach, PAWS, that seeks to understand the technical and social constraints of providing Internet access, free at the point of use, by sharing existing broadband subs...

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 HD...