How Physicality Enables Trust: A New Era of Trust-Centered Cyberphysical Systems

Multi-agent cyberphysical systems enable new capabilities in efficiency, resilience, and security. The unique characteristics of these systems prompt a reevaluation of their security concepts, including their vulnerabilities, and mechanisms to mitigate these vulnerabilities. This survey paper examines how advancement in wireless networking, coupled with the sensing and computing in cyberphysical systems, can foster novel security capabilities. This study delves into three main themes related to securing multi-agent cyberphysical systems. First, we discuss the threats that are particularly relevant to multi-agent cyberphysical systems given the potential lack of trust between agents. Second, we present prospects for sensing, contextual awareness, and authentication, enabling the inference and measurement of ``inter-agent trust" for these systems. Third, we elaborate on the application of quantifiable trust notions to enable ``resilient coordination," where ``resilient" signifies sustained functionality amid attacks on multiagent cyberphysical systems. We refer to the capability of cyberphysical systems to self-organize, and coordinate to achieve a task as autonomy. This survey unveils the cyberphysical character of future interconnected systems as a pivotal catalyst for realizing robust, trust-centered autonomy in tomorrow's world

Combating Attacks and Abuse in Large Online Communities

Internet users today are connected more widely and ubiquitously than ever before. As a result, various online communities are formed, ranging from online social networks (Facebook, Twitter), to mobile communities (Foursquare, Waze), to content/interests based networks (Wikipedia, Yelp, Quora). While users are benefiting from the ease of access to information and social interactions, there is a growing concern for users' security and privacy against various attacks such as spam, phishing, malware infection and identity theft. Combating attacks and abuse in online communities is challenging. First, today’s online communities are increasingly dependent on users and user-generated content. Securing online systems demands a deep understanding of the complex and often unpredictable human behaviors. Second, online communities can easily have millions or even billions of users, which requires the corresponding security mechanisms to be highly scalable. Finally, cybercriminals are constantly evolving to launch new types of attacks. This further demands high robustness of security defenses. In this thesis, we take concrete steps towards measuring, understanding, and defending against attacks and abuse in online communities. We begin with a series of empirical measurements to understand user behaviors in different online services and the uniquesecurity and privacy challenges that users are facing with. This effort covers a broad set of popular online services including social networks for question and answering (Quora), anonymous social networks (Whisper), and crowdsourced mobile communities (Waze). Despite the differences of specific online communities, our study provides a first look at their user activity patterns based on empirical data, and reveals the need for reliable mechanisms to curate user content, protect privacy, and defend against emerging attacks. Next, we turn our attention to attacks targeting online communities, with focus on spam campaigns. While traditional spam is mostly generated by automated software, attackers today start to introduce "human intelligence" to implement attacks. This is maliciouscrowdsourcing (or crowdturfing) where a large group of real-users are organized to carry out malicious campaigns, such as writing fake reviews or spreading rumors on social media. Using collective human efforts, attackers can easily bypass many existing defenses (e.g.,CAPTCHA). To understand the ecosystem of crowdturfing, we first use measurements to examine their detailed campaign organization, workers and revenue. Based on insights from empirical data, we develop effective machine learning classifiers to detect crowdturfingactivities. In the meantime, considering the adversarial nature of crowdturfing, we also build practical adversarial models to simulate how attackers can evade or disrupt machine learning based defenses. To aid in this effort, we next explore using user behavior models to detect a wider range of attacks. Instead of making assumptions about attacker behavior, our idea is to model normal user behaviors and capture (malicious) behaviors that are deviated from norm. In this way, we can detect previously unknown attacks. Our behavior model is based on detailed clickstream data, which are sequences of click events generated by users when using the service. We build a similarity graph where each user is a node and the edges are weightedby clickstream similarity. By partitioning this graph, we obtain "clusters" of users with similar behaviors. We then use a small set of known good users to "color" these clusters to differentiate the malicious ones. This technique has been adopted by real-world social networks (Renren and LinkedIn), and already detected unexpected attacks. Finally, we extend clickstream model to understanding more-grained behaviors of attackers (and real users), and tracking how user behavior changes over time. In summary, this thesis illustrates a data-driven approach to understanding and defending against attacks and abuse in online communities. Our measurements have revealed new insights about how attackers are evolving to bypass existing security defenses today. Inaddition, our data-driven systems provide new solutions for online services to gain a deep understanding of their users, and defend them from emerging attacks and abuse

Transparent, trustworthy and privacy-preserving supply chains

Over the years, supply chains have evolved from a few regional traders to globally complex chains of trade. Consequently, supply chain management systems have become heavily dependent on digitization for the purpose of data storage and traceability of goods. However, these traceability systems suffer from issues such as scattering of information across multiple silos and susceptibility of erroneous or modified data and thus are often unable to provide reliable information about a product. Due to propriety reasons, often end-to-end traceability is not available to the general consumer. The second issue is ensuring the credibility of the collated information about a product. The digital data may not be the true representation of the physical events which raises the issues of trusting the available information. If the source of digital data is not trustworthy, the provenance or traceability of a product becomes questionable. The third issue in supply chain management is a trade-off between the provenance information and protection of this data. The information is often associated with the identity of the contributing entity to ensure trust. However, the identity association makes it difficult to protect trade secrets such as shipments, pricing, and trade frequency of traders while simultaneously ensuring the provenance/traceability to the consumers. Our work aims to address above mentioned challenges related to traceability, trustworthiness and privacy. To support traceability and provenance, a consortium blockchain based framework, ProductChain, is proposed which provides an immutable audit trail of the supply chain events pertaining to the product and its origin. The framework also presents a sharded network model to meet the scalability needs of complex supply chains. Simulation results for our Proof of Concept (PoC) implementation show that query time for retrieving end-to-end traceability is of the order of a few milliseconds even when the information is collated from multiple regional blockchains. Next, to ensure the credibility of data from the supply chain entities, it is important to have an accountability mechanism which can penalise or reward the entities for their dishonest or honest contributions, respectively. We propose the TrustChain framework, which calculates a trust score for data contributing entities to the blockchain using multiple observations. These observations include feedback from interactions among supply chain entities, inputs from third party regulators and readings from IoT sensors. The integrated reputation system with blockchain, dynamically assigns trust and reputation scores to commodities and traders using smart contracts. A PoC implementation over Hyperledger Fabric shows that TrustChain incurs minimal overheads over a baseline. For protecting trade secrets while simultaneously ensuring traceability, PrivChain is proposed. PrivChain's framework allows traders to share computation or proofs in support of provenance and traceability claims rather than sharing the data itself. The framework also proposes an integrated incentive mechanism for traders providing such proofs. A PoC implementation on Hyperledger Fabric reveals a minimal overhead of using PrivChain as the data related computations are carried off-chain. Finally, we propose TradeChain which addresses the issue of preserving the privacy of identity related information with the blockchain data and gives greater access control to the data owners, i.e. traders. This framework decouples the identities of traders by managing two ledgers: one for managing decentralised identities and another for recording supply chain events. The information from both ledgers is then collated using access tokens provided by the data owners. In this way, they can dynamically control access to the blockchain data at a granular level. A PoC implementation is developed both on Hyperledger Indy and Fabric and we demonstrate minimal overheads for the different components of TradeChain

Combating Software and Sybil Attacks to Data Integrity in Crowd-Sourced Embedded Systems

Crowd-sourced mobile embedded systems allow people to contribute sensor data, for critical applications, including transportation, emergency response and eHealth. Data integrity becomes imperative as malicious participants can launch software and Sybil attacks modifying the sensing platform and data. To address these attacks, we develop (1) a Trusted Sensing Peripheral (TSP) enabling collection of high-integrity raw or aggregated data, and participation in applications requiring additional modalities; and (2) a Secure Tasking and Aggregation Protocol (STAP) enabling aggregation of TSP trusted readings by untrusted intermediaries, while efficiently detecting fabricators. Evaluations demonstrate that TSP and STAP are practical and energy-efficient

FinBook: literary content as digital commodity

This short essay explains the significance of the FinBook intervention, and invites the reader to participate. We have associated each chapter within this book with a financial robot (FinBot), and created a market whereby book content will be traded with financial securities. As human labour increasingly consists of unstable and uncertain work practices and as algorithms replace people on the virtual trading floors of the worlds markets, we see members of society taking advantage of FinBots to invest and make extra funds. Bots of all kinds are making financial decisions for us, searching online on our behalf to help us invest, to consume products and services. Our contribution to this compilation is to turn the collection of chapters in this book into a dynamic investment portfolio, and thereby play out what might happen to the process of buying and consuming literature in the not-so-distant future. By attaching identities (through QR codes) to each chapter, we create a market in which the chapter can ‘perform’. Our FinBots will trade based on features extracted from the authors’ words in this book: the political, ethical and cultural values embedded in the work, and the extent to which the FinBots share authors’ concerns; and the performance of chapters amongst those human and non-human actors that make up the market, and readership. In short, the FinBook model turns our work and the work of our co-authors into an investment portfolio, mediated by the market and the attention of readers. By creating a digital economy specifically around the content of online texts, our chapter and the FinBook platform aims to challenge the reader to consider how their personal values align them with individual articles, and how these become contested as they perform different value judgements about the financial performance of each chapter and the book as a whole. At the same time, by introducing ‘autonomous’ trading bots, we also explore the different ‘network’ affordances that differ between paper based books that’s scarcity is developed through analogue form, and digital forms of books whose uniqueness is reached through encryption. We thereby speak to wider questions about the conditions of an aggressive market in which algorithms subject cultural and intellectual items – books – to economic parameters, and the increasing ubiquity of data bots as actors in our social, political, economic and cultural lives. We understand that our marketization of literature may be an uncomfortable juxtaposition against the conventionally-imagined way a book is created, enjoyed and shared: it is intended to be

Strategies for Unbridled Data Dissemination: An Emergency Operations Manual

This project is a study of free data dissemination and impediments to it. Drawing upon post-structuralism, Actor Network Theory, Participatory Action Research, and theories of the political stakes of the posthuman by way of Stirnerian egoism and illegalism, the project uses a number of theoretical, technical and legal texts to develop a hacker methodology that emphasizes close analysis and disassembly of existent systems of content control. Specifically, two tiers of content control mechanisms are examined: a legal tier, as exemplified by Intellectual Property Rights in the form of copyright and copyleft licenses, and a technical tier in the form of audio, video and text-based watermarking technologies. A series of demonstrative case studies are conducted to further highlight various means of content distribution restriction. A close reading of a copyright notice is performed in order to examine its internal contradictions. Examples of watermarking employed by academic e-book and journal publishers and film distributors are also examined and counter-forensic techniques for removing such watermarks are developed. The project finds that both legal and technical mechanisms for restricting the flow of content can be countervailed, which in turn leads to the development of different control mechanisms and in turn engenders another wave of evasion procedures. The undertaken methodological approach thus leads to the discovery of on-going mutation and adaptation of in-between states of resistance. Finally, an analysis of various existent filesharing applications is performed, and a new Tor-based BitTorrent tracker is set up to strengthen the anonymization of established filesharing methods. It is found that there exist potential de-anonymization attacks against all analyzed file-sharing tools, with potentially more secure filesharing options also seeing less user adoption

Parliament Buildings: The architecture of politics in Europe

As political polarisation undermines confidence in the shared values and established constitutional orders of many nations, it is imperative that we explore how parliaments are to stay relevant and accessible to the citizens whom they serve. The rise of modern democracies is thought to have found physical expression in the staged unity of the parliamentary seating plan. However, the built forms alone cannot give sufficient testimony to the exercise of power in political life. Parliament Buildings brings together architecture, history, art history, history of political thought, sociology, behavioural psychology, anthropology and political science to raise a host of challenging questions. How do parliament buildings give physical form to norms and practices, to behaviours, rituals, identities and imaginaries? How are their spatial forms influenced by the political cultures they accommodate? What kinds of histories, politics and morphologies do the diverse European parliaments share, and how do their political trajectories intersect? This volume offers an eclectic exploration of the complex nexus between architecture and politics in Europe. Including contributions from architects who have designed or remodelled four parliament buildings in Europe, it provides the first comparative, multi-disciplinary study of parliament buildings across Europe and across history