Taking Computation to Data: Integrating Privacy-preserving AI techniques and Blockchain Allowing Secure Analysis of Sensitive Data on Premise

PhD thesis in Information technologyWith the advancement of artificial intelligence (AI), digital pathology has seen significant progress in recent years. However, the use of medical AI raises concerns about patient data privacy. The CLARIFY project is a research project funded under the European Union’s Marie Sklodowska-Curie Actions (MSCA) program. The primary objective of CLARIFY is to create a reliable, automated digital diagnostic platform that utilizes cloud-based data algorithms and artificial intelligence to enable interpretation and diagnosis of wholeslide-images (WSI) from any location, maximizing the advantages of AI-based digital pathology. My research as an early stage researcher for the CLARIFY project centers on securing information systems using machine learning and access control techniques. To achieve this goal, I extensively researched privacy protection technologies such as federated learning, differential privacy, dataset distillation, and blockchain. These technologies have different priorities in terms of privacy, computational efficiency, and usability. Therefore, we designed a computing system that supports different levels of privacy security, based on the concept: taking computation to data. Our approach is based on two design principles. First, when external users need to access internal data, a robust access control mechanism must be established to limit unauthorized access. Second, it implies that raw data should be processed to ensure privacy and security. Specifically, we use smart contractbased access control and decentralized identity technology at the system security boundary to ensure the flexibility and immutability of verification. If the user’s raw data still cannot be directly accessed, we propose to use dataset distillation technology to filter out privacy, or use locally trained model as data agent. Our research focuses on improving the usability of these methods, and this thesis serves as a demonstration of current privacy-preserving and secure computing technologies

Tamper-Resistant Peer-to-Peer Storage for File Integrity Checking.

“... oba es gibt kan Kompromiß, zwischen ehrlich sein und link, a wann’s no so afoch ausschaut, und wann’s noch so üblich is...” — Wolfgang Ambros, 1975 One of the activities of most successful intruders of a computer system is to modify data on the victim, either to hide his/her presence and to destroy the evidence of the break-in, or to subvert the system completely and make it accessible for further abuse without triggering alarms. File integrity checking is one common method to mitigate the effects of successful intrusions by detecting the changes an intruder makes to files on a computer system. Historically file integrity checking has been implemented using tools that operate locally on a single system, which imposes quite some restrictions regarding maintenance and scalability. Recent improvements for large scale environments have introduced trusted central servers which provide secure fingerprint storage and logging facilities, but such centralism presents some new shortcomings

Federated Robust Embedded Systems: Concepts and Challenges

The development within the area of embedded systems (ESs) is moving rapidly, not least due to falling costs of computation and communication equipment. It is believed that increased communication opportunities will lead to the future ESs no longer being parts of isolated products, but rather parts of larger communities or federations of ESs, within which information is exchanged for the benefit of all participants. This vision is asserted by a number of interrelated research topics, such as the internet of things, cyber-physical systems, systems of systems, and multi-agent systems. In this work, the focus is primarily on ESs, with their specific real-time and safety requirements. While the vision of interconnected ESs is quite promising, it also brings great challenges to the development of future systems in an efficient, safe, and reliable way. In this work, a pre-study has been carried out in order to gain a better understanding about common concepts and challenges that naturally arise in federations of ESs. The work was organized around a series of workshops, with contributions from both academic participants and industrial partners with a strong experience in ES development. During the workshops, a portfolio of possible ES federation scenarios was collected, and a number of application examples were discussed more thoroughly on different abstraction levels, starting from screening the nature of interactions on the federation level and proceeding down to the implementation details within each ES. These discussions led to a better understanding of what can be expected in the future federated ESs. In this report, the discussed applications are summarized, together with their characteristics, challenges, and necessary solution elements, providing a ground for the future research within the area of communicating ESs

Mistrust: Ethnographic Approximations

Scholars have long seen trust as a foundational social good. We therefore have ample studies on building trust in free markets, on cultivating trust in the state, and on rebuilding trust through civil society. The contributors to this volume, instead, take a step back. They ask: Can mistrust ever be more than the flip side of trust, more than the sign of an absence or failure? By looking ethnographically at what a variety of actors actually do when they express mistrust, this volume offers a richly empirical trove of the social life of mistrust across a range of settings

Crowdsourcing atop blockchains

Traditional crowdsourcing systems, such as Amazon\u27s Mechanical Turk (MTurk), though once acquiring great economic successes, have to fully rely on third-party platforms to serve between the requesters and the workers for basic utilities. These third-parties have to be fully trusted to assist payments, resolve disputes, protect data privacy, manage user authentications, maintain service online, etc. Nevertheless, tremendous real-world incidents indicate how elusive it is to completely trust these platforms in reality, and the reduction of such over-reliance becomes desirable. In contrast to the arguably vulnerable centralized approaches, a public blockchain is a distributed and transparent global consensus computer that is highly robust. The blockchain is usually managed and replicated by a large-scale peer-to-peer network collectively, thus being much more robust to be fully trusted for correctness and availability. It, therefore, becomes enticing to build novel crowdsourcing applications atop blockchains to reduce the over-trust on third-party platforms. However, this new fascinating technology also brings about new challenges, which were never that severe in the conventional centralized setting. The most serious issue is that the blockchain is usually maintained in the public Internet environment with a broader attack surface open to anyone. This not only causes serious privacy and security issues, but also allows the adversaries to exploit the attack surface to hamper more basic utilities. Worse still, most existing blockchains support only light on-chain computations, and the smart contract executed atop the decentralized consensus computer must be simple, which incurs serious feasibility problems. In reality, the privacy/security issue and the feasibility problem even restrain each other and create serious tensions to hinder the broader adoption of blockchain. The dissertation goes through the non-trivial challenges to realize secure yet still practical decentralization (for urgent crowdsourcing use-cases), and lay down the foundation for this line of research. In sum, it makes the next major contributions. First, it identifies the needed security requirements in decentralized knowledge crowdsourcing (e.g., data privacy), and initiates the research of private decentralized crowdsourcing. In particular, the confidentiality of solicited data is indispensable to prevent free-riders from pirating the others\u27 submissions, thus ensuring the quality of solicited knowledge. To this end, a generic private decentralized crowdsourcing framework is dedicatedly designed, analyzed, and implemented. Furthermore, this dissertation leverages concretely efficient cryptographic design to reduce the cost of the above generic framework. It focuses on decentralizing the special use-case of Amazon MTurk, and conducts multiple specific-purpose optimizations to remove needless generality to squeeze performance. The implementation atop Ethereum demonstrates a handling cost even lower than MTurk. In addition, it focuses on decentralized crowdsourcing of computing power for specific machine learning tasks. It lets a requester place deposits in the blockchain to recruit some workers for a designated (randomized) programs. If and only if these workers contribute their resources to compute correctly, they would earn well-deserved payments. For these goals, a simple yet still useful incentive mechanism is developed atop the blockchain to deter rational workers from cheating. Finally, the research initiates the first systematic study on crowdsourcing blockchains\u27 full nodes to assist superlight clients (e.g., mobile phones and IoT devices) to read the blockchain\u27s records. This dissertation presents a novel generic solution through the powerful lens of game-theoretic treatments, which solves the long-standing open problem of designing generic superlight clients for all blockchains

The InfoSec Handbook

Computer scienc

Data Exfiltration:A Review of External Attack Vectors and Countermeasures

AbstractContext One of the main targets of cyber-attacks is data exfiltration, which is the leakage of sensitive or private data to an unauthorized entity. Data exfiltration can be perpetrated by an outsider or an insider of an organization. Given the increasing number of data exfiltration incidents, a large number of data exfiltration countermeasures have been developed. These countermeasures aim to detect, prevent, or investigate exfiltration of sensitive or private data. With the growing interest in data exfiltration, it is important to review data exfiltration attack vectors and countermeasures to support future research in this field. Objective This paper is aimed at identifying and critically analysing data exfiltration attack vectors and countermeasures for reporting the status of the art and determining gaps for future research. Method We have followed a structured process for selecting 108 papers from seven publication databases. Thematic analysis method has been applied to analyse the extracted data from the reviewed papers. Results We have developed a classification of (1) data exfiltration attack vectors used by external attackers and (2) the countermeasures in the face of external attacks. We have mapped the countermeasures to attack vectors. Furthermore, we have explored the applicability of various countermeasures for different states of data (i.e., in use, in transit, or at rest). Conclusion This review has revealed that (a) most of the state of the art is focussed on preventive and detective countermeasures and significant research is required on developing investigative countermeasures that are equally important; (b) Several data exfiltration countermeasures are not able to respond in real-time, which specifies that research efforts need to be invested to enable them to respond in real-time (c) A number of data exfiltration countermeasures do not take privacy and ethical concerns into consideration, which may become an obstacle in their full adoption (d) Existing research is primarily focussed on protecting data in ‘in use’ state, therefore, future research needs to be directed towards securing data in ‘in rest’ and ‘in transit’ states (e) There is no standard or framework for evaluation of data exfiltration countermeasures. We assert the need for developing such an evaluation framework

Framing online communications of civil and uncivil groups in post-conflict Northern Ireland

This thesis explores the ways in which civil and uncivil groups in Northern Ireland use the Internet to generate soft power. This research assesses whether the Internet creates a critical multiplier effect for marginal groups, such as terrorists and interface communities. A coding scheme, adapted from previous studies of political part websites, is used to determine whether these groups have realised the potential of the Internet as a tool for political mobilisation. The dissertation considers whether there are any qualitative differences between the online framing of terrorist-linked parties and the constitutional parties in the region. The phenomenon of amateur terrorism is also analysed through the lens of Loyalist and Republican solidarity actors. The analysis determines whether solidarity actors were more likely to justify political violence on their websites than their respective political fronts. In addition, the websites of rival residents’ groups are examined to determine whether the Internet can help generate social capital across sectarian interfaces. The analysis determines whether residents’ groups use the Web to strengthen in-group identities, or to engage in dialogue with rival interface communities. In doing so, the research tests the cyberoptimist assertion that the Internet will facilitate forms of communication that undermine unequal power relations within nation-states. The online audience for Northern Irish terrorists is modelled using Internet usage patterns and the ranking systems used by Internet search engines. Internet usage patterns are examined to define the potential audience available to Northern Irish terrorists via their websites. The study suggests that there is little to differentiate between the websites of terrorist-linked groups, such as Sinn Fein, and the websites of constitutional parties, such as the Social Democratic and Labour Party (SDLP). In contrast, Loyalist and Republican amateurs often use paramilitary insignias on their websites to demonstrate their opposition to the peace process. However, these websites do not constitute a new dimension of terrorist threat to the peace process. Analysis of residents’ group websites suggests that they further the competition of ‘victimhoods’ between Loyalist and Republican interface communities. Both sides use their web presence to claim that they were constantly under threat of attack from the community situated at the other side of the ‘peaceline.’ Moreover, the thesis suggests that there will be a limited online audience for both civil and uncivil actors in Northern Ireland. The online audience for these actors is likely to consist of Internet users who use the Web for political research and Loyalist and Republican supporters in the ‘offline’ world