Dr Constantin Catalin Dragan


Biography

Areas of specialism

applied cryptography; provable security; formal verification; electronic voting

My publications

Publications

Catalin Dragan, Mark Manulis (2020)Bootstrapping Online Trust: Timeline Activity Proofs, In: Data Privacy Management, Cryptocurrencies and Blockchain Technology SpringerLink

Establishing initial trust between a new user and an online service, is being generally facilitated by centralized social media platforms, i.e., Facebook, Google, by allowing users to use their social profiles to prove “trustworthiness” to a new service which has some verification policy with regard to the information that it retrieves from the profiles. Typically, only static information, e.g., name, age, contact details, number of friends, are being used to establish the initial trust. However, such information provides only weak trust guarantees, as (malicious) users can trivially create new profiles and populate them with static data fast to convince the new service. We argue that the way the profiles are used over (longer) periods of time should play a more prominent role in the initial trust establishment. Intuitively, verification policies, in addition to static data, could check whether profiles are being used on a regular basis and have a convincing footprint of activities over various periods of time to be perceived as more trustworthy. In this paper, we introduce Timeline Activity Proofs (TAP) as a new trust factor. TAP allows online users to manage their timeline activities in a privacy-preserving way and use them to bootstrap online trust, e.g., as part of registration to a new service. In our model we do not rely on any centralized social media platform. Instead, users are given full control over the activities that they wish to use as part of TAP proofs. A distributed public ledger is used to provide the crucial integrity guarantees, i.e., that activities cannot be tampered with retrospectively. Our TAP construction adopts standard cryptographic techniques to enable authorized access to encrypted activities of a user for the purpose of policy verification and is proven to provide data confidentiality protecting the privacy of user’s activities and authenticated policy compliance protecting verifiers from users who cannot show the required footprint of past activities.

Catalin Dragan, Daniel Gardham, Mark Manulis (2020)Hierarchical Attribute-based Signatures, In: International Conference on Cryptology and Network Security Springer Nature

Attribute-based Signatures (ABS) are a powerful tool allowing users with attributes issued by authorities to sign messages while also proving that their attributes satisfy some policy. ABS schemes provide a exible and privacy-preserving approach to authentication since the signer's identity and attributes remain hidden within the anonymity set of users sharing policy-conform attributes. Current ABS schemes exhibit some limitations when it comes to the management and issue of attributes. In this paper we address the lack of support for hierarchical attribute management, a property that is prevalent in traditional PKIs where certication authorities are organised into hierarchies and signatures are veried along roots of trust. Hierarchical Attribute-based Signatures (HABS) introduced in this work support delegation of attributes along paths from the top-level authority down to the users while also ensuring that signatures produced by these users do not leak their delegation paths, thus extending the original privacy guarantees of ABS schemes. Our generic HABS construction also ensures unforgeability of signatures in the presence of collusion attacks and contains an extended traceability property allowing a dedicated tracing authority to identify the signer and reveal its attribute delegation paths. We include a public verication procedure for the accountability of the tracing authority. We anticipate that HABS will be useful for privacy-preserving authentication in applications requiring hierarchical delegation of attribute-issuing rights and where knowledge of delegation paths might leak information about signers and their attributes, e.g., in intelligent transport systems where vehicles may require certain attributes to authenticate themselves to the infrastructure but remain untrackable by the latter.

Véronique Cortier, Constantin Cătălin Dragan, Francois Dupressoir, Bogdan Warinschi (2018)Machine-checked proofs for electronic voting: privacy and verifiability for Belenios, In: Proceedings of the 31st IEEE Computer Security Foundations Symposium Institute of Electrical and Electronics Engineers (IEEE)

We present a machine-checked security analysis of Belenios – a deployed voting protocol used already in more than 200 elections. Belenios extends Helios with an explicit registration authority to obtain eligibility guarantees. We offer two main results. First, we build upon a recent framework for proving ballot privacy in EasyCrypt. Inspired by our application to Belenios, we adapt and extend the privacy security notions to account for protocols that include a registration phase. Our analysis identifies a trust assumption which is missing in the existing (pen and paper) analysis of Belenios: ballot privacy does not hold if the registrar misbehaves, even if the role of the registrar is seemingly to provide eligibility guarantees. Second, we develop a novel framework for proving strong verifiability in EasyCrypt and apply it to Belenios. In the process, we clarify several aspects of the pen-and-paper proof, such as how to deal with revote policies. Together, our results yield the first machine-checked analysis of both ballot privacy and verifiability properties for a deployed electronic voting protocol. Perhaps more importantly, we identify several issues regarding the applicability of existing definitions of privacy and verifiability to systems other than Helios. While we show how to adapt the definitions to the particular case of Belenios, our findings indicate the need for more general security notions for electronic voting protocols with registration authorities.

We introduce Biometric-Authenticated Keyword Search (BAKS), a novel searchable encryption scheme that relieves clients from managing cryptographic keys and relies purely on client's biometric data for authenticated outsourcing and retrieval of files indexed by encrypted keywords. BAKS utilises distributed trust across two servers and the liveness assumption which models physical presence of the client; in particular, BAKS security is guaranteed even if clients' biometric data, which often has low entropy, becomes public. We formalise two security properties, Authentication and Indistinguisha-bility against Chosen Keyword Attacks, which ensure that only a client with a biometric input sufficiently close to the registered template is considered legitimate and that neither of the two servers involved can learn any information about the encrypted keywords. Our BAKS construction further supports outsourcing and retrieval of files using multiple keywords and flexible search queries (e.g., conjunction, disjunction and subset-type queries). An additional update mechanism allows clients to replace their registered biometrics without requiring re-encryption of outsourced keywords , which enables smooth user migration across devices supporting different types of biometrics.

Constantin-Catalin Dragan, Daniel Gardham, Mark Manulis (2018)Hierarchical Attribute-based Signatures. 17th International Conference, CANS 2018, Naples, Italy, September 30 – October 3, 2018, In: Cryptology and Network Security. CANS 2018. Lecture Notes in Computer Science11124pp. 212-234 Springer Verlag

Attribute-based Signatures (ABS) are a powerful tool allowing users with attributes issued by authorities to sign messages while also proving that their attributes satisfy some policy. ABS schemes provide a exible and privacy-preserving approach to authentication since the signer's identity and attributes remain hidden within the anonymity set of users sharing policy-conform attributes. Current ABS schemes exhibit some limitations when it comes to the management and issue of attributes. In this paper we address the lack of support for hierarchical attribute management, a property that is prevalent in traditional PKIs where certification authorities are organised into hierarchies and signatures are verified along roots of trust. Hierarchical Attribute-based Signatures (HABS) introduced in this work support delegation of attributes along paths from the top-level authority down to the users while also ensuring that signatures produced by these users do not leak their delegation paths, thus extending the original privacy guarantees of ABS schemes. Our generic HABS construction also ensures unforgeability of signatures in the presence of collusion attacks and contains an extended traceability property allowing a dedicated tracing authority to identify the signer and reveal its attribute delegation paths. We include a public verification procedure for the accountability of the tracing authority. We anticipate that HABS will be useful for privacy-preserving authentication in applications requiring hierarchical delegation of attribute-issuing rights and where knowledge of delegation paths might leak information about signers and their attributes, e.g., in intelligent transport systems where vehicles may require certain attributes to authenticate themselves to the infrastructure but remain untrackable by the latter.

Yifan Yang, Daniel Cooper, John Collomosse, Catalin Dragan, Mark Manulis, Jo Briggs, Jamie Steane, Arthi Manohar, Wendy Moncur, Helen Jones (2020)TAPESTRY: A De-centralized Service for Trusted Interaction Online, In: IEEE Transactions on Services Computingpp. 1-1 Institute of Electrical and Electronics Engineers (IEEE)

We present a novel de-centralised service for proving the provenance of online digital identity, exposed as an assistive tool to help non-expert users make better decisions about whom to trust online. Our service harnesses the digital personhood (DP); the longitudinal and multi-modal signals created through users' lifelong digital interactions, as a basis for evidencing the provenance of identity. We describe how users may exchange trust evidence derived from their DP, in a granular and privacy-preserving manner, with other users in order to demonstrate coherence and longevity in their behaviour online. This is enabled through a novel secure infrastructure combining hybrid on- and off-chain storage combined with deep learning for DP analytics and visualization. We show how our tools enable users to make more effective decisions on whether to trust unknown third parties online, and also to spot behavioural deviations in their own social media footprints indicative of account hijacking.