Claudio Orlandi

CR
h-index3
5papers
566citations
Novelty65%
AI Score34

5 Papers

CRNov 30, 2024
Distributed Differentially Private Data Analytics via Secure Sketching

Jakob Burkhardt, Hannah Keller, Claudio Orlandi et al.

We introduce the linear-transformation model, a distributed model of differentially private data analysis. Clients have access to a trusted platform capable of applying a public matrix to their inputs. Such computations can be securely distributed across multiple servers using simple and efficient secure multiparty computation techniques. The linear-transformation model serves as an intermediate model between the highly expressive central model and the minimal local model. In the central model, clients have access to a trusted platform capable of applying any function to their inputs. However, this expressiveness comes at a cost, as it is often prohibitively expensive to distribute such computations, leading to the central model typically being implemented by a single trusted server. In contrast, the local model assumes no trusted platform, which forces clients to add significant noise to their data. The linear-transformation model avoids the single point of failure for privacy present in the central model, while also mitigating the high noise required in the local model. We demonstrate that linear transformations are very useful for differential privacy, allowing for the computation of linear sketches of input data. These sketches largely preserve utility for tasks such as private low-rank approximation and private ridge regression, while introducing only minimal error, critically independent of the number of clients.

GTSep 27, 2018
Sharing Information with Competitors

Simina Brânzei, Claudio Orlandi, Guang Yang

We study the mechanism design problem in the setting where agents are rewarded using information only. This problem is motivated by the increasing interest in secure multiparty computation techniques. More specifically, we consider the setting of a joint computation where different agents have inputs of different quality and each agent is interested in learning as much as possible while maintaining exclusivity for information. Our high level question is to design mechanisms that motivate all agents (even those with high-quality input) to participate in the computation and we formally study problems such as set union, intersection, and average.

CRFeb 11, 2016
Access Control Encryption: Enforcing Information Flow with Cryptography

Ivan Damgård, Helene Haagh, Claudio Orlandi

We initiate the study of Access Control Encryption (ACE), a novel cryptographic primitive that allows fine-grained access control, by giving different rights to different users not only in terms of which messages they are allowed to receive, but also which messages they are allowed to send. Classical examples of security policies for information flow are the well known Bell-Lapadula [BL73] or Biba [Bib75] model: in a nutshell, the Bell-Lapadula model assigns roles to every user in the system (e.g., public, secret and top-secret). A users' role specifies which messages the user is allowed to receive (i.e., the no read-up rule, meaning that users with public clearance should not be able to read messages marked as secret or top-secret) but also which messages the user is allowed to send (i.e., the no write-down rule, meaning that a user with top-secret clearance should not be able to write messages marked as secret or public). To the best of our knowledge, no existing cryptographic primitive allows for even this simple form of access control, since no existing cryptographic primitive enforces any restriction on what kind of messages one should be able to encrypt. Our contributions are: - Introducing and formally defining access control encryption (ACE); - A construction of ACE with complexity linear in the number of the roles based on classic number theoretic assumptions (DDH, Paillier); - A construction of ACE with complexity polylogarithmic in the number of roles based on recent results on cryptographic obfuscation;

CRFeb 18, 2015
How to Bootstrap Anonymous Communication

Sune K. Jakobsen, Claudio Orlandi

We ask whether it is possible to anonymously communicate a large amount of data using only public (non-anonymous) communication together with a small anonymous channel. We think this is a central question in the theory of anonymous communication and to the best of our knowledge this is the first formal study in this direction. To solve this problem, we introduce the concept of anonymous steganography: think of a leaker Lea who wants to leak a large document to Joe the journalist. Using anonymous steganography Lea can embed this document in innocent looking communication on some popular website (such as cat videos on YouTube or funny memes on 9GAG). Then Lea provides Joe with a short key $k$ which, when applied to the entire website, recovers the document while hiding the identity of Lea among the large number of users of the website. Our contributions include: - Introducing and formally defining anonymous steganography, - A construction showing that anonymous steganography is possible (which uses recent results in circuits obfuscation), - A lower bound on the number of bits which are needed to bootstrap anonymous communication.

CRFeb 14, 2012
A New Approach to Practical Active-Secure Two-Party Computation

Jesper Buus Nielsen, Peter Sebastian Nordholt, Claudio Orlandi et al.

We propose a new approach to practical two-party computation secure against an active adversary. All prior practical protocols were based on Yao's garbled circuits. We use an OT-based approach and get efficiency via OT extension in the random oracle model. To get a practical protocol we introduce a number of novel techniques for relating the outputs and inputs of OTs in a larger construction. We also report on an implementation of this approach, that shows that our protocol is more efficient than any previous one: For big enough circuits, we can evaluate more than 20000 Boolean gates per second. As an example, evaluating one oblivious AES encryption (~34000 gates) takes 64 seconds, but when repeating the task 27 times it only takes less than 3 seconds per instance.