9 citations · 25 across the 11 of their papers we have counts for
11 papers
The LLMbda Calculus: AI Agents, Conversations, and Information Flow
Zac Garby, Andrew D. Gordon, David Sands
Large language models are increasingly deployed as agents: they plan, call tools, read untrusted data, and act on the results. This exposes them to prompt injection: data meant onl…
Reconciling Shannon and Scott with a Lattice of Computable Information
Sebastian Hunt, David Sands, Sandro Stucki
This paper proposes a reconciliation of two different theories of information. The first, originally proposed in a lesser-known work by Claude Shannon, describes how the informatio…
Monitoring Data Minimisation
Srinivas Pinisetty, Thibaud Antignac, David Sands +1
Data minimisation is a privacy enhancing principle, stating that personal data collected should be no more than necessary for the specific purpose consented by the user. Checking t…
Data Minimisation: a Language-Based Approach (Long Version)
Thibaud Antignac, David Sands, Gerardo Schneider
Data minimisation is a privacy-enhancing principle considered as one of the pillars of personal data regulations. This principle dictates that personal data collected should be no…
Featherweight PINQ
Hamid Ebadi, David Sands
Differentially private mechanisms enjoy a variety of composition properties. Leveraging these, McSherry introduced PINQ (SIGMOD 2009), a system empowering non-experts to construct…
The Anatomy and Facets of Dynamic Policies
Niklas Broberg, Bart van Delft, David Sands
Information flow policies are often dynamic; the security concerns of a program will typically change during execution to reflect security-relevant events. A key challenge is how t…