Humanitarian Aid Distribution with Privacy-Preserving Assessment Capabilities

Abstract

In times of crisis, humanitarian organizations bring aid to those affected (e.g., water, food, medical supplies, cash assistance). Prior works introduced privacy-preserving systems for digitizing the aid distribution process, increasing their efficiency and security. These solutions, by design, do not allow humanitarian organizations to collect metrics about the aid distribution process. Such assessments (e.g., the proportion of aid distributed to a minority) are crucial to enable the organizations to improve their operations, to perform their duty of care, and to enable transparency and accountability towards recipients, donors, and the public in general. In partnership with the International Committee of the Red Cross (ICRC), we identify assessments relevant to humanitarian aid deployments and these assessments’ security and privacy requirements. We introduce a generic framework that augments existing privacy-preserving humanitarian aid distributions with such assessments. This framework enables the collection of aggregate statistics about the aid distribution process without compromising the privacy of recipients, and without requiring any changes to the existing protocols. To realize our framework we introduce one-time functional encryption (1FE), for which we propose efficient realizations from standard cryptographic primitives. We design and implement two variants of our framework: a more efficient one, secure against semi-honest adversaries; and a more robust one, secure against malicious adversaries. We also introduce the novel notions of threat model agility and graceful degradation. These notions enable us to model the unstable environment of humanitarian aid distribution, where the capabilities of the adversary may change suddenly (e.g., when a militia takes over a region in conflict), invalidating the threat model under which the system was originally deployed. We believe these notions are of independent interest for other privacy-preserving applications deployed in unstable environments.

Christian Knabenhans

Ph.D. student in security and privacy

Doctoral student at EPFL. Applied cryptography, privacy-enhancing technologies, useable security.