Christian Weinert

Integrity, authenticity, non-repudiation, and proof of existence for long-term archiving

The world increasingly depends on archives to store digital documents, such as land registers and medical records, for long periods of time. For stored documents to remain trustworthy, archives must provide proofs that a document existed on a certain date and has not been changed since. In addition, in many cases, the origin of the document must be verifiable and the originator must not be able to repudiate that she is the originator. In this paper, we survey the solutions that provide the above protection goals in the long term. We analyze and compare the solutions with respect to their functionalities (which protection goals do they achieve?), the trust assumptions they require, and their performance. From this analysis and comparison, we deduce deficiencies of the current solutions and important research problems that must be solved in order to come up with protection solutions that are even more satisfactory.

Efficient Circuit-Based PSI via Cuckoo Hashing

While there has been a lot of progress in designing efficient custom protocols for computing Private Set Intersection (PSI), there has been less research on using generic Multi-Party Computation (MPC) protocols for this task. However, there are many variants of the set intersection functionality that are not addressed by the existing custom PSI solutions and are easy to compute with generic MPC protocols (e.g., comparing the cardinality of the intersection with a threshold or measuring ad conversion rates).

A Performance Analysis of Long-Term Archiving Techniques

A challenge for digital archives managing long lived data, such as medical records and land registers, is to guarantee long-term authenticity, integrity, and datedness. Although some techniques have been proposed that provide these security goals, most proposals lack a corresponding performance analysis. Thus, in this paper we provide an analytical analysis of the performance of several proposals. Following, to see the impact of different approaches on the runtime, we implemented the most promising schemes and compared them with respect to their required storage space and verification time. Furthermore, the identified computational bottlenecks of the techniques are presented and corresponding improvements are indicated. Finally, we show how to select a long-term archiving scheme and the appropriate key sizes based on trust assumptions and the number of documents to be archived.

CogniCrypt: Supporting developers in using cryptography

Previous research suggests that developers often struggle using low-level cryptographic APIs and, as a result, produce insecure code. When asked, developers desire, among other things, more tool support to help them use such APIs. In this paper, we present CogniCrypt, a tool that supports developers with the use of cryptographic APIs. CogniCrypt assists the developer in two ways. First, for a number of common cryptographic tasks, CogniCrypt generates code that implements the respective task in a secure manner. Currently, CogniCrypt supports tasks such as data encryption, communication over secure channels, and long-term archiving. Second, CogniCrypt continuously runs static analyses in the background to ensure a secure integration of the generated code into the developers workspace. This video demo showcases the main features of CogniCrypt: youtube.com/watch?v=JUq5mRHfAWY.

An efficient time-stamping solution for long-term digital archiving

Long-term archiving of digital data is necessary to meet many legal requirements. For example, hospitals in many countries must keep health records of patients for decades. Archiving usually relies on digital signatures and time-stamps to prove the security properties of archived data, such as integrity and proof of existence. Moreover, archived data often needs to be updated, e.g. a new prescription is added to a patients record, but without compromising integrity and proof of existence. To date, a solution that guarantees integrity and proof of existence indefinitely and allows for updates on archived data is Content Integrity Service (CIS). In this paper, we introduce an improved version of CIS named Content Integrity Service with Skip Lists (CISS) that changes the time-stamping process of CIS by using two different types of time-stamps together with skip lists. We demonstrate that CISS outperforms CIS by analyzing the algorithms and running experiments in realistic scenarios.

Large-Scale Privacy-Preserving Statistical Computations for Distributed Genome-Wide Association Studies

We present privacy-preserving solutions for Genome-Wide Association Studies (GWAS) based on Secure Multi-Party Computation (SMPC). Using SMPC, we protect the privacy of patients when medical institutes collaborate for computing statistics on genomic data in a distributed fashion. Previous solutions for this task lack efficiency and/or use inadequate algorithms that are of limited practical value. Concretely, we optimize and implement multiple algorithms for the χ^2

MoPS: A Modular Protection Scheme for Long-Term Storage

-, G-, and P-test in the ABY framework (Demmler et al., NDSS»15) and evaluate them in a distributed GWAS scenario. Statistical tests generally require advanced mathematical operations. For operations that cannot be calculated in integer arithmetic, we make use of the existing IEEE 754 floating point arithmetic implementation in ABY (Demmler et al., CCS»15). To improve performance, we extend the mixed-protocol capabilities of ABY by optimizing and implementing the integer to floating point conversion protocols of Aliasgari et al.\ (NDSS»13), which may be of independent interest. Furthermore, we consider extended contingency tables for the χ^2

Chameleon: A Hybrid Secure Computation Framework for Machine Learning Applications

- and G-test that use codeword counts instead of counts for only two alleles, thereby allowing for advanced, realistic analyses. Finally, we consider an outsourcing scenario where two non-colluding semi-trusted third parties process secret-shared input data from multiple institutes. Our extensive evaluation shows, compared to the prior art of Constable et al.\ (BMC Medical Informatics and Decision Making»15), an improved run-time efficiency of the χ^2

VoiceGuard: Secure and Private Speech Processing

-test by up to factor 37x. We additionally demonstrate practicality in scenarios with millions of participants and hundreds of collaborating institutes.

Efficient Circuit-based PSI via Cuckoo Hashing.

Current trends in technology, such as cloud computing, allow outsourcing the storage, backup, and archiving of data. This provides efficiency and flexibility, but also poses new risks for data security. It in particular became crucial to develop protection schemes that ensure security even in the long-term, i.e. beyond the lifetime of keys, certificates, and cryptographic primitives. However, all current solutions fail to provide optimal performance for different application scenarios. Thus, in this work, we present MoPS, a modular protection scheme to ensure authenticity and integrity for data stored over long periods of time. MoPS does not come with any requirements regarding the storage architecture and can therefore be used together with existing archiving or storage systems. It supports a set of techniques which can be plugged together, combined, and migrated in order to create customized solutions that fulfill the requirements of different application scenarios in the best possible way. As a proof of concept we implemented MoPS and provide performance measurements. Furthermore, our implementation provides additional features, such as guidance for non-expert users and export functionalities for external verifiers.