Correction to Improving the DGK comparison protocol

At the IEEE Workshop on Information Forensics and Security in 2012, Veugen introduced two ways of improving a well-known secure comparison protocol by Damgård, Geisler and Krøigaard, which uses additively homomorphic encryption. The first new protocol reduced the computational effort of one party by roughly $50\%$. The second one showed how to achieve perfect security towards one party without additional costs, whereas the original version with encrypted inputs only achieved statistical security. However, the second protocol contained a mistake, leading to incorrect outputs in some cases. We show how to correct this mistake, without increasing its computational complexity

Cloud-based Quadratic Optimization with Partially Homomorphic Encryption

The development of large-scale distributed control systems has led to the outsourcing of costly computations to cloud-computing platforms, as well as to concerns about privacy of the collected sensitive data. This paper develops a cloud-based protocol for a quadratic optimization problem involving multiple parties, each holding information it seeks to maintain private. The protocol is based on the projected gradient ascent on the Lagrange dual problem and exploits partially homomorphic encryption and secure multi-party computation techniques. Using formal cryptographic definitions of indistinguishability, the protocol is shown to achieve computational privacy, i.e., there is no computationally efficient algorithm that any involved party can employ to obtain private information beyond what can be inferred from the party's inputs and outputs only. In order to reduce the communication complexity of the proposed protocol, we introduced a variant that achieves this objective at the expense of weaker privacy guarantees. We discuss in detail the computational and communication complexity properties of both algorithms theoretically and also through implementations. We conclude the paper with a discussion on computational privacy and other notions of privacy such as the non-unique retrieval of the private information from the protocol outputs

Privacy-Aware Processing of Biometric Templates by Means of Secure Two-Party Computation

The use of biometric data for person identification and access control is gaining more and more popularity. Handling biometric data, however, requires particular care, since biometric data is indissolubly tied to the identity of the owner hence raising important security and privacy issues. This chapter focuses on the latter, presenting an innovative approach that, by relying on tools borrowed from Secure Two Party Computation (STPC) theory, permits to process the biometric data in encrypted form, thus eliminating any risk that private biometric information is leaked during an identification process. The basic concepts behind STPC are reviewed together with the basic cryptographic primitives needed to achieve privacy-aware processing of biometric data in a STPC context. The two main approaches proposed so far, namely homomorphic encryption and garbled circuits, are discussed and the way such techniques can be used to develop a full biometric matching protocol described. Some general guidelines to be used in the design of a privacy-aware biometric system are given, so as to allow the reader to choose the most appropriate tools depending on the application at hand

Cloud-Based Quadratic Optimization with Partially Homomorphic Encryption

This article develops a cloud-based protocol for a constrained quadratic optimization problem involving multiple parties, each holding private data. The protocol is based on the projected gradient ascent on the Lagrange dual problem and exploits partially homomorphic encryption and secure communication techniques. Using formal cryptographic definitions of indistinguishability, the protocol is shown to achieve computational privacy. We show the implementation results of the protocol and discuss its computational and communication complexity. We conclude this article with a discussion on privacy notions

Ifosfamide with regional hyperthermia in soft-tissue sarcomas

For high-risk soft tissue sarcomas (HR-STS) of adults, new treatment strategies are needed to improve outcome with regard to local control and overall survival. Therefore, systemic chemotherapy has been integrated either after (adjuvant) or before (neoadjuvant) optimal local treatment by surgery and radiotherapy in HR-STS. The combination with regional hyperthermia as a new treatment strategy seems to open a new therapeutic window. Copyright (C) 2003 S. Karger AG, Basel

Improving methods for the study of membrane proteins by solid-state NMR

Solid state NMR is a emerging method for the study of membrane proteins, which has received much interest in recent years. Limiting the study of many pharmacologically relevant targets, are the often long measuring times, required to obtain especially higher dimensional solid state NMR spectra of good quality. To address this problem, multiple methods where developed in this work, which can be categorized into two groups. The first set of methods aims at the quality of certain spectra, by implementing a spectral filter, which increases the fidelity of the measured data. The second set of methods, addresses the problem of long measuring times directly, by increasing the sensitivity per unit time, as could be shown, for example, on homo- and heteronuclear singlequantum-singlequantum correlation experiments. The gains in measuring time for the latter group of methods are typically in the order of 2-3, but some experiments allow multiple methods to be employed simultaneously, which can lead to a decrease in measuring time of a factor of up to 8. It is important to mention, that none of the methods introduced in this work require any equipment in addition to the conventional setup present in most sold state NMR laboratories and no changes or addition to the samples under study are required. Therefore the gains reported in this work come at no extra cost and require only minimal implementation effort on the side of the user.Festkörper-NMR ist eine Methode zur Untersuchung von integralen Membranproteinen, die in den letzten Jahren viel Beachtung gefunden hat. Ein Problem bei der Untersuchung von vielen pharmakologisch relevanten Zielen, sind die oft langen Messzeiten, die sich gerade für höherdimensionale Festkörper-NMR Experimente ergeben. Um dieses Problem zu behandeln, werden in der vorliegenden Arbeit mehrere Methoden vorgestellt, die sich in zwei Kategorien unterteilen lassen. Die erste Kategorie beschäftigt sich mit dem Filtern von Spektren, um die Qualität der resultierenden Daten zu verbessern. Die Methoden der zweiten Kategorie erhöhen direkt die Sensitivität pro Zeiteinheit, wie z.B. an homo- und heteronuklearen Singlequanten-Singlequanten Korrelationsspektren gezeigt werden konnte. Die Methoden letzterer Kategorie erlauben in der Regel eine Messzeitverkürzung um einen Faktor von 2-3, können aber bei bestimmten Experimenten zusammen eingesetzt werden, was in einer Messzeitverkürzung um einem Faktor von bis zu 8 resultieren kann. Es ist wichtig zu erwähnen, das alle Methoden, die in dieser Arbeit vorgestellt werden, ohne zusätzliches Ausrüstung, über die normalerweise in Festkörper-NMR Laboratorien vorhandenen Geräte hinaus benötigen. Des weiteren sind keine Zusätze oder Veränderungen an den zu untersuchenden Proben vonnöten. Daher ist allen Methoden in dieser Arbeit gemein, das sie ohne Mehrkosten und mit minimalem Implementierungsaufwand vom Endbenutzer angewendet werden können