Open Access

We propose in this work to solve privacy preserving set relations performed by a third party in an outsourced configuration. We argue that solving the disjointness relation based on Bloom filters is a new contribution in particular by having another layer of privacy on the sets cardinality. We propose to compose the set relations in a slightly different way by applying a keyed hash function. Besides discussing the correctness of the set relations, we analyze how this impacts the privacy of the sets content as well as providing privacy on the sets cardinality. We are in particular interested in how having bits overlapping in the Bloom filters impacts the privacy level of our approach. Finally, we present our results with real-world parameters in two concrete scenarios.

While prospect of tracking mobile devices' users is widely discussed all over European countries to counteract COVID-19 propagation, we propose a Bloom filter based construction providing users' location privacy and preventing mass surveillance. We apply a solution based on Bloom filters data structure that allows a third party, a government agency, to perform some privacy-preserving set relations on a mobile telco's access logfile. By computing set relations, the government agency, given the knowledge of two identified persons, has an instrument that provides a (possible) infection chain from the initial to the final infected user no matter at which location on a worldwide scale they are. The benefit of our approach is that intermediate possible infected users can be identified and subsequently contacted by the agency. With such approach, we state that solely identities of possible infected users will be revealed and location privacy of others will be preserved. To this extent, it meets General Data Protection Regulation (GDPR)requirements in this area.

Covert- and side-channels as well as techniques to establish them in cloud computing are in focus of research for quite some time. However, not many concrete mitigation methods have been developed and even less have been adapted and concretely implemented by cloud providers. Thus, we recently conceptually proposed C 3 -Sched a CPU scheduling based approach to mitigate L2 cache covert-channels. Instead of flushing the cache on every context switch, we schedule trusted virtual machines to create noise which prevents potential covert-channels. Additionally, our approach aims on preserving performance by utilizing existing instead of artificial workload while reducing covert-channel related cache flushes to cases where not enough noise has been achieved. In this work we evaluate cache covert-channel mitigation and performance impact of our integration of C 3 -Sched in the XEN credit scheduler. Moreover, we compare it to naive solutions and more competitive approaches.

Covert and Side-Channels have been known for a long time due to their versatile forms of appearance. For nearly every technical improvement or change in technology, such channels have been (re-)created or known methods have been adapted. For example the introduction of hyperthreading technology has introduced new possibilities for covert communication between malicious processes because they can now share the arithmetic logical unit (ALU) as well as the L1 and L2 cache which enables establishing multiple covert channels. Even virtualization which is known for its isolation of multiple machines is prone to covert and side-channel attacks due to the sharing of resources. Therefore itis not surprising that cloud computing is not immune to this kind of attacks. Even more, cloud computing with multiple, possibly competing users or customers using the same shared resources may elevate the risk of unwanted communication. In such a setting the ”air gap” between physical servers and networks disappears and only the means of isolation and virtual separation serve as a barrier between adversary and victim. In the work at hand we will provide a survey on weak spots an adversary trying to exfiltrate private data from target virtual machines could exploit in a cloud environment. We will evaluate the feasibility of example attacks and point out possible mitigation solutions if they exist.

In this work we describe the implementation details of a protocol suite for a secure and reliable over-the-air reprogramming of wireless restricted devices. Although, recently forward error correction codes aiming at a robust transmission over a noisy wireless medium have extensively been discussed and evaluated, we believe that the clear value of the contribution at hand is to share our experience when it comes to a meaningful combination and implementation of various multihop (broadcast) transmission protocols and custom-fit security building blocks: For a robust and reliable data transmission we make use of fountain codes a.k.a. rateless erasure codes and show how to combine such schemes with an underlying medium access control protocol, namely a distributed low duty cycle medium access control (DLDC-MAC). To handle the well known problem of packet pollution of forward-error-correction approaches where an attacker bogusly modifies or infiltrates some minor number of encoded packets and thus pollutes the whole data stream at the receiver side, we apply homomorphic message authentication codes (HomMAC). We discuss implementation details and the pros and cons of the two currently available HomMAC candidates for our setting. Both require as the core cryptographic primitive a symmetric block cipher for which, as we will argue later, we have opted for the PRESENT, PRIDE and PRINCE (exchangeable) ciphers in our implementation.

This work discusses several use cases of post-mortem mobile device tracking in which privacy is required e.g. due to client-confidentiality agreements and sensibility of data from government agencies as well as mobile telecommunication providers. We argue that our proposed Bloomfilter based privacy approach is a valuable technical building block for the arising General Data Protection Regulation (GDPR) requirements in this area. In short, we apply a solution based on the Bloom filters data structure that allows a 3rd party to performsome privacy saving setrelations on a mobiletelco’s access logfile or other mobile access logfile from harvesting parties without revealing any other mobile users in the proximity of a mobile base station but still allowing to track perpetrators.

In the area of cloud computing, judging the fulfillment of service-level agreements on a technical level is gaining more and more importance. To support this we introduce privacy preserving set relations as inclusiveness and disjointness based ao Bloom filters. We propose to compose them in a slightly different way by applying a keyed hash function. Besides discussing the correctness of set relations, we analyze how this impacts the privacy of the sets content as well as providing privacy on the sets cardinality. Indeed, our solution proposes to bring another layer of privacy on the sizes. We are in particular interested how the overlapping bits of a Bloom filter impact the privacy level of our approach. We concretely apply our solution to a use case of cloud security audit on access control and present our results with real-world parameters.

Ziel von UNIKOPS (Universell konfigurierbare Sicherheitslösung für Cyberphysikalische heterogene Systeme) ist es, hochflexible Software- und teilweise auch Hardwarelösungen mit sehr hohem Sicherheitsniveau zu entwickeln, die in einer Vielzahl von CPS-Anwendungsfeldern, insbesondere mit Sensorknoten, einsetzbar sind.

In a Semi-autonomic cloud auditing architecture we weaved in privacy enhancing mechanisms [15] by applying the public key version of the Somewhat homomorphic encryption (SHE) scheme from [4]. It turns out that the performance of the SHE can be significantly improved by carefully deriving relevant crypto parameters from the concrete cloud auditing use cases for which the scheme serves as a privacy enhancing approach. We provide a generic algorithm for finding good SHE parameters with respect to a given use case scenario by analyzing and taking into consideration security, correctness and performance of the scheme. Also, to show the relevance of our proposed algorithms we apply it to two predominant cloud auditing use cases.

In the work at hand, we combine a Private Information Retrieval (PIR) protocol with Somewhat Homomorphic Encryption (SHE) and use Searchable Encryption (SE) with the objective to provide security and confidentiality features for a third party cloud security audit. During the auditing process, a third party auditor will act on behalf of a cloud service user to validate the security requirements performed by a cloud service provider. Our concrete contribution consists of developing a PIR protocol which is proceeding directly on a log database of encrypted data and allowing to retrieve a sum or a product of multiple encrypted elements. Subsequently, we concretely apply our new form of PIR protocol to a cloud audit use case where searchable encryption is employed to allow additional confidentiality requirements to the privacy of the user. Exemplarily we are considering and evaluating an audit of client accesses to a controlled resource provided by a cloud service provider.