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We propose secure multi-party computation techniques for the distributed computation of the average using a privacy-preserving extension of gossip algorithms. While recently there has been mainly research on the side of gossip algorithms (GA) for data aggregation itself, to the best of our knowledge, the aforementioned research line does not take into consideration the privacy of the entities involved. More concretely, it is our objective to not reveal a node's private input value to any other node in the network, while still computing the average in a fully-decentralized fashion. Not revealing in our setting means that an attacker gains only minor advantage when guessing a node's private input value. We precisely quantify an attacker's advantage when guessing - as a mean for the level of data privacy leakage of a node's contribution. Our results show that by perturbing the input values of each participating node with pseudo-random noise with appropriate statistical properties (i) only a minor and configurable leakage of private information is revealed, by at the same time (ii) providing a good average approximation at each node. Our approach can be applied to a decentralized prosumer market, in which participants act as energy consumers or producers or both, referred to as prosumers.
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.
Several cloud schedulers have been proposed in the literature with different optimization goals such as reducing power consumption, reducing the overall operational costs or decreasing response times. A less common goal is to enhance the system security by applying specific scheduling decisions. The security risk of covert channels is known for quite some time, but is now back in the focus of research because of the multitenant nature of cloud computing and the co-residency of several per-tenant virtual machines on the same physical machine. Especially several cache covert channels have been identified that aim to bypass a cloud infrastructure's sandboxing mechanism. For instance, cache covert channels like the one proposed by Xu et. al. use the idealistic scenario with two alternately running colluding processes in different VMs accessing the cache to transfer bits by measuring cache access time. Therefore, in this paper we present a cascaded cloud scheduler coined C 3 -Sched aiming at mitigating the threat of a leakage of customers data via cache covert channels by preventing processes to access cache lines alternately. At the same time we aim at maintaining the cloud performance and minimizing the global scheduling overhead.
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 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.
Remote code attestation protocols are an essential building block to offer a reasonable system security for wireless embedded devices. In the work at hand we investigate in detail the trustability of a purely software-based remote code attestation based inference mechanism over the wireless when e.g. running the prominent protocol derivate SoftWare-based ATTestation for Embedded Devices (SWATT). Besides the disclosure of pitfalls of such a protocol class we also point out good parameter choices which allow at least a meaningful plausibility check with a balanced false positive and false negative ratio.
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.
Das Buch bietet eine fundierte Einführung in die Chronologie bekannter Angriffe und Verwundbarkeiten auf mobile Systeme und dessen konzeptionelle Einordnung der letzten zwei Dekaden. So erhält der Leser einen einmaligen Überblick über die Vielfältigkeit nachweisbar ausgenutzter Angriffsvektoren auf verschiedenste Komponenten mobiler drahtloser Geräte sowie den teilweise inhärent sicherheitskritischen Aktivitäten moderner mobiler OS. Eine für Laien wie Sicherheitsarchitekten gleichermaßen fesselnde Lektüre, die das Vertrauen in sichere mobile Systeme stark einschränken dürfte.
Der Inhalt
Verwundbarkeit von 802.15.4: PiP-Injektion
Verwundbarkeit von WLAN: KRACK-Angriff auf WPA2
Verwundbarkeit von Bluetooth: Blueborne und Co.
Verwundbarkeiten von NFC und durch NFC
Angriffe über das Baseband
Android Sicherheitsarchitektur
Horizontale Rechteausweitung
Techniken zu Obfuskierung und De-Obfuskierung von Apps
Apps mit erhöhten Sicherheitsbedarf: Banking Apps
Positionsbestimmung durch Swarm-Mapping
Seitenkanäle zur Überwindung des ‚Air-gap‘
Ausblick: 5G Sicherheitsarchitektur
Die Zielgruppen: Studierende der Informatik, Wirtschaftsinformatik, Elektrotechnik oder verwandter Studiengänge Praktiker, IT-Sicherheitsbeauftragte, Datenschutzbeauftragte, Entscheidungsträger, Nutzer drahtloser Geräte, die an einem ‚Blick unter die Motorhaube‘ interessiert sind.
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.