Extended Combinatorial Constructions for Peer-to-peer User-Private Information Retrieval

We consider user-private information retrieval (UPIR), an interesting alternative to private information retrieval (PIR) introduced by Domingo-Ferrer et al. In UPIR, the database knows which records have been retrieved, but does not know the identity of the query issuer. The goal of UPIR is to disguise user profiles from the database. Domingo-Ferrer et al.\ focus on using a peer-to-peer community to construct a UPIR scheme, which we term P2P UPIR. In this paper, we establish a strengthened model for P2P UPIR and clarify the privacy goals of such schemes using standard terminology from the field of privacy research. In particular, we argue that any solution providing privacy against the database should attempt to minimize any corresponding loss of privacy against other users. We give an analysis of existing schemes, including a new attack by the database. Finally, we introduce and analyze two new protocols. Whereas previous work focuses on a special type of combinatorial design known as a configuration, our protocols make use of more general designs. This allows for flexibility in protocol set-up, allowing for a choice between having a dynamic scheme (in which users are permitted to enter and leave the system), or providing increased privacy against other users.Comment: Updated version, which reflects reviewer comments and includes expanded explanations throughout. Paper is accepted for publication by Advances in Mathematics of Communication

Private Information Retrieval in an Anonymous Peer-to-Peer Environment

Private Information Retrieval (PIR) protocols enable a client to access data from a server without revealing what data was accessed. The study of Computational Private Information Retrieval (CPIR) protocols, an area of PIR protocols focusing on computational security, has been a recently reinvigorated area of focus in the study of cryptography. However, CPIR protocols still have not been utilized in any practical applications. The aim of this thesis is to determine whether the Melchor Gaborit CPIR protocol can be successfully utilized in a practical manner in an anonymous peer-to-peer environment

LightPIR: Privacy-Preserving Route Discovery for Payment Channel Networks

Payment channel networks are a promising approach to improve the scalability of cryptocurrencies: they allow to perform transactions in a peer-to-peer fashion, along multi-hop routes in the network, without requiring consensus on the blockchain. However, during the discovery of cost-efficient routes for the transaction, critical information may be revealed about the transacting entities. This paper initiates the study of privacy-preserving route discovery mechanisms for payment channel networks. In particular, we present LightPIR, an approach which allows a source to efficiently discover a shortest path to its destination without revealing any information about the endpoints of the transaction. The two main observations which allow for an efficient solution in LightPIR are that: (1) surprisingly, hub labelling algorithms - which were developed to preprocess "street network like" graphs so one can later efficiently compute shortest paths - also work well for the graphs underlying payment channel networks, and that (2) hub labelling algorithms can be directly combined with private information retrieval. LightPIR relies on a simple hub labeling heuristic on top of existing hub labeling algorithms which leverages the specific topological features of cryptocurrency networks to further minimize storage and bandwidth overheads. In a case study considering the Lightning network, we show that our approach is an order of magnitude more efficient compared to a privacy-preserving baseline based on using private information retrieval on a database that stores all pairs shortest paths

Maintaining unlinkability in group based P2P environments

In the wake of the success of Peer-to-Peer (P2P) networking, security has arisen as one of its main concerns, becoming a key issue when evaluating a P2P system. Unfortunately, some systems' design focus targeted issues such as scalabil-ity or overall performance, but not security. As a result, security mechanisms must be provided at a later stage, after the system has already been designed and partially (or even fully) implemented, which may prove a cumbersome proposition. This work exposes how a security layer was provided under such circumstances for a specic Java based P2P framework: JXTA-Overlay.Arran de l'èxit de (P2P) peer-to-peer, la seguretat ha sorgit com una de les seves principals preocupacions, esdevenint una qüestió clau en l'avaluació d'un sistema P2P. Malauradament, alguns sistemes de disseny apunten focus de problemes com l'escalabilitat o l'acompliment general, però no de seguretat. Com a resultat d'això, els mecanismes de seguretat s¿han de proporcionar en una etapa posterior, després que el sistema ja ha estat dissenyat i parcialment (o fins i tot totalment) implementat, la qual cosa pot ser una proposició incòmode. Aquest article exposa com es va proveir una capa de seguretat sota aquestes circumstàncies per un Java específic basat en un marc P2P: JXTA-superposició.A raíz del éxito de (P2P) peer-to-peer, la seguridad ha surgido como una de sus principales preocupaciones, convirtiéndose en una cuestión clave en la evaluación de un sistema P2P. Desgraciadamente, algunos sistemas de diseño apuntan un foco de problemas como la escalabilidad o el desempeño general, pero no de seguridad. Como resultado de ello, los mecanismos de seguridad se proporcionarán en una etapa posterior, después de que el sistema ya ha sido diseñado y parcialmente (o incluso totalmente) implementado, lo que puede ser una proposición incómodo. Este artículo expone cómo se proveyó una capa de seguridad bajo estas circunstancias por un Java específico basado en un marco P2P: JXTA-superposición

CHORUS Deliverable 2.1: State of the Art on Multimedia Search Engines

Based on the information provided by European projects and national initiatives related to multimedia search as well as domains experts that participated in the CHORUS Think-thanks and workshops, this document reports on the state of the art related to multimedia content search from, a technical, and socio-economic perspective. The technical perspective includes an up to date view on content based indexing and retrieval technologies, multimedia search in the context of mobile devices and peer-to-peer networks, and an overview of current evaluation and benchmark inititiatives to measure the performance of multimedia search engines. From a socio-economic perspective we inventorize the impact and legal consequences of these technical advances and point out future directions of research

Secure communication using dynamic VPN provisioning in an Inter-Cloud environment

Most of the current cloud computing platforms offer Infrastructure as a Service (IaaS) model, which aims to provision basic virtualised computing resources as on-demand and dynamic services. Nevertheless, a single cloud does not have limitless resources to offer to its users, hence the notion of an Inter-Cloud enviroment where a cloud can use the infrastructure resources of other clouds. However, there is no common framework in existence that allows the srevice owners to seamlessly provision even some basic services across multiple cloud service providers, albeit not due to any inherent incompatibility or proprietary nature of the foundation technologies on which these cloud platforms are built. In this paper we present a novel solution which aims to cover a gap in a subsection of this problem domain. Our solution offer a security architecture that enables service owners to provision a dynamic and service-oriented secure virtual private network on top of multiple cloud IaaS providers. It does this by leveraging the scalability, robustness and flexibility of peer- to-peer overlay techniques to eliminate the manual configuration, key management and peer churn problems encountered in setting up the secure communication channels dynamically, between different components of a typical service that is deployed on multiple clouds. We present the implementation details of our solution as well as experimental results carried out on two commercial clouds

Knowledge is at the Edge! How to Search in Distributed Machine Learning Models

With the advent of the Internet of Things and Industry 4.0 an enormous amount of data is produced at the edge of the network. Due to a lack of computing power, this data is currently send to the cloud where centralized machine learning models are trained to derive higher level knowledge. With the recent development of specialized machine learning hardware for mobile devices, a new era of distributed learning is about to begin that raises a new research question: How can we search in distributed machine learning models? Machine learning at the edge of the network has many benefits, such as low-latency inference and increased privacy. Such distributed machine learning models can also learn personalized for a human user, a specific context, or application scenario. As training data stays on the devices, control over possibly sensitive data is preserved as it is not shared with a third party. This new form of distributed learning leads to the partitioning of knowledge between many devices which makes access difficult. In this paper we tackle the problem of finding specific knowledge by forwarding a search request (query) to a device that can answer it best. To that end, we use a entropy based quality metric that takes the context of a query and the learning quality of a device into account. We show that our forwarding strategy can achieve over 95% accuracy in a urban mobility scenario where we use data from 30 000 people commuting in the city of Trento, Italy.Comment: Published in CoopIS 201