Efficient Sharing of Encrypted Data

Bennett, Krista; Grothoff, Christian; Horozov, T.; Patrascu, Ioana

doi:10.1007/3-540-45450-0_8

Cited by 24 publications

(21 citation statements)

References 3 publications

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“…Therefore, we decide to keep the circuit creation and relay selection under the user's direct control, and we propose the use of bloom filters to let the user identify which relays can connect to each other. 2 In particular, we require each peer to attach to his public onion key a bloom filter where the neighbors of the peer have been encoded, called neighbor bloom filter and built over the neighbors' identifiers. The filter, as well as the onion key, must be signed by the peer with his identity key, and is stored and distributed together with the onion key.…”

Section: Building An Onion Circuitmentioning

confidence: 99%

Key Management for Onion Routing in a True Peer to Peer Setting

Palmieri

Pouwelse

2014

Advances in Information and Computer Security

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Abstract. Onion routing is a technique for anonymous and privacy preserving communication at the base of popular Internet anonymity tools such as Tor. In onion routing, traffic is relayed by a number of intermediary nodes (called relays) before it reaches the intended destination. To guarantee privacy and prevent tampering, each packet is encrypted multiple times in a layered manner, using the public keys of the relays. Therefore, this mechanism makes two important assumptions: first, that the relays are able to communicate with each other; second, that the user knows the list of available relays and their respective public keys. Tor implements therefore a distributed directory listing the relays and their keys. When a user is not able to communicate with relays directly, he has to use special bridge servers to connect to the onion network. This construction, however, does not work in a fully peer to peer setting, where each peer only knows a limited number of other peers and may not be able to communicate with some of them due, for instance, to NAT or firewalls. In this paper we propose a key management scheme for onion routing that overcomes these problems. The proposed solution does not need a directory system and does not imply knowledge of all active relays, while it guarantees the secure distribution of public keys. We also present an alternative strategy for building circuit of relays based on bloom filters. The proposed construction overcomes some of the structural inefficiencies of the Tor design, and opens the way for implementing onion routing over a true peer to peer overlay network.

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Section: Building An Onion Circuitmentioning

confidence: 99%

Key Management for Onion Routing in a True Peer to Peer Setting

Palmieri

Pouwelse

2014

Advances in Information and Computer Security

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“…The main disadvantage of the dual receiver cryptosystem is that the server needs to send an auxiliary private key to a client for decrypting a partial ciphertext, which is insecure in the real environment. Recently, there is much work on keyword search on encrypted files, such as Song et al [9], Bennett et al [10], and Chang et al [12]. In this paper, we borrow the idea of partial decipherment, and propose an efficient privacy preserving keyword search scheme by improving PEKS, which requires no private key transmission and is more applicable to a cloud environment.…”

Section: A Related Workmentioning

confidence: 99%

An Efficient Privacy Preserving Keyword Search Scheme in Cloud Computing

Liu

Wang

2009

2009 International Conference on Computational Science and Engineering

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Abstract-A user stores his personal files in a cloud, and retrieves them wherever and whenever he wants. For the sake of protecting the user data privacy and the user queries privacy, a user should store his personal files in an encrypted form in a cloud, and then sends queries in the form of encrypted keywords. However, a simple encryption scheme may not work well when a user wants to retrieve only files containing certain keywords using a thin client. First, the user needs to encrypt and decrypt files frequently, which depletes too much CPU capability and memory power of the client. Second, the service provider couldn't determine which files contain keywords specified by a user if the encryption is not searchable. Therefore, it can only return back all the encrypted files. A thin client generally has limited bandwidth, CPU and memory, and this may not be a feasible solution under the circumstances. In this paper, we investigate the characteristics of cloud computing and propose an efficient privacy preserving keyword search scheme in cloud computing. It allows a service provider to participate in partial decipherment to reduce a client's computational overhead, and enables the service provider to search the keywords on encrypted files to protect the user data privacy and the user queries privacy efficiently. By proof, our scheme is semantically secure.

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“…Proving the authenticity of a remote microprocessor [11] and (ultimately) the trustworthiness of a remote machine are still open problems. gnunet compensates for the impossibility of guaranteeing anonymity against very powerful attackers by providing deniability [1]. Even if a powerful adversary can determine who sent a message, the deniable encoding and searching mechanism for content (see [1]) ensures that the adversary may still be unable to determine what the message is about.…”

Section: Measuring Anonymitymentioning

confidence: 99%

“…This situation is not as problematic as it may sound since peers can start with a very slow download rate r. This will increase the network load on the network, especially since idle nodes are likely to spread a query much further than busy nodes would. Thus the load on the network will quickly rise (at least in the proximity of the peer starting the download), allowing the peer to increase r. Since gnunet's content encoding [1] has the inherent property that a downloading node can initially only send a small set of queries (due to the tree-structure of the encoding), the requirement that a node must start with a small r to achieve anonymity until the network load rises is in practice what the code must do anyway. The network always has some level of background noise for key exchange and node advertisement propagation that should be sufficient for a node to hide the origin of a single query.…”

Section: Measuring Anonymitymentioning

confidence: 99%

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gap – Practical Anonymous Networking

Bennett

Grothoff

2003

Privacy Enhancing Technologies

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Abstract. This paper describes how anonymity is achieved in gnunet, a framework for anonymous distributed and secure networking. The main focus of this work is gap, a simple protocol for anonymous transfer of data which can achieve better anonymity guarantees than many traditional indirection schemes and is additionally more efficient. gap is based on a new perspective on how to achieve anonymity. Based on this new perspective it is possible to relax the requirements stated in traditional indirection schemes, allowing individual nodes to balance anonymity with efficiency according to their specific needs.

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Efficient Sharing of Encrypted Data

Cited by 24 publications

References 3 publications

Key Management for Onion Routing in a True Peer to Peer Setting

Key Management for Onion Routing in a True Peer to Peer Setting

An Efficient Privacy Preserving Keyword Search Scheme in Cloud Computing

gap – Practical Anonymous Networking

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