Compressed network coding vectors

Jafari, Mahdi; Keller, Lorenzo; Fragouli, Christina; Argyraki, Katerina

doi:10.1109/isit.2009.5206041

Cited by 32 publications

(49 citation statements)

References 11 publications

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“…We can, therefore, claim that the number of packets transmitted in the network does not change compared to SenseCode without encryption (we found that larger packet sizes do not increase the packet error rates substantially). Moreover, we can significantly compress the coding vectors using techniques similar to [5].…”

Section: Cost Analysismentioning

confidence: 99%

Low cost security for sensor networks

Atsan

Safaka

Keller

et al. 2013

2013 International Symposium on Network Coding (NetCod)

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Abstract-We design and evaluate a lightweight encryption protocol suitable for sensor networks, that enables weak security in the presence of passive eavesdroppers. At every communication round, our protocol creates a key between each sensor node and the sink, by appropriately mixing and coding information packets that the nodes passively overhear. Evaluation using the TOSSIM simulator indicates that with our protocol we can gain significant security benefits at low overhead cost.

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Section: Cost Analysismentioning

confidence: 99%

Low cost security for sensor networks

Atsan

Safaka

Keller

et al. 2013

2013 International Symposium on Network Coding (NetCod)

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“…To solve the linear Equation (1) the Gaussian elimination algorithm needs to be deployed at the receiver side [6]. ⎛ ⎜ ⎜ ⎜ ⎝ …”

Section: A Coding and Decodingmentioning

confidence: 99%

Hidden sources from an arbitrary receiver

Poostindouz

Karimian

2012

2012 16th IEEE Mediterranean Electrotechnical Conference

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Network coding is a novel technique in which internal nodes are permitted to combine independent sources information. In networks that linear network coding is engaged, two main approaches are discussed for the network code design problem of selecting linear combinations: randomized setting and deterministic manner. In this paper we consider a security issue where a set of independent messages are expected to be hidden from an arbitrary receiver. The proposed algorithm prevents the insecure receiver to access the concerned information, based on randomized framework. By this approach we benefit from random network coding advantages by employing time-variant local vectors at some internal nodes. The cost is probable loss of complete randomness in these few nodes

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“…For instance, Jafari et al [3] have proposed to employ shortened coding vectors to efficiently convey the coding coefficients. They exploit the fact that, in some networks, usually not all source packets are combined.…”

Section: Introductionmentioning

confidence: 99%

Panda: A protocol-assisted network decoding algorithm

Greco

Kieffer

Adjih

et al. 2014

2014 International Symposium on Network Coding (NetCod)

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With random linear network coding, mixed packets contain in their headers information about the coding operations performed on the original packets to allow their recovery by the receiver. This introduces an overhead that could be significant if the packet size is relatively small w.r.t. the size of the generation. In this paper, we propose to remove the part of the added header related to the network coding coefficients and to consider network decoding as a source separation problem. This problem is addressed using a maximum a posteriori estimation technique. It exploits some a priori information related to the content of the headers added to the original packets by the upper layers of the protocol stack, before network coding. Experiments show that, despite the fact that traditional source separation techniques are completely inadequate to handle this scenario, the proposed approach is able to recover all packets within streams of thousands of generations without a single decoding error. 1

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Compressed network coding vectors

Cited by 32 publications

References 11 publications

Low cost security for sensor networks

Low cost security for sensor networks

Hidden sources from an arbitrary receiver

Panda: A protocol-assisted network decoding algorithm

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