Gathering Sensor Data in Home Networks with IPFIX

Abstract. New developments in military, health and home areas call for new approaches for data acquisition in real-time. Such application areas frequently include challenging requirements for collection, process-ing and analysis of environmental data. Wireless Sensor Networks can collect such environmental data efficiently. Collected sensor node data needs to be transmitted in an efficient way due to limitations of sensor node resources in battery power and available bandwidth. In this paper, we present a method for efficient transmission of sensor measurement data using the IETF standard IPFIX. We show that its template based design is suitable for efficient transmission of senor data with low band-width consumption. In this paper, we present the protocol and its imple-mentation in Wireless Sensor Networks (WSNs). Additionally, a header compression scheme is introduced which further reduces communication cost during data transmission.

Secure Computation using Leaky Correlations (Asymptotically Optimal Constructions)

Most secure computation protocols can be effortlessly adapted to offload a significant fraction of their computationally and cryptographically expensive components to an offline phase so that the parties can run a fast online phase and perform their intended computation securely. During this offline phase, parties generate private shares of a sample generated from a particular joint distribution, referred to as the correlation. These shares, however, are susceptible to leakage attacks by adversarial parties, which can compromise the security of the entire secure computation protocol. The objective, therefore, is to preserve the security of the honest party despite the leakage performed by the adversary on her share. Prior solutions, starting with $n$-bit leaky shares, either used 4 messages or enabled the secure computation of only sub-linear size circuits. Our work presents the first 2-message secure computation protocol for 2-party functionalities that have $\Theta(n)$ circuit-size despite $\Theta(n)$-bits of leakage, a qualitatively optimal result. We compose a suitable 2-message secure computation protocol in parallel with our new 2-message correlation extractor. Correlation extractors, introduced by Ishai, Kushilevitz, Ostrovsky, and Sahai (FOCS--2009) as a natural generalization of privacy amplification and randomness extraction, recover ``fresh\u27\u27 correlations from the leaky ones, which are subsequently used by other cryptographic protocols. We construct the first 2-message correlation extractor that produces $\Theta(n)$-bit fresh correlations even after $\Theta(n)$-bit leakage. Our principal technical contribution, which is of potential independent interest, is the construction of a family of multiplication-friendly linear secret sharing schemes that is simultaneously a family of small-bias distributions. We construct this family by randomly ``twisting then permuting\u27\u27 appropriate Algebraic Geometry codes over constant-size fields

ID List Forwarding Free Confidentiality Preserving Data Aggregation for Wireless Sensor Networks

Wireless sensor networks (WSNs) are composed of sensor nodes with limited energy which is difficult to replenish. Data aggregation is considered to help reduce communication overhead with in-network processing, thus minimizing energy consumption and maximizing network lifetime. Meanwhile, it comes with challenges for data confidentiality protection. Many existing confidentiality preserving aggregation protocols have to transfer list of sensors' ID for base station to explicitly tell which sensor nodes have actually provided measurement. However, forwarding a large number of node IDs brings overwhelming extra communication overhead. In this paper, we propose provably secure aggregation scheme perturbation-based efficient confidentiality preserving protocol (PEC2P) that allows efficient aggregation of perturbed data without transferring any ID information. In general, environmental data is confined to a certain range; hence, we utilize this feature and design an algorithm to help powerful base station retrieve the ID of reporting nodes. We analyze the accuracy of PEC2P and conclude that base station can retrieve the sum of environmental data with an overwhelming probability. We also prove that PEC2P is CPA secure by security reduction. Experiment results demonstrate that PEC2P significantly reduces node congestion (especially for the root node) during aggregation process in comparison with the existing protocols. © 2013 Liehuang Zhu et al