A Survey on Privacy Preserving Data Aggregation Protocols for Wireless Sensor Networks

Many wireless sensor network (WSN) applications require privacy of the sampled data during transmission from the source nodes to a data collecting device, say a query server. Providing an efficient data aggregation scheme with preserving data privacy is a challenging problem in WSNs. Although the secure data aggregation in WSNs has been well studied in the recent years, there exists a little work, for instance PDA (Privacy-preserving Data Aggregation), which focuses on protecting sensor data not only from adversaries but also from the participating trusted sensor nodes. However, PDA suffers from two problems. The first one is high communication cost due to unnecessary traffics in the network during data transmissions. The second one is high computation cost due to the use of expensive technique to customize sensor data. To resolve the problems, we, in this paper, propose a new private data aggregation scheme for WSNs. The proposed scheme applies the additive property of complex numbers in order to combine sensor data and preserve data privacy during transmissions to the query server. We show from our analytical performance evaluations that our scheme is more efficient than the PDA scheme in terms of both communication and computation costs.

With the exponential rise of pervasive computing applications, data privacy has become much more of an important issue than before. When data is aggregated at each hop in a sensor network, it becomes harder to protect its privacy. A number of privacy preserving data aggregation algorithms have recently appeared for wireless sensor networks (WSNs), very few of them however also address the issue of data integrity along with privacy. Data privacy and integrity are two contrasting objectives to achieve in general. In a privacy preserved data aggregation, it becomes easier for an attacker to inject false data hence, we suggest that both privacy and integrity of data should be treated together. In this paper, we present an energy efficient, privacy preserving data aggregation algorithm which also preserves data integrity in WSNs. We analyze the security of the algorithm and provide proofs for confidentiality and integrity. We enhance this algorithm further to localize, to a certain degree, the corrupt aggregator. We provide the results of our implementation of the algorithm on TelosB motes, illustrating that both the computational overhead and the energy consumption are very low. Finally, we compare our algorithm with other schemes having similar objectives demonstrating that our algorithm performs better in terms of band with usage and energy consumption in a WSN environment.

How to determine the source-visiting sequence among the target sensor nodes and manage the mobile agent (MA) effectively is the crucial problem in Mobile-Agent-based computing model for wireless sensor networks (WSNs). In this paper, we propose a novel improved Directed Diffusion-based MA mechanism (IDDMA) for WSNs. IDDMA uses an improved gradient generation algorithm to set up multiple optimal gradients among sensor nodes. The source nodes will subsequently send two distinct types of the exploratory data packet to implement the discovery of the sources and build the routing tables for the MA routing, respectively. Then, the MA in target region could choose its next-hop node dynamically according to the established routing table for MA in each source node and achieve the data fusion; finally it will return to the Sink. Simulation results show that the mechanism outperforms two existing routing protocols in end-to-end packet delay and average energy consumption.

Providing efficient data aggregation while preserving data privacy is a challenging problem in wireless sensor networks research. In this paper, we present two privacy-preserving data aggregation schemes for additive aggregation functions. The first scheme -cluster-based private data aggregation (CPDA)-leverages clustering protocol and algebraic properties of polynomials. It has the advantage of incurring less communication overhead. The second scheme -Slice-Mix-AggRegaTe (SMART)-builds on slicing techniques and the associative property of addition. It has the advantage of incurring less computation overhead. The goal of our work is to bridge the gap between collaborative data collection by wireless sensor networks and data privacy. We assess the two schemes by privacy-preservation efficacy, communication overhead, and data aggregation accuracy. We present simulation results of our schemes and compare their performance to a typical data aggregation scheme -TAG, where no data privacy protection is provided. Results show the efficacy and efficiency of our schemes. To the best of our knowledge, this paper is among the first on privacy-preserving data aggregation in wireless sensor networks.

Wireless sensor network (WSN), has been a much attracted area for researchers for quite a while. Even with the extensive research activity over the last few years, WSNs still has a lot of ground to cover. Sensor Networks are basically data- centric wireless self-organizing network which is created by the many individual sensor nodes. They are battery driven devices, and as any battery powered devices it too has a limited lifespan. WSNs are widely used for tracking wild animals and border surveillance, enemy tracking, etc. Hence it may not be possible to recharge batteries frequently so the main objective will be to reduce energy consumption. It can be reduced in many ways like effective node placement, clustering, data aggregation, synchronized transmission etc. In this paper we are analyzing some of the available protocols for our further research.

Wireless integrated sensor networks, which include collecting, managing data and communication, are used more and more widely for their low cost and convenient deployment. Nowadays the research concerning each aspect of sensor networks is fairly active. Data Aggregation mechanism is one of the key problems in sensor networks. By considering the data transmission delay and overall network energy efficiency, this chapter develops a game-theoretic model of real-time reliable aggregation (RA-G) mechanism for wireless sensor networks. Based on the study of related literatures, first of all in this chapter, the research status of WSN, the system architecture, the characteristics, and the critical technologies are summarized, current typical routing algorithms of WSN are classified and introduced one by one. Taking the implicit collaborative imperative for sensors to achieve overall network objectives (accomplish real-time collection tasks effectively) subject to individual resource consumption into account, this paper proposes a game-theoretic model of reliable data aggregation architecture in wireless sensor networks, defines a multi-tier data aggregation architecture in which semantic based aggregation and average computation aggregation is performed in sensor-level and node-level aggregation respectively. All nodes that detect the same target join the same logic group. Each selected group leader uses game-theoretic model which tradeoffs between energy dissipation and data transmission delay to determine the degree of aggregation. To meet the real-time constraints and balance the energy consumption between nodes, a decision-making model based on game theory which takes delay compensation into account is proposed in the data-relaying stage. The simulation results show that the use of reliable data aggregation architecture can reduce the total transmission overhead of WSN, make the network more energy-efficient and prolong the lifetime of sensor network. On the other hand, the game-theoretic model used in group-level aggregation and data-relaying stage balance the tradeoffs between the energy dissipation and the timeliness of data transmission; therefore, also RA-G data aggregation mechanism is reliable.

One of the most effective way to prevent unauthorized and corrupted message being forwarded in wireless sensor network. But there is high computational and communication overhead in addition to lack of scalability and resilience to node compromise attacks. So to address these issues, a polynomial-based scheme was recently introduced. However, this scheme and its extensions all have the weakness of a built-in threshold determined by the degree of the polynomial. when the number of messages transmitted is larger than this threshold, the adversary can fully recover the polynomial. In the existing system, an unconditionally secure and efficient source anonymous message authentication (SAMA) scheme is presented which is based on the optimal modified Elgamal signature (MES) scheme on elliptic curves. This MES scheme is secure against adaptive chosen-message attacks in the random oracle model. This scheme enables the intermediate nodes to authenticate the message so that all corrupted message can be detected and dropped to conserve the sensor power. While achieving compromise resiliency, flexible-time authentication and source identity protection, this scheme does not have the threshold problem. While enabling intermediate nodes authentication, this scheme allows any node to transmit an unlimited number of messages without suffering the threshold problem. But by using this method the black hole and gray hole attacks are detected but wormhole attack is doesn't detect. Because the wormhole attack is one of the harmful attacks which degrade the network performance. So, in the proposed system, one innovative technique is introduced which is called an efficient wormhole detection mechanism in the wireless sensor networks. In this method, considers the RTT between two successive nodes and those nodes' neighbor number which is needed to compare those values of other successive nodes. The identification of wormhole attacks is based on the two faces. The first consideration is that the transmission time between two wormhole attack affected nodes is considerable higher than that between two normal neighbor nodes. The second detection mechanism is based on the fact that by introducing new links into the network, the adversary increases the number of neighbors of the nodes within its radius. An experimental result shows that the proposed method achieves high network performance.

In wireless sensor networks, sensor nodes have limited battery power. Data aggregation is an important technique in a wireless sensor network to reduce the energy consumption by eliminating the redundant data and delivering useful data to the user. Data aggregation technique is used to gather the data sensed by the sensor nodes in the network and aggregates the sensed data in an energy-efficient way so that overall network lifetime can be increased. Cluster, tree, chain, and grid are some of the architectures for data aggregation in wireless sensor networks. In this paper, authors present an analysis-based survey of data aggregation protocols for tree-based architecture in wireless sensor networks. The authors analyze each algorithm on the basis of performance measurements such as network lifetime, energy consumption, and node distance. Authors also compare these algorithms on the basis of the preferred parameter and a key feature of each algorithm. In the fifth section of the paper, authors described the proposed approach to construct the data aggregation tree to maximize the network lifetime. In the proposed approach, authors used distance parameter to construct minimum spanning tree, and other parameters such as load and energy are preferred in a balanced manner to reduce the energy consumption and to maximize the network lifetime.

A formal treatment to the security of Concealed Data Aggregation (CDA) and the more general Private Data Aggregation (PDA) is given. While there exist a handful of constructions, rigorous security models and analyses for CDA or PDA are still lacking. Standard security notions for public key encryption, including semantic security and indistinguishability against chosen ciphertext attacks, are refined to cover the multisender nature and aggregation functionality of CDA and PDA in the security model. The proposed security model is sufficiently general to cover most application scenarios and constructions of privacy-preserving data aggregation. An impossibility result on achieving security against adaptive chosen ciphertext attacks in CDA/PDA is shown. A generic CDA construction based on public key homomorphic encryption is given, along with a proof of its security in the proposed model. The security of a number of existing schemes is analyzed in the proposed model.

The main goal of research concerning energy aware routing algorithm for wireless sensor network is to increase the lifetime and long-term connectivity of the wireless sensor networks. However, most of energy aware routing algorithms do not take into account the clustering mechanism efficiently. In this paper, we present an efficient energy aware routing algorithm for the wireless sensor networks. In our algorithm, the data aggregation technique and adaptive clustering mechanism are considered for reducing and compacting the cumulative size of packets on the wireless sensor networks. Simulation results show that the energy usage of EAR-ACM is significantly reduced compared with the previous clustering based routing algorithm for the sensor networks.KeywordsSensor NetworkSensor NodeWireless Sensor NetworkCluster HeadData PacketThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

The current research work in wireless sensor networks has mostly focused on the resolving issues related to power consumption and computational resource constraints in the wireless sensor networks .To achieve the same various specific routing schemes ,MAC and cross layered protocols and techniques have been proposed and designed .But with recent advances the privacy issues related to the data collected and transmitted by the wireless sensor networks had taken the center stage .Privacy preservation in wireless sensor networks has become more challenging because of the wireless nature of communication in WSN as well as its self organizing architecture. The present paper provides a comparative review of various privacy preserving mechanisms proposed and implemented in wireless sensor networks with respect to the privacy notions of k- anonymity and L-diversity. Along with the discussion and analysis the present work is an effort for the pavement of a way towards the future research in the field of privacy preservation in WSN.

With increasing of load in wireless sensor network, congestion will make network performance worse quickly. Network performance will be improved by introducing based on single-hop flow control mechanism for wireless sensor network, in which the former hop nodes of congestion nodes adjust flow to control flow rate coming into congestion nodes. In addition, this mechanism can keep the balance of rate between inflow and outflow in congestion nodes.

Disseminating data generated by sensors to sinks at different locations is one of essential functions in wireless sensor networks (WSNs). Recent research focuses much on how a source node forwards sensing data directly to the sink. In this paper, we propose a novel dissemination scheme that obtains five-layer data aggregation by introducing aggregator layers between sensors and sinks. The five aggregation layers from bottom to top are raw data aggregation, in-node data aggregation, group aggregation, aggregator aggregation and agent aggregation layers. In addition, the proposed network architecture for data delivery comprises two different transfer tiers. The lower tier is WSN and the upper tier is WLAN. The simulation results show that our scheme provides excellent throughput and reduces more power consumption for WSNs.

Wireless sensor networks (WSNs) are wireless ad hoc networks of tiny sensor nodes increasingly deployed for multiple civilian and military applications, including patient monitoring, wildlife monitoring, battlefield surveillance, enemy tracking, etc. Like other computer networks, WSNs must be provided of security services such as key management, confidentiality, integrity and authentication. However, the nature of WSNs and their operational requirements introduce new exciting challenges on security design. Key management is a fundamental security service and a hot topic of research in security for WSNs. In this paper, we will review the state of the art on key management for WSNs and provide a glimpse on current and future developments in this area.

Clustering is a useful mechanism in wireless sensor networks that helps to cope with scalability problems and, if combined with in-network data aggregation, may increase the energy efficiency of the network. At the same time, by assigning a special role to the cluster head nodes, clustering makes the network more vulnerable to attacks. In particular, disabling a cluster head by physical destruction or jamming may render the entire cluster inoperable temporarily until the problem is detected and a new cluster head is elected. Hence, the cluster head nodes may be attractive targets of attacks, and one would like to make it difficult for an adversary to identify them. The adversary can try to identify the cluster head nodes in various ways, including the observation of the cluster head election process itself and the analysis of the traffic patterns after the termination of the cluster head election. In this paper, we focus on the former problem, which we call the private cluster head election problem. This problem has been neglected so far, and as a consequence, existing cluster head election protocols leak too much information making the identification of the elected cluster head nodes easy even for a passive external observer. We propose the first private cluster head election protocol for wireless sensor networks that is designed to hide the identity of the elected cluster head nodes from an adversary that can observe the execution of the protocol.