A survey of security issues in wireless sensor networks <s> PLAIN-TEXT BASED SECURE DATA AGGREGATION <s> An emerging class of important applications uses ad hoc wireless networks of low-power sensor devices to monitor and send information about a possibly hostile environment to a powerful base station connected to a wired network. To conserve power, intermediate network nodes should aggregate results from individual sensors. However, this opens the risk that a single compromised sensor device can render the network useless, or worse, mislead the operator into trusting a false reading. We present a protocol that provides a secure aggregation mechanism for wireless networks that is resilient to both intruder devices and single device key compromises. Our protocol is designed to work within the computation, memory and power consumption limits of inexpensive sensor devices, but takes advantage of the properties of wireless networking, as well as the power asymmetry between the devices and the base station. <s> BIB001 </s> A survey of security issues in wireless sensor networks <s> PLAIN-TEXT BASED SECURE DATA AGGREGATION <s> Secure data transmission and data aggregation are critical in designing cluster-based sensor networks. This paper presents an Energy-efficient and Secure Pattern-based Data Aggregation protocol (ESPDA) for wireless sensor networks. ESPDA is energy and bandwidth efficient because cluster-heads prevent the transmission of redundant data from sensor nodes. ESPDA is also secure because it does not require the encrypted data to be decrypted by cluster-heads to perform data aggregation. In ESPDA, cluster-head first requests sensor nodes to send the corresponding pattern code for the sensed data. If multiple sensor nodes send the same pattern code to the cluster-head, then only one of them is permitted to send the data to the cluster-head. Hence, ESPDA has advantages over the conventional data aggregation techniques with respect to energy, bandwidth efficiency and security. Simulations results show that as data redundancy increases, the amount of data transmitted from sensor nodes to cluster-head decreases up to 45% when compared to conventional algorithms. <s> BIB002 </s> A survey of security issues in wireless sensor networks <s> PLAIN-TEXT BASED SECURE DATA AGGREGATION <s> Wireless sensor networks consist of many inexpensive wireless nodes, each having sensing capability with some computational and communication power. Asymmetric cryptographic algorithms are not suitable for providing security on wireless sensor networks due to limited computation, power, and storage resources available on sensor nodes. Therefore, the energy-efficient security protocol proposed in this paper uses symmetric cryptographic algorithms to support security. To mitigate the drawbacks of symmetric cryptographic algorithms, the session key is changed dynamically, in addition to employing code-hopping technique in non-blocking OVSF codes. <s> BIB003 </s> A survey of security issues in wireless sensor networks <s> PLAIN-TEXT BASED SECURE DATA AGGREGATION <s> In wireless sensor networks, sensor nodes are spread randomly over the coverage area to collect information of interest. Data fusion is used to process these collected information before they are sent to the base station, the observer of the sensor network. We study the security of the data fusion process in this work. In particular, we propose a witness-based solution to assure the validation of the data sent from data fusion nodes to the base station. We also present the theoretical analysis for the overhead associated with the mechanism, which indicates that even in an extremely harsh environment the overhead is low for the proposed mechanism. <s> BIB004 </s> A survey of security issues in wireless sensor networks <s> PLAIN-TEXT BASED SECURE DATA AGGREGATION <s> In sensor networks, data aggregation is a vital primitive enabling efficient data queries. An on-site aggregator device collects data from sensor nodes and produces a condensed summary which is forwarded to the off-site querier, thus reducing the communication cost of the query. Since the aggregator is on-site, it is vulnerable to physical compromise attacks. A compromised aggregator may report false aggregation results. Hence, it is essential that techniques are available to allow the querier to verify the integrity of the result returned by the aggregator node. ::: ::: We propose a novel framework for secure information aggregation in sensor networks. By constructing efficient random sampling mechanisms and interactive proofs, we enable the querier to verify that the answer given by the aggregator is a good approximation of the true value, even when the aggregator and a fraction of the sensor nodes are corrupted. In particular, we present efficient protocols for secure computation of the median and average of the measurements, for the estimation of the network size, for finding the minimum and maximum sensor reading, and for random sampling and leader election. Our protocols require only sublinear communication between the aggregator and the user. <s> BIB005
Hu and Evans proposed a secure aggregation (SA) protocol for WSNs that is resilient to both intruder devices and single device key compromises BIB001 . However, the protocol may be vulnerable if a parent and a child node in the hierarchy are compromised. Przydatek et al. proposed a secure information aggregation (SIA) framework for sensor networks BIB005 . The framework consists of three node categories: a home server, base station(s), and sensor nodes. A base station is a resourcesenhanced node which is used as intermediary between the home server and the sensor nodes, and is also the candidate to perform the aggregation task. SIA assumes that each sensor has a unique identifier and shares a separate secret cryptographic key with both the home server and the aggregator. The keys enable message authentication and encryption if data confidentiality is required. Moreover, it further assumes that the home server and base station can use a mechanism, such as µTESLA, to broadcast authentic messages. The proposed solution consists of three parts: computation of the result, committing to the collected data, and reporting the aggregation result while proving the correctness of the result. In the first part, the aggregator collects the data from sensors and locally computes the aggregation result. The aggregator can verify the authenticity of each sensor reading. In the second part, the aggregator commits to the collected data. The commitment to the input data ensures that the aggregator uses the data provided by the sensors, and that the statement to be verified by the home server about the correctness of computed results is meaningful. One efficient way of committing to the data is a Merkle hash-tree construction. In this construction, all the data collected from the sensors is placed at the leaves of the tree. The aggregator then computes a binary hash tree starting from the leaf nodes. Each internal node in the hash tree is computed as the hash value of the concatenation of its two child nodes. The root of the tree is called the commitment of the collected data. As the hash function in use is collision resistant, once the aggregator commits to the collected values it cannot change any of them. Figure 5 shows an example of a Merkle hash tree. In the third part, the aggregator and the home server engage in a protocol in which the aggregator communicates the aggregation result and the commitment to the server while proving to the server that the reported results are correct using interactive proof protocols. Moreover, the authors also presented efficient protocols for secure computation of the median and average of the measurements, for the estimation of the network size, and for finding the minimum and maximum sensor reading. Deng et al. proposed a collection of mechanisms for securing in-network processing (SINP) for WSNs  . Security mechanisms were proposed to address the downstream requirement that sensor nodes authenticate commands disseminated from parent aggregators and the upstream requirement that aggregators authenticate data produced by sensors before aggregating that data. In the downstream stage, two techniques are involved: one-way functions and µTESLA. The SA BIB001 , SIA BIB005 , SINP  , ESPDA BIB002 BIB003 SDDA  , WDA BIB004 CDA  , HSC  Plaintext-based aggregation