Secure Data Aggregation Protocol Research Articles

Multi-Objective Meta-Heuristic Approach for Energy-Efficient Secure Data Aggregation in Wireless Sensor Networks

Energy consumption in the sensor network is primarily due to the switching states of radio transceivers and long busy states of sensor nodes in the network. Data aggregation techniques reduce the number of transmissions and improve the bandwidth utilization. Secure data aggregation and energy-efficient routing protocols establish the secure channel, and reduce the communication overhead in the network. Multi-objective optimization methods based on the weighted sum method, the utility method and meta-heuristic search methods enhance the performance of meta-heuristic algorithms. This article proposes multi-objective meta-heuristic approach for energy-efficient secure data aggregation (MH-EESDA) protocol in wireless sensor networks. The proposed protocol uses divide-and-conquer approach to form the secure clusters and perform the secure data aggregation in energy-efficient route paths of the network. The protocol functions in three phases. In the first phase, the clusters are formed, in the second phase, the secure nodes are selected and in the third phase, energy-efficient data aggregation is performed across the secure route paths of the network. The sensor node energy and data aggregation rate are evaluated for (1) minimum degree of intrusions (2) threshold-based degree of intrusions and (3) maximum degree of intrusions in the network. Simulation results illustrate significant improvements in the proposed MH-EESDA protocol.

Symmetric-Key Based Homomorphic Primitives for End-to-End Secure Data Aggregation in Wireless Sensor Networks

In wireless sensor networks, secure data aggregation protocols target the two major objectives, namely, security and en route aggregation. Although en route aggregation of reverse multi-cast traffic improves energy efficiency, it becomes a hindrance to end-to-end security. Concealed data aggregation protocols aim to preserve the end-to-end privacy of sensor readings while performing en route aggregation. However, the use of inherently malleable privacy homomorphism makes these protocols vulnerable to active attackers. In this paper, we propose an integrity and privacy preserving end-to-end secure data aggregation protocol. We use symmetric key-based homomorphic primitives to provide end-to-end privacy and end-to-end integrity of reverse multicast traffic. As sensor network has a non-replenishable energy supply, the use of symmetric key based homomorphic primitives improves the energy efficiency and increase the sensor network’s lifetime. We comparatively evaluate the performance of the proposed protocol to show its efficacy and efficiency in resource-constrained environments.

Integrity and Privacy Preserving Secure Data Aggregation in Wireless Sensor Networks

Data aggregation based on in-network processing is useful in improving the communications overhead in Wireless Sensor Networks (WSNs) by reducing the overall number of packets communicated to the base station. However, due to the fusion of data items sourced at different nodes into a single one, the security of the aggregated data as well as that of the aggregating node, demands critical investigation. This paper observes that though there have been substantial numbers of research attempts recently in proposing techniques for secure data aggregation, there is still a need for a coherent, integrated framework for secure data aggregation. It proposes such an integrated framework for secure data aggregation in this paper. The proposed framework implements a secure data aggregation protocol, offering the attributes viz. confidentiality, privacy, authentication, robustness, as well as data integrity using a defined data aggregation topology. In addition to that, the proposed framework is based on a zero configuration protocol that supports a generation of a defined aggregation topology and a key exchange procedure. This work supports the framework with detailed security analysis and performance evaluation on TinyOS platform using TOSSIM as the base simulator. Through humble observations, this is an unique attempt that integrates the support for security features, topology generation and key management in a single, secure data aggregation protocol; substantiating the proposal with elaborate experimental evaluation, too.

Secure Aggregation of Exact Sum Queries with Integrity Protection for Wireless Sensor Networks

The in-network processing consists of data aggregation operations e.g. Summation, averaging, min-max value, variance etc. Data aggregation reduces the number of message transmitted to the Wireless Sensor Network(WSN) by calculating the sub aggregation results at the intermediate nodes. Furthermore the sensor nodes are deployed in open and unsafe environments, so the security of sensed and aggregated data is crucial. This situation necessitates the investigation of the Secure Data Aggregation (SDA) protocol. Many protocols have been proposed concerning finding answers for SUM queries in WSNs but most of them either offer only approximate answers for SUM queries or do not live up to all the security requirements. The focus of the research in this paper is to investigate a SDA protocol which satisfies all the security requirements viz. Confidentiality, Privacy, Authentication, Integrity and Freshness of the query result and also returns the exact answers for SUM queries (as well as their derivatives, e.g., COUNT, AVG, etc). The protocol applies homomorphic encryption that promises the privacy as well as confidentiality of data sent by sensor nodes with innetwork aggregation. The protocol achieves integrity of sensed data by means of secret sharing scheme, message authentication code (MAC) and data diffusion methods. Proposed scheme satisfies all the essential security requirements for secure in-network aggregation. This scheme does not impose extra overhead in communication. Therefore, the scheme is best desirable for resource-restrain WSNs.

Secure Data Accumulation and Certification Procedure for Sensor Networks

The Wireless Sensor Network appears as an emerging technology which consists of thousands of small and low cost sensors. These sensors have limited power, computation, storage and communication capabilities. The data aggregation framework process is required which combines the data coming from various sensors, remove the redundancies in those data and then enroot them. In this paper, we have proposed a secure data aggregation protocol for wireless sensor networks (WSNs) that is robust to deceitful nodes. The goal of this protocol is to guarantee the essential security needs (like authentication, data confidentiality & data integrity) as well as to achieve the low communication overhead and be fitted with various aggregation functions (like sum, average, max, min etc.).To achieve these security needs, it uses symmetric encryption and message authentication code. Encryption ensures data confidentiality while message authentication code ensures authentication and data integrity. An anomaly detection algorithm is used to detect the anomaly or outliers and thus prevent the deceitful corrupted data from being contributed to the final aggregated results.

무선 센서 네트워크에서 Compromised Aggregator에 대응을 위한 모니터링 기반 시큐어 데이터 병합 프로토콜

Data aggregation is important in wireless sensor networks. However, it also introduces many security problems, one of which is that a compromised node may inject false data or drop a message during data aggregation. Most existing solutions rely on encryption, which however requires high computation and communication cost. But they can only detect the occurrence of an attack without finding the attacking node. This makes sensor nodes waste their energy in sending false data if attacks occur repeatedly. Even an existing work can identify the location of a false data injection attack but it has a limitation that at most 50% of total sensor nodes can participate in data transmission. Therefore, a novel approach is required such that it can identify an attacker and also increase the number of nodes which participate in data transmission. In this paper, we propose a monitoring-based secure data aggregation protocol to prevent against a compromised aggregator which injects false data or drops a message. The proposed protocol consists of aggregation tree construction and secure data aggregation. In secure data aggregation, we use integration of abnormal data detection with monitoring and a minimal cryptographic technique. The simulation results show the proposed protocol increases the number of participating nodes in data transmission to 95% of the total nodes. The proposed protocol also can identify the location of a compromised node which injects false data or drops a message. A communication overhead for tracing back a location of a compromised node is O(n) where n is the total number of nodes and the cost is the same or better than other existing solutions.

Mitigating On‐Off attacks in reputation‐based secure data aggregation for wireless sensor networks

AbstractIn‐network aggregation is considered as an efficient way to reduce the energy consumption in wireless sensor networks (WSNs). However, it opens doors for a compromised node to distort the integrity of the aggregated data by altering the data and disrupting transmission of the aggregation results. Thus, several secure data aggregation protocols were designed to mitigate the effect of the node compromise attack and ensure data integrity. Most protocols can detect the manipulation of the aggregation results and then reject them at the base station, which gives a single node compromise the opportunity to disrupt the limited resources in the network. Reputation‐based secure data aggregation protocols take a step further in helping to identify compromised nodes as early as possible. However, reputation‐based protocols are prone to On‐Off attacks (OOs) in which a compromised node is able to affect the aggregation results without being detected. The compromised node behaves maliciously now and then to ensure that its reputation value is within the trustable level. A solution to defeat this attack is proposed in this paper. The significance of the proposal is twofold: (i) it extends Alzaid et al.'s protocol and mitigates the effect of the OO on the aggregation results, and (ii) it considers non‐homogeneous environments, which requires distinguishing between abrupt and incipient changes. In a comparative analysis of our proposal with Alzaid et al.'s protocol, plain estimate, and reputation‐based estimate shows its superior performance in mitigating the effect of the attack. Copyright © 2011 John Wiley & Sons, Ltd.

Secure data aggregation in wireless sensor networks: A comprehensive overview

Wireless sensor networks often consists of a large number of low-cost sensor nodes that have strictly limited sensing, computation, and communication capabilities. Due to resource restricted sensor nodes, it is important to minimize the amount of data transmission so that the average sensor lifetime and the overall bandwidth utilization are improved. Data aggregation is the process of summarizing and combining sensor data in order to reduce the amount of data transmission in the network. As wireless sensor networks are usually deployed in remote and hostile environments to transmit sensitive information, sensor nodes are prone to node compromise attacks and security issues such as data confidentiality and integrity are extremely important. Hence, wireless sensor network protocols, e.g., data aggregation protocol, must be designed with security in mind. This paper investigates the relationship between security and data aggregation process in wireless sensor networks. A taxonomy of secure data aggregation protocols is given by surveying the current “state-of-the-art” work in this area. In addition, based on the existing research, the open research areas and future research directions in secure data aggregation concept are provided.

SDAP

Hop-by-hop data aggregation is a very important technique for reducing the communication overhead and energy expenditure of sensor nodes during the process of data collection in a sensor network. However, because individual sensor readings are lost in the per-hop aggregation process, compromised nodes in the network may forge false values as the aggregation results of other nodes, tricking the base station into accepting spurious aggregation results. Here a fundamental challenge is how can the base station obtain a good approximation of the fusion result when a fraction of sensor nodes are compromised? To answer this challenge, we propose SDAP, a Secure Hop-by-hop Data Aggregation Protocol for sensor networks. SDAP is a general-purpose secure data aggregation protocol applicable to multiple aggregation functions. The design of SDAP is based on the principles of divide-and-conquer and commit-and-attest . First, SDAP uses a novel probabilistic grouping technique to dynamically partition the nodes in a tree topology into multiple logical groups (subtrees) of similar sizes. A commitment-based hop-by-hop aggregation is performed in each group to generate a group aggregate. The base station then identifies the suspicious groups based on the set of group aggregates. Finally, each group under suspect participates in an attestation process to prove the correctness of its group aggregate. The aggregate by the base station is calculated over all the group aggregates that are either normal or have passed the attestation procedure. Extensive analysis and simulations show that SDAP can achieve the level of efficiency close to an ordinary hop-by-hop aggregation protocol while providing high assurance on the trustworthiness of the aggregation result. Last, prototype implementation on top of TinyOS shows that our scheme is practical on current generation sensor nodes such as Mica2 motes.