Two-tiered Sensor Networks Research Articles

An integrity-preserving technique for range queries over data streams in two-tier sensor networks

Two-tier sensor networks enable energy and computation saving due to the introduction of non-constrained storage nodes acting as intermediates between the sensors, which provide data, and the sink, which needs to access these data by submitting queries to the storage nodes. However, the storage nodes maintain a lot of data coming from different sensors and represent a single point of failure targeted by the attackers. In this scenario, robust guarantees about the integrity of the query result (i.e., completeness, freshness, and correctness) should be provided. This is a very well-known problem, traditionally faced through Merkle-Hash-Tree-based data structures. This paper presents a technique more efficient than the state-of-the-art methods for data insertions and deletions, supporting range queries over even non-temporal dimensions. Thus, the proposed solution appears suitable to the considered scenario, in which data can be updated with high frequency and insertions and deletions are executed by constrained devices.

Securing top-k query processing in two-tiered sensor networks

ABSTRACT Integrity and privacy are two important secure matrices in cyber security. Due to the limited resources and computing capability of the sensor nodes, it is challenging to simultaneously satisfy these two matrices for top-k querying in two-tiered sensor networks. To solve this problem, this paper proposes a weight-bind-based secure top-k query processing scheme (WBB-TQ), which utilises both the order-preserving symmetric encryption scheme (OPES) and the pairwise-key encryption technique to ensure data privacy in top-k querying. Since OPES can keep the size orders of the sensed data items unchanged before and after they are encrypted, the upper-layer storage nodes in the network can process top-k queries without knowing the exact values of the sensed data items. To guarantee the completeness of query results, we propose a novel method to establish chaining relationship among all the data items generated by each sensor node. By checking whether the relationship holds on not, Sink can find out whether adversaries drop and/or tamper with part or all of the qualified top-k data items in the query results. Theoretical analyses show that WBB-TQ can preserve data integrity and privacy of the top-k query results. Extensive simulation results further demonstrate that, WBB-TQ incurs very low computational and communication cost in securing top-k querying.

Relay Node Placement Based on Optimal Transmission Distance in Two-Tiered Sensor Network

With the gradual expansion of the application field in wireless sensor networks, the problems of the energy consumption has received more and more attention. In wireless sensor networks, the location of sensor nodes and gateway nodes are usually fixed. To ensure that the energy consumption of the sensor network is minimized during data transmission, it is necessary to optimize the placement of relay nodes. This paper proposes the solution of relay nodes placement based on optimal transmission distance, which can minimize the energy consumption and extend the lifetime of the entire network during the transmission process. This scheme starts with a one-dimensional queue network and calculates the optimal distance for each hop transmission to minimize the energy consumption of the one-dimensional queue network. Due to the poor connectivity of the one-dimensional queue network, the concept of the optimal transmission distance is introduced into two-dimensional network, so that the placement scheme can be divided into the symmetrical relay node placement and the asymmetric relay node placement. Finally, the energy consumption of the network is minimized by properly selecting relay nodes. The simulation show that the proposed relay node placement scheme can reduce the energy consumption of the sensor network and extend the network life cycle.

α-Fraction First Strategy for Hierarchical Model in Wireless Sensor Networks

Energy hole refers to the critical issue near the sinks for data collecting, this problem effects the lifetime of wireless sensor network to a great extent. Frequently data forwarding from distributed sensors to the sink will speed up the energy consumption of the sensors near the sink. This circumstance shortens the lifetime of the sensor network. In this paper, an α-fraction first strategy was proposed to build a hierarchical model of wireless sensor networks that concerning the energy consumption. The model mixes the so-called relay nodes into the network for transmitting and collecting data from the other sensor nodes. We studied the Farthest First traversal and Harel methods, then combined the proposed α-fraction first strategy with the two methods respectively. Three algorithms of FF+Fr(α), HD+Fr(α), and HL+Fr(α) were designed for determining the relay nodes in sensor networks. The algorithms can be used to construct a two-tier sensor network with fewer relay nodes than the results of the Farthest First traversal and Harel methods. The proposed strategy also could be used with any other algorithms that regarding for choosing one of many options. The simulation results show that our proposed algorithms perform well. Thus, the network lifetime can be prolonged.

Privacy and Integrity Preserving Top- $k$ Query Processing for Two-Tiered Sensor Networks

Privacy and integrity have been the main road block to the applications of two-tiered sensor networks. The storage nodes, which act as a middle tier between the sensors and the sink, could be compromised and allow attackers to learn sensitive data and manipulate query results. Prior schemes on secure query processing are weak, because they reveal non-negligible information, and therefore, attackers can statistically estimate the data values using domain knowledge and the history of query results. In this paper, we propose the first top- $k$ query processing scheme that protects the privacy of sensor data and the integrity of query results. To preserve privacy, we build an index for each sensor collected data item using pseudo-random hash function and Bloom filters and transform top- $k$ queries into top-range queries. To preserve integrity, we propose a data partition algorithm to partition each data item into an interval and attach the partition information with the data. The attached information ensures that the sink can verify the integrity of query results. We formally prove that our scheme is secure under IND-CKA security model. Our experimental results on real-life data show that our approach is accurate and practical for large network sizes.

CSRQ: Communication-Efficient Secure Range Queries in Two-Tiered Sensor Networks.

In recent years, we have seen many applications of secure query in two-tiered wireless sensor networks. Storage nodes are responsible for storing data from nearby sensor nodes and answering queries from Sink. It is critical to protect data security from a compromised storage node. In this paper, the Communication-efficient Secure Range Query (CSRQ)—a privacy and integrity preserving range query protocol—is proposed to prevent attackers from gaining information of both data collected by sensor nodes and queries issued by Sink. To preserve privacy and integrity, in addition to employing the encoding mechanisms, a novel data structure called encrypted constraint chain is proposed, which embeds the information of integrity verification. Sink can use this encrypted constraint chain to verify the query result. The performance evaluation shows that CSRQ has lower communication cost than the current range query protocols.

Random Secure Comparator Selection Based Privacy-Preserving MAX/MIN Query Processing in Two-Tiered Sensor Networks

Privacy-preserving data queries for wireless sensor networks (WSNs) have drawn much attention recently. This paper proposes a privacy-preserving MAX/MIN query processing approach based on random secure comparator selection in two-tiered sensor network, which is denoted by RSCS-PMQ. The secret comparison model is built on the basis of the secure comparator which is defined by 0-1 encoding and HMAC. And the minimal set of highest secure comparators generating algorithm MaxRSC is proposed, which is the key to realize RSCS-PMQ. In the data collection procedures, the sensor node randomly selects a generated secure comparator of the maximum data into ciphertext which is submitted to the nearby master node. In the query processing procedures, the master node utilizes the MaxRSC algorithm to determine the corresponding minimal set of candidate ciphertexts containing the query results and returns it to the base station. And the base station obtains the plaintext query result through decryption. The theoretical analysis and experimental result indicate that RSCS-PMQ can preserve the privacy of sensor data and query result from master nodes even if they are compromised, and it has a better performance on the network communication cost than the existing approaches.

An Efficient Top-kQuery Processing with Result Integrity Verification in Two-Tiered Wireless Sensor Networks

In two-tiered wireless sensor networks, storage nodes take charge of both storing the sensing data items and processing the query request issued by the base station. Due to their important role, storage nodes are more attractive to adversaries in a hostile environment. Once a storage node is compromised, attackers may falsify or abandon the data when answering the query issued by the base station, which will make the base station get incorrect or incomplete result. This paper proposes an efficient top-kquery processing scheme with result integrity verification named as ETQ-RIV in two-tiered sensor networks. According to the basic idea that sensor nodes submit some encoded message containing the sequence relationship as proof information for verification along with their collected sensing data items, a data binding and collecting protocol and a verifiable query response protocol are proposed and described in detail. Detailed quantitative analysis and evaluation experiments show that ETQ-RIV performs better than the existing work in both communication cost and query result redundancy rate.

Privacy-preserving data aggregation in two-tiered wireless sensor networks with mobile nodes.

Privacy-preserving data aggregation in wireless sensor networks (WSNs) with mobile nodes is a challenging problem, as an accurate aggregation result should be derived in a privacy-preserving manner, under the condition that nodes are mobile and have no pre-specified keys for cryptographic operations. In this paper, we focus on the SUM aggregation function and propose two privacy-preserving data aggregation protocols for two-tiered sensor networks with mobile nodes: Privacy-preserving Data Aggregation against non-colluded Aggregator and Sink (PDAAS) and Privacy-preserving Data Aggregation against Colluded Aggregator and Sink (PDACAS). Both protocols guarantee that the sink can derive the SUM of all raw sensor data but each sensor's raw data is kept confidential. In PDAAS, two keyed values are used, one shared with the sink and the other shared with the aggregator. PDAAS can protect the privacy of sensed data against external eavesdroppers, compromised sensor nodes, the aggregator or the sink, but fails if the aggregator and the sink collude. In PDACAS, multiple keyed values are used in data perturbation, which are not shared with the aggregator or the sink. PDACAS can protect the privacy of sensor nodes even the aggregator and the sink collude, at the cost of a little more overhead than PDAAS. Thorough analysis and experiments are conducted, which confirm the efficacy and efficiency of both schemes.

A Privacy and Integrity Preserving Range Query Protocol in Two-Tiered Sensor Networks

A Privacy and Integrity Preserving Range Query Protocol in Two-Tiered Sensor Networks

Quality Analysis of Massive High-Definition Video Streaming in Two-Tiered Embedded Camera-Sensing Systems

This paper presents the quality analysis results of high-definition video streaming in two-tiered camera sensor network applications. In the camera-sensing system, multiple cameras sense visual scenes in their target fields and transmit the video streams via IEEE 802.15.3c multigigabit wireless links. However, the wireless transmission introduces interferences to the other links. This paper analyzes the capacity degradation due to the interference impacts from the camera-sensing nodes to the main aggregation link (AL), that is, the link from AL transmitter to AL receiver. For the study, IEEE 802.15.3c specific path-loss and antenna models are used for more precise evaluation. Finally, the quality analysis results are presented in terms of the number of cameras in a cell, beamwidth, the transmit power at camera sensor nodes, and the transmit power at AL nodes. With the listed factors, the analysis quantifies the actual video quality degradation in the presented camera sensing system.

A study towards applying thermal inertia for energy conservation in rooms

We are in an age where people are paying increasing attention to energy conservation around the world. The heating and air-conditioning systems of buildings introduce one of the largest chunks of energy expenses. In this article, we make a key observation that after a meeting or a class ends in a room, the indoor temperature will not immediately increase to the outdoor temperature. We call this phenomenon thermal inertia . Thus, if we arrange subsequent meetings in the same room rather than in a room that has not been used for some time, we can take advantage of such undissipated cool or heated air and conserve energy. Though many existing energy conservation solutions for buildings can intelligently turn off facilities when people are absent, we believe that understanding thermal inertia can lead system designs to go beyond on-and-off-based solutions to a wider realm. We propose a framework for exploring thermal inertia in room management. Our framework contains two components. (1) The energy-temperature correlation model captures the relation between indoor temperature change and energy consumption. (2) The energy-aware scheduling algorithms: given information for the relation between energy and temperature change, energy-aware scheduling algorithms arrange meetings not only based on common restrictions, such as meeting time and room capacity requirement, but also energy consumptions. We identify the interface between these components so further works towards same on direction can make efforts on individual components. We develop a system to verify our framework. First, it has a wireless sensor network to collect indoor, outdoor temperature and electricity expenses of the heating or air-conditioning devices. Second, we build an energy-temperature correlation model for the energy expenses and the corresponding room temperature. Third, we develop room scheduling algorithms. In detail, we first extend the current sensor hardware so that it can record the electricity expenses in re-heating or re-cooling a room. As the sensor network needs to work unattendedly, we develop a hardware board for long-range communications so that the Imote2 can send data to a remote server without a computer relay close by. An efficient two-tiered sensor network is developed with our extended Imote2 and TelosB sensors. We apply laws of thermodynamics and build a correlation model of the energy needed to re-cool a room to a target temperature. Such model requires parameter calibration and uses the data collected from the sensor network for model refinement. Armed with the energy-temperature correlation model, we develop an optimal algorithm for a specified case, and we further develop two fast heuristics for different practical scenarios. Our demo system is validated with real deployment of a sensor network for data collection and thermodynamics model calibration. We conduct a comprehensive evaluation with synthetic room and meeting configurations, as well as real class schedules and classroom topologies of The Hong Kong Polytechnic University, academic calendar year of Spring 2011. We observe 20% energy savings as compared with the current schedules.

A Novel Verification Scheme for Fine-Grained Top-k Queries in Two-Tiered Sensor Networks

A two-tiered architecture with resource-rich master nodes at the upper tier and resource-poor sensor nodes at the lower tier is expected to be adopted in large scale sensor networks. In a hostile environment, adversaries are more motivated to compromise the master nodes to break the authenticity and completeness of query results, whereas it is lack of light and secure query processing protocol in tiered sensor networks at present. In this paper, we study the problem of verifiable fine-grained top- $$k$$ k queries in two-tiered sensor networks, and propose a novel verification scheme, which is named Verification Scheme for Fine-grained Top- $$k$$ k Queries (VSFTQ). To make top- $$k$$ k query results verifiable, VSFTQ establishes relationships among data items of each sensor node using their orders, which are encrypted together with the scores of the data items and the interested time epoch number using distinct symmetric keys kept by each sensor node and the network owner. Both theoretical analysis and simulation results show that VSFTQ can not only ensure high probability of detecting forged and/or incomplete query results, but also significantly decrease the amount of verification information when compared with existing schemes.

Privacy and integrity preserving skyline queries in tiered sensor networks

Storage nodes in two-tiered sensor networks are responsible for storing sensor-collected data and processing the sink-issued queries. Therefore, storage nodes are vulnerable to attack because of their importance. In this paper, we propose a privacy and integrity preserving protocol called SSQ, which is able to prevent compromised storage nodes from leaking sensitive data and allows the sink to detect the misbehaviors of compromised storage nodes. For privacy preserving, a size-limited bucketing technique is proposed to mix the data in a range, and a prefix membership verification technique based on Bloom filters is developed to perform skyline queries on encrypted data items. For integrity preserving, a Merkle hash tree-based technique is investigated to prevent compromised storage nodes from tampering and dropping data. Detailed performance evaluations confirm the high efficacy and efficiency of SSQ. Copyright © 2013 John Wiley & Sons, Ltd.

EMQP: An Energy-Efficient Privacy-Preserving MAX/MIN Query Processing in Tiered Wireless Sensor Networks

We consider a hybrid two-tiered sensor network consisting of regular resource-limited sensor nodes and powerful master nodes with abundant resources. In the architecture, master nodes take charge of storing data collected by sensor nodes and processing queries from the base station. Due to the important role of master nodes, they might easily become the target for the adversary to compromise in an untrusted or hostile circumstance. A compromised master node may leak sensitive data in its storage to the adversary, which breaches the data privacy. This paper proposes EMQP, a novel and energy-efficient privacy-preserving MAX/MIN query protocol which is capable of preventing adversaries from obtaining sensitive data collected by sensor nodes. To preserve privacy, the 0-1 encoding verification, keyed-hash message authentication coding, and symmetric encryption are applied to achieve the secret comparison of data items without knowing their real values. On the basis of secret comparison mechanism, the data submission and query processing protocols are proposed to describe the details of EMQP. And the analyses on privacy protection and energy consumption are also given. Moreover, a hash-based optimization method is presented to save more energy of the resource-limited sensor nodes. The simulation result shows that EMQP is more efficient than the current work in energy consumption.

Privacy- and Integrity-Preserving Range Queries in Sensor Networks

The architecture of two-tiered sensor networks, where storage nodes serve as an intermediate tier between sensors and a sink for storing data and processing queries, has been widely adopted because of the benefits of power and storage saving for sensors as well as the efficiency of query processing. However, the importance of storage nodes also makes them attractive to attackers. In this paper, we propose SafeQ, a protocol that prevents attackers from gaining information from both sensor collected data and sink issued queries. SafeQ also allows a sink to detect compromised storage nodes when they misbehave. To preserve privacy, SafeQ uses a novel technique to encode both data and queries such that a storage node can correctly process encoded queries over encoded data without knowing their values. To preserve integrity, we propose two schemes--one using Merkle hash trees and another using a new data structure called neighborhood chains--to generate integrity verification information so that a sink can use this information to verify whether the result of a query contains exactly the data items that satisfy the query. To improve performance, we propose an optimization technique using Bloom filters to reduce the communication cost between sensors and storage nodes.

Verifiable Privacy-Preserving Sensor Network Storage for Range Query

We consider a hybrid two-tiered sensor network consisting of regular sensors and special sensors with large storage capacity, called storage nodes. In this structure, regular sensors push” their raw data to nearby storage nodes and the sink diffuses queries only to storage nodes and pull” the reply from them. We investigate security and privacy threats when the sensor network is deployed in an untrusted or hostile environment. The major concern is that storage nodes might easily become the target for the adversary to compromise due to their important role. A compromised storage node may leak the data stored there to the adversary breaching the data privacy. Also, it may send wrong information as the reply to a query breaking the data integrity. This paper focuses on range query, a fundamental operation in a sensor network. The solution framework includes a privacy-preserving storage scheme which utilizes a bucketing technique to mix the data in a certain range, and a verifiable query protocol which employs encoding numbers to enable the sink to validate the reply. We further study the performance of event detection, an application implemented by range query. Our simulation results illustrate that our schemes are efficient for communication and effective for privacy and security protection.

SEF: A Secure, Efficient, and Flexible Range Query Scheme in Two-Tiered Sensor Networks

Large-scale wireless sensor networks follow the two-tiered architecture, where master nodes take charge of storing data and processing queries. However, if a master node is compromised, the information stored in it may be exposed, and query results can be juggled. This paper presents a novel scheme called SEF for secure range queries. To preserve privacy, SEF employs the order-preserving symmetric encryption which not only supports efficient range queries, but also maintains a strong security standard. To preserve authenticity and integrity of query results, we propose a novel data structure called Authenticity & Integrity tree. Moreover, SEF is flexible since it allows users to include or exclude the authenticity and integrity guarantee. To the best of our knowledge, this paper is the first to use the characteristic of NAND flash to achieve high storage utilization and query processing efficiency. The efficiency of the proposed scheme is demonstrated by experiments on real sensor platforms.

A Spatiotemporal Approach for Secure Range Queries in Tiered Sensor Networks

We target a two-tier sensor network with resource-rich master nodes at the upper tier and resource-poor sensor nodes at the lower tier. Master nodes collect data from sensor nodes and answer the queries from the network owner. The reliance on master nodes for data storage and query processing raises serious concerns about both data confidentiality and query-result correctness in hostile environments. In particular, a compromised master node may leak hosted sensitive data to the adversary; it may also return juggled or incomplete data in response to a query. This paper presents a novel spatiotemporal approach to ensure secure range queries in event-driven two-tier sensor networks. It offers data confidentiality by preventing master nodes from reading hosted data and also enables efficient range-query processing. More importantly, it allows the network owner to verify with very high probability whether a query result is authentic and complete by examining the spatial and temporal relationships among the returned data. The high efficacy and efficiency of our approach are confirmed by detailed performance evaluations.

Routing-Aware Clustering Algorithms for Two-Tiered Sensor Networks

In hierarchical two-tiered sensor networks, higher-powered relay nodes can be used as cluster heads for designing scalable sensor networks. It has been shown that, in such networks, the assignment of sensor nodes to clusters plays an important role in determining the lifetime of the network. In this paper, we have proposed two routing-aware, distributed algorithms for assigning sensor nodes to clusters in two-tiered networks. The first heuristic assumes that all relay nodes, acting as cluster heads, send their data directly to the base station. The second heuristic relaxes this assumption and is to be used with any network where each relay node uses a multihop route to send its data to the base station. Unlike conventional clustering algorithms, our approaches take into consideration the routing scheme used by the relay nodes, and attempt to balance the energy dissipation of the nodes. We have compared the results of our distributed approaches with the optimal solutions obtained using an integer linear program (ILP) formulation, as well as existing techniques, based on heuristics. The results indicate that our approaches, on average, can produce results that are close to the optimal solutions and consistently outperform existing heuristics.