Confidentiality and Integrity for Data Aggregation in WSN Using Homomorphic Encryption

Soufiene, Ben Othman; Bahattab, Abdullah Ali; Trad, Abdelbasset; Youssef, Habib

doi:10.1007/s11277-014-2061-z

Cited by 64 publications

(46 citation statements)

References 31 publications

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“…Multiple proposals have been developed, from the aggregation of values [5,6,7,28,29,30,31,32,33,34,35,36], to additions [2,3,26,37,38,39,40,41,42,43], calculus of minimums or maximums [10,44,45] or even more complex tasks such as averages [9,10,30,46], variances [9,46], range queries [6] or logic operations [8].…”

Section: Related Workmentioning

confidence: 99%

“…Anonymity is generally achieved by the use of cryptographic schemes, e.g. symmetric encryption [2,6,7,30] or more sophisticated schemes like homomorphic encryption [8,37,38,39,31,40,41,42,43,46], homomorphic aggregation of signatures [36] and homomorphic encryption with re-randomization applying a proxy [5]. By contrast, Groat et al [44] propose the use of randomized arrays instead of a cryptographic system.…”

Section: Related Workmentioning

confidence: 99%

“…Privacy preservation against observers is considered in [2,3,5,7,8,29,26,44,31,41,42,46,36,25,48]. The use of cryptography is demanding to manage this issue [2,3,5,7,8,28,29,26,38,46,36,25,48], as well as randomized arrays or negative surveys [44].…”

Section: Related Workmentioning

confidence: 99%

“…Verifying that aggregation is correctly performed without polluted results is also addressed by several proposals [6,30,26,28,31,41,35,36,43,25,48]. A monitoring neighbour scheme is proposed in [26], where neighbours of intermediate aggregator nodes monitor their behaviour.…”

Section: Related Workmentioning

confidence: 99%

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PAgIoT – Privacy-preserving Aggregation protocol for Internet of Things

González-Manzano

Fuentes

Pastrana

et al. 2016

Journal of Network and Computer Applications

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Modern society highly relies on the use of cyberspace to perform a huge variety of activities, such as social networking or e-commerce, and new technologies are continuously emerging. As such, computer systems may store a huge amount of information, which makes data analysis and storage a challenge. Information aggregation and correlation are two basic mechanisms to reduce the problem size, for example by filtering out redundant data or grouping similar one. These processes require high processing capabilities, and thus their application in Internet of Things (IoT) scenarios is not straightforward due to resource constraints. Furthermore, privacy issues may arise when the data at stake is personal. In this paper we propose PAgIoT, a Privacy-preserving Aggregation protocol suitable for IoT settings.It enables multi-attribute aggregation for groups of entities while allowing for privacy-preserving value correlation. Results show that PAgIoT is resis- * Corresponding author Email addresses: lgmanzan@inf.uc3m.es (L. González-Manzano a * ), jfuentes@inf.uc3m.es (José M. de Fuentes a ), spastran@inf.uc3m.es (Sergio Pastrana a ), pperis@inf.uc3m.es ( Pedro Peris-Lopez a ), luis@iec.csic.es (Luis Hernández-Encinas b )tant to security attacks, it outperforms existing proposals that provide with the same security features, and it is feasible in resource-constrained devices and for aggregation of up to 10 attributes in big networks.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

See 2 more Smart Citations

PAgIoT – Privacy-preserving Aggregation protocol for Internet of Things

González-Manzano

Fuentes

Pastrana

et al. 2016

Journal of Network and Computer Applications

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“…With varying network topology, such as cluster based [2], tree based [3], chain based [4], various data aggregation schemes have been proposed [4], [5], [6], [7], [8], [9]. Data aggregation mainly exploits the redundancy in the spatially and temporally corelated data sensed by the nodes [10].…”

Section: Related Workmentioning

confidence: 99%

Hierarchical Compressed Sensing for Cluster Based Wireless Sensor Networks

Singh¹,

Kumar²

2016

ijacsa

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Abstract-Data transmission consumes significant amount of energy in large scale wireless sensor networks (WSNs). In such an environment, reducing the in-network communication and distributing the load evenly over the network can reduce the overall energy consumption and maximize the network lifetime significantly. In this work, the aforementioned problem of network lifetime and uneven energy consumption in large scale wireless sensor networks is addressed. This work proposes a hierarchical compressed sensing (HCS) scheme to reduce the innetwork communication during the data gathering process. Corelated sensor readings are collected via a hierarchical clustering scheme. A compressed sensing (CS) based data processing scheme is devised to transmit the data from the source to the sink. The proposed HCS is able to identify the optimal position for the application of CS to achieve reduced and similar number of transmissions on all the nodes in the network. An activity map is generated to validate the reduced and uniformly distributed communication load of the WSN. Based on the number of transmissions per data gathering round, the bit-hop metric model is used to analyse the overall energy consumption. Simulation results validate the efficiency of the proposed method over the existing CS based approaches.

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DoS detection in WSNs: Energy‐efficient methods for selecting monitoring nodes

Monnet

Mokdad

Ballarini

et al. 2017

Concurrency and Computation

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Summary The use of wireless sensor networks (WSNs) has increased rapidly over the last years. Due to their low resources, sensors come along with new issues regarding network security and energy consumption. Focusing on the network availability, previous studies proposed to protect clustered network against denial of service attacks with the use of traffic monitoring agents on some nodes. Those control nodes have to analyze the traffic inside a cluster and to send warnings to the cluster head whenever an abnormal behavior (e.g., high packets throughput or non‐retransmission of packets) is detected. But if the control nodes (cNodes) die out of exhaustion, they leave the network unprotected. To better fight against attacks, we try to enhance this solution by renewing periodically the election process. Furthermore, we propose three energy‐aware and secure methods to designate the cNodes in a hierarchically clustered WSN. The first one is a simple self‐election process where nodes randomly designate themselves. It leads to a better load balancing than a static method (i.e., with no renewal), but we argue that we can obtain better results by considering the remaining energy of the nodes at cNodes selection time. Hence, the second algorithm is purely based on the residual energy of the sensors. We discuss limitations of this deterministic process concerning security and cluster coverage and suggest workarounds. These improvements lead us to the third mechanism. It is based on residual energy too, but it includes a democratic election process in which nodes in the cluster vote to optimize the cNode role attribution. Results obtained from simulation experiments with the ns‐2 tool are provided to analyze the energy repartition in the network and to compare the three selection algorithms. All experimental outcomes show improvements of the load balancing in the network, while maintaining good detection coverage, in regard to static selection. Furthermore, the analysis of the respective performances of the three mechanisms is used as a basis to establish recommendations regarding the use cases of those methods. Copyright © 2017 John Wiley & Sons, Ltd.

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Confidentiality and Integrity for Data Aggregation in WSN Using Homomorphic Encryption

Cited by 64 publications

References 31 publications

PAgIoT – Privacy-preserving Aggregation protocol for Internet of Things

PAgIoT – Privacy-preserving Aggregation protocol for Internet of Things

Hierarchical Compressed Sensing for Cluster Based Wireless Sensor Networks

DoS detection in WSNs: Energy‐efficient methods for selecting monitoring nodes

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