Role Assignment for Data Aggregation in Wireless Sensor Networks

Patel, Maulin; Venkatesan, S.; Weiner, Doug

doi:10.1109/ainaw.2007.316

Cited by 9 publications

(4 citation statements)

References 12 publications

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“…In addition to the CCM mode, the other three modes are parallelizable. Our proposed scheme can be also implemented in a parallel manner, which will be useful for scenarios having powerful nodes in the network, such as a multi-core base station processing many large packets resulting from data aggregation [49]. The authenticity of the ciphertext depends on the IV or the nonce in the three modes, while it depends on the IV and K for our proposed AEADS.…”

Section: Security Comparisonmentioning

confidence: 99%

Authenticated Encryption Based on Chaotic Neural Networks and Duplex Construction

Abdoun¹,

Assad²,

Hoang

et al. 2021

Symmetry

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In this paper, we propose, implement and analyze an Authenticated Encryption with Associated Data Scheme (AEADS) based on the Modified Duplex Construction (MDC) that contains a chaotic compression function (CCF) based on our chaotic neural network revised (CNNR). Unlike the standard duplex construction (SDC), in the MDC there are two phases: the initialization phase and the duplexing phase, each contain a CNNR formed by a neural network with single layer, and followed by a set of non-linear functions. The MDC is implemented with two variants of width, i.e., 512 and 1024 bits. We tested our proposed scheme against the different cryptanalytic attacks. In fact, we evaluated the key and the message sensitivity, the collision resistance analysis and the diffusion effect. Additionally, we tested our proposed AEADS using the different statistical tests such as NIST, Histogram, chi-square, entropy, and correlation analysis. The experimental results obtained on the security performance of the proposed AEADS system are notable and the proposed system can then be used to protect data and authenticate their sources.

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Section: Security Comparisonmentioning

confidence: 99%

Authenticated Encryption Based on Chaotic Neural Networks and Duplex Construction

Abdoun¹,

Assad²,

Hoang

et al. 2021

Symmetry

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“…Following the works of [9] and [39], we will assume that the UAVs can be assigned to one or more of the following roles at each time interval: (i) a sensor, which observes the target/AOI (called node 0), via a sensor and produces the data which will be relayed to the base station (called node n + 1), (ii) a relay, which simply relays its own data to the next level node without any processing, or (iii) an aggregator, which receives one or more data from other nodes, then aggregates the data of the same type to produce a single data point and sends the aggregated data to the next level node. Figure 2 illustrates the information flow in an aggregation network topology.…”

Section: Uav Role Assignmentmentioning

confidence: 99%

Optimizing Communication and Computation for Multi-UAV Information Gathering Applications

Thammawichai

Sujit

Kerrigan

et al. 2018

IEEE Trans. Aerosp. Electron. Syst.

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Mobile agent networks, such as multi-UAV systems, are constrained by limited resources. In particular, limited energy affects system performance directly, such as system lifetime. It has been demonstrated in the wireless sensor network literature that the communication energy consumption dominates the computational and the sensing energy consumption. Hence, the lifetime of the multi-UAV systems can be extended significantly by optimizing the amount of communication data, at the expense of increasing computational cost. In this work, we aim at attaining an optimal trade-off between the communication and the computational energy. Specifically, we propose a mixed-integer optimization formulation for a multi-hop hierarchical clustering-based self-organizing UAV network incorporating data aggregation, to obtain an energy-efficient information routing scheme. The proposed framework is tested on two applications, namely target tracking and area mapping. Based on simulation results, our method can significantly save energy compared to a baseline strategy, where there is no data aggregation and clustering scheme. I. INTRODUCTIONInexpensive mobile agents, such as unmanned aerial vehicles (UAVs), are useful for several remote monitoring applications such as agriculture [1], geology [2], ecology [3] and forestry [4]. The viability of UAVs for scientific and non-military applications are due to reduced cost of the UAVs, low sensor cost and ease in handling. Typically, these applications are of large scale and the mission time can be shortened by introducing multiple UAVs.Central to these applications is the necessity to have a human-in-the-loop (HITL) capability that increases situational awareness and operator autonomy to modify missions dynamically. For HITL, UAVs have to gather and disseminate information periodically to the operator who may be located at a distant (base station) from the operational arena. Typical information required at the base station is aerial footage [5], which is a communication intensive operation consuming considerable energy. Unfortunately, low cost UAVs have limited flight time due to battery/fuel capacity. Hence, there is a need to find different mechanisms by which flight time endurance can be increased. One way is to use gliders that take advantage of the updrafts to soar for long endurance [6]. However, during soaring it is very difficult to maintain a good resolution of the terrain due to varying UAV height for mapping or surveillance applications. Instead, we propose to optimize the energy consumed by various units in a given aircraft to increase the flight time and hence the UAV team mission time.For many applications [1], [4], it is necessary that a UAV must fly at a constant speed and maintain a prescribed height. Under these conditions, the major energy consumption units are propulsion, sensing, computation and communication. On average, the power consumed during flight is approximately constant. The sensing and the computational units also consume constant power. However, the energy e...

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“…This work demonstrates that the re-encryption schemes can be expensive due to some costly operations. Moreover, the proposed solutions display an important limitation: they rely entirely on symmetric (shared key) cryptography, allowing only the base station to decrypt ciphertexts and, thus, preventing the sensor nodes from employing data aggregation mechanisms [10] on the locally stored data. Although asymmetric mechanisms are known to be more resource-consuming than symmetric ones, they have the advantage of allowing sensors to decrypt the data and perform data aggregation, eliminating redundancy and, thus, minimizing the memory and transmission overheads.…”

Section: Introductionmentioning

confidence: 99%

Design and implementation of data survival in unattended wireless sensor networks

Santos

Margi

2011

30th IEEE International Performance Computing and Communications Conference

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In Wireless Sensor Networks, the base station is generally the only unconditionally trusted entity. If it is not connected for a period of time, the network is left unattended and sensor nodes cannot offload data in real time. Thus, until the base station becomes available, adversaries can compromise some sensor nodes and selectively destroy data. In order to prevent such attacks, providing the so-called "data survival", some strategies can be employed. In this paper, we propose a new strategy based on the concept of secure multi-party protocols. The main advantages of the proposed strategy are not limited to the security, since it (1) preserves privacy, (2) enables the use o data aggregation, (3) enforces a level of trust among nodes, which collaborate to compute functions. Additionally, we implement and evaluate the proposed solution using a real sensor platform. Results show the low cost of the scheme in terms of energy consumption and processing time.

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Role Assignment for Data Aggregation in Wireless Sensor Networks

Cited by 9 publications

References 12 publications

Authenticated Encryption Based on Chaotic Neural Networks and Duplex Construction

Authenticated Encryption Based on Chaotic Neural Networks and Duplex Construction

Optimizing Communication and Computation for Multi-UAV Information Gathering Applications

Design and implementation of data survival in unattended wireless sensor networks

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