Efficiently securing data on a wireless sensor network

Healy, Michael; Newe, Thomas; Lewis, Elfed

doi:10.1088/1742-6596/76/1/012063

Cited by 25 publications

(15 citation statements)

References 3 publications

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“…Finally, Table 9 and Table 10 depict a comparison of the main operations (PM, ECDH, ECIES and AES-128 encryption) between the proposed design and software implementations tested by [34–36]. …”

Section: Resultsmentioning

confidence: 99%

Extending the IEEE 802.15.4 Security Suite with a Compact Implementation of the NIST P-192/B-163 Elliptic Curves

Piedra

Braeken

Touhafi

2013

Sensors

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Typically, commercial sensor nodes are equipped with MCUsclocked at a low-frequency (i.e., within the 4–12 MHz range). Consequently, executing cryptographic algorithms in those MCUs generally requires a huge amount of time. In this respect, the required energy consumption can be higher than using a separate accelerator based on a Field-programmable Gate Array (FPGA) that is switched on when needed. In this manuscript, we present the design of a cryptographic accelerator suitable for an FPGA-based sensor node and compliant with the IEEE802.15.4 standard. All the embedded resources of the target platform (Xilinx Artix-7) have been maximized in order to provide a cost-effective solution. Moreover, we have added key negotiation capabilities to the IEEE 802.15.4 security suite based on Elliptic Curve Cryptography (ECC;. Our results suggest that tailored accelerators based on FPGA can behave better in terms of energy than contemporary software solutions for motes, such as the TinyECC and NanoECC libraries. In this regard, a point multiplication (PM) can be performed between 8.58- and 15.4-times faster, 3.40- to 23.59-times faster (Elliptic Curve Diffie-Hellman, ECDH) and between 5.45- and 34.26-times faster (Elliptic Curve Integrated Encryption Scheme, ECIES). Moreover, the energy consumption was also improved with a factor of 8.96 (PM).

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Section: Resultsmentioning

confidence: 99%

Extending the IEEE 802.15.4 Security Suite with a Compact Implementation of the NIST P-192/B-163 Elliptic Curves

Piedra

Braeken

Touhafi

2013

Sensors

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“…Different types of microcontroller are available which have different internal architecture, power consumption, speed and instruction set [7] [8]. Also, sensors vary in their power consumption.…”

Section: Block Diagrammentioning

confidence: 99%

Power Analysis of Sensor Node Using Simulation Tool

Sittalatchoumy¹,

Kanthavel²,

Seetharaman³

2016

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Power consumption of sensor node is analyzed in this paper. In order to analyze the energy consumption, the node model is simulated using Proteus Software tool. The proposed sensor node's power characteristics are measured by using different combinations of microprocessors and sensors. Using this, the energy consumption of the node is calculated. This is a cost-effective method and provides appropriate power model for specific applications.

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“…Most schemes provide encrypting capabilities based on a secret key shared among nodes, either in software [43] or hardware level [44], [45]. In addition, notable advances have been observed in the implementation of Elliptic Curve Cryptography (ECC) [46], [47], which has emerged as a promising alternative to RSA-based algorithms, guaranteeing the same level of security, 18 while employing a much smaller key size.…”

Section: ) Challengesmentioning

confidence: 99%

Machine-to-machine (M2M) communications for e-health applications

Kartsakli

Lalos

Antonopoulos

et al. 2015

Machine-to-Machine (M2M) Communications

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The emerging technology of Machine-to-Machine (M2M) communications is bringing a paradigm shift in healthcare delivery. A broad range of e-Health applications can be conceived, with considerable benefits for both patients and healthcare providers. Many technological challenges have to be met, however, to ensure the widespread adoption of e-Health solutions in the future. In this context, we aim to provide a comprehensive overview on M2M systems for e-Health applications from a wireless communication perspective. We provide an overview of the candidate wireless technologies that are suitable for different parts of the M2M system architecture and then show how these technologies are seamlessly integrated to provide an end-to-end e-Health solution. In particular, we discuss end-toend solution designs and testbed implementations, we present the key security and privacy challenges associated with the sensitive nature of medical data and we summarize the most recent research projects dedicated to e-Health applications. Index TermsMachine-to-Machine (M2M), e-Health, WBAN, M2M Area Network, M2M Communications Network, IEEE 802.15.6, end-to-end communications

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Efficiently securing data on a wireless sensor network

Cited by 25 publications

References 3 publications

Extending the IEEE 802.15.4 Security Suite with a Compact Implementation of the NIST P-192/B-163 Elliptic Curves

Extending the IEEE 802.15.4 Security Suite with a Compact Implementation of the NIST P-192/B-163 Elliptic Curves

Power Analysis of Sensor Node Using Simulation Tool

Machine-to-machine (M2M) communications for e-health applications

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