Comparative performance and energy consumption analysis of different AES implementations on a wireless sensor network node

Zhang, Fan; Dojen, Reiner; Coffey, Tom

doi:10.1504/ijsnet.2011.042767

Cited by 38 publications

(19 citation statements)

References 32 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…They do not however study this implementation on different plaintext lengths and instead rely on datasheets to extend to lengths longer than one block. However, this conclusion is not backed by Zhang et al in [6] which compares different AES implementations on the MicaZ nodes. They conclude that hardware assisted encryption is faster, but also consumes more energy due to the external chip which handles the computation in hardware.…”

Section: Related Workmentioning

confidence: 87%

“…We also refer to these hybrids as hardware implementations. For the pure software implementation we used an optimized version of AES, called TableLookupAES [6].…”

Section: Methodsmentioning

confidence: 99%

“…We also built on the work of Zhan [6] and showed that the newer ATmega128RFA1 microcontroller with an integrated transceiver, used in the Sparrow v3.2 node, can reduce both the duration and the energy consumption of AES operations. This is in contrast to work done on previous sensor nodes, that used a separated microcontroller and transceiver and which had a higher energy cost when running the encryption in hardware as opposed to using a pure software implementation.…”

Section: ) Energy Experimentsmentioning

confidence: 99%

See 2 more Smart Citations

Measuring the performance and energy consumption of AES in wireless sensor networks

Panait¹,

Dragomir²

2015

Annals of Computer Science and Information Systems

View full text Add to dashboard Cite

Abstract-With WSN deployments increasing in popularity, securing those deployments becomes a necessity. This can be achieved by encrypting inter-node communications and/or using message authentication codes. AES is a well studied symmetric cipher, with no known practical vulnerabilities, that can be used to solve both problems. We provide an optimized implementation of AES, with four modes of operation (ECB, CBC, CFB and CTR), that uses the hardware accelerator available on the ATmega128RFA1 microcontroller, and compare it with the best known software implementation. We show that our hardware AES implementation is both faster and more energy efficient than a software implementation. This is not the case for previous sensor nodes and implementations, which show an improved execution speed, but with a higher energy consumption.

show abstract

Section: Related Workmentioning

confidence: 87%

“…We also refer to these hybrids as hardware implementations. For the pure software implementation we used an optimized version of AES, called TableLookupAES [6].…”

Section: Methodsmentioning

confidence: 99%

Section: ) Energy Experimentsmentioning

confidence: 99%

See 1 more Smart Citation

Measuring the performance and energy consumption of AES in wireless sensor networks

Panait¹,

Dragomir²

2015

Annals of Computer Science and Information Systems

View full text Add to dashboard Cite

show abstract

“…The plaintext is initially organised into a State array, which is a 4x4 array of bytes, and the key is expanded into the required number of round keys [60]. Each round consists of 4 operations, AddRoundKey (combine each round key with the state), SubBytes (replace each byte with another according to Rijndael"s S-Box), ShiftRows (shift each row with a certain offset) and MixColumns (the 4 bytes in every column are combined using an invertible linear transformation).…”

Section: Department Of Electrical Electronic and Computer Engineerinmentioning

confidence: 99%

“…It was however found that it is still feasible for use on these wireless devices. There have also been many proposed optimised implementations that improve the algorithms performance [60].…”

Section: Department Of Electrical Electronic and Computer Engineerinmentioning

confidence: 99%

Data aggregation using homomorphic encryption in wireless sensor networks

Ramotsoela

Hancke

2015

2015 Information Security for South Africa (ISSA)

View full text Add to dashboard Cite

Degree:Master of Engineering (Computer Engineering)Keywords: wireless sensor networks, homomorphic encryption, network security, aggregation Wireless sensor networks have become increasingly popular in many applications such as environment monitoring and law enforcement. Data aggregation is a method used to reduce network traffic but cannot be used together with conventional encryption schemes because it is not secure and introduces extra overhead. Homomorphic encryption is an encryption scheme that allows data processing on encrypted data as opposed to plaintext. It has the benefit that each intermediate node does not have to decrypt each packet, but the resulting cyphertext is usually much larger than the original plaintext. This could negatively affect system performance because the energy consumption of each node is directly proportional to the amount of data it transmits.This study investigates the benefits and drawback of using homomorphic encryption in the aggregation process particularly in the context of scalable networks. It was found that conventional encryption outperforms the homomorphic encryption for smaller networks, but as the network size grows, homomorphic encryption starts outperforming conventional encryption. It was also found that the homomorphic encryption scheme does significantly reduce the performance of plaintext aggregation. This performance reduction will however be acceptable for most applications where security is a concern. ............................................................................ . The sensor changes depending on the specific application the sensor node is used in.The processor is usually a simple processor with low computational power. The power source is usually a limited power supply such as commercial battery.These resource constraints mean that the efficiency of data transfer is paramount in these applications. This is because the energy consumption of the nodes is directly proportional to the amount of data transferred [2]. One of the methods that can be used to reduce traffic in the network is called data aggregation. This process involves combining data coming from different sources enroute [3].Aggregation however becomes a problem when security is an issue in the system [4]. This is because each node would have to decrypt each packet, aggregate the data, and then encrypt the result before sending it to the next hop. Secure information aggregation in WSNs is a growing field and one of the proposed solutions to achieving this is called homomorphic encryption. Homomorphic encryption is an encryption scheme that allows data processing on encrypted data as opposed to plaintext [5].Homomorphic encryption allows the data to be aggregated without having to decrypt each incoming packet. In homomorphic encryption schemes, for a given encryption key, each plaintext can be encrypted into a number of different cyphertexts [6]. This means the resulting cyphertext is larger than the original plaintext. As already mentioned, the energy consumption of the nodes i...

show abstract

Fusion: coalesced confidential storage and communication framework for the IoT

Bağcı

Raza

Roedig

et al. 2015

Security Comm Networks

View full text Add to dashboard Cite

Comprehensive security mechanisms are required for a successful implementation of the Internet of Things (IoT). Existing solutions focus mainly on securing the communication links between Internet hosts and IoT devices. However, as most IoT devices nowadays provide vast amounts of flash storage space, it is as well required to consider storage security within a comprehensive security framework. Instead of developing independent security solutions for storage and communication, we propose Fusion, a framework that provides coalesced confidential storage and communication. Fusion uses existing secure communication protocols for the IoT such as Internet protocol security (IPsec) and datagram transport layer security (DTLS) and re-uses the defined communication security mechanisms within the storage component. Thus, trusted mechanisms developed for communication security are extended into the storage space. Notably, this mechanism allows us to transmit requested data directly from the file system without decrypting read data blocks and then re-encrypting these for transmission. Thus, Fusion provides benefits in terms of processing speed and energy efficiency, which are important aspects for resource-constrained IoT devices. This paper describes the Fusion architecture and its instantiation for IPsecbased and DTLS-based systems. We describe Fusion's implementation and evaluate its storage overheads, communication performance, and energy consumption. network (6LoWPAN) [2,3]. The main contribution of 6LoWPAN are compression mechanisms that allow us to

show abstract

Comparative performance and energy consumption analysis of different AES implementations on a wireless sensor network node

Cited by 38 publications

References 32 publications

Measuring the performance and energy consumption of AES in wireless sensor networks

Measuring the performance and energy consumption of AES in wireless sensor networks

Data aggregation using homomorphic encryption in wireless sensor networks

Fusion: coalesced confidential storage and communication framework for the IoT

Contact Info

Product

Resources

About