The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
A survey on lightweight ciphers for IoT devices
Abstract
Embedded systems are found to be used in a wide range of domains. But the inherent limitations of size, memory and power, limits its functionality in secure transmission of sensitive information. The existing cryptographic systems need some area for implementation, limiting its use in embedded systems. Hence, lightweight ciphers which can be easily implemented in resource constrained devices were introduced. In this paper we discuss such existing lightweight block ciphers, PRESENT, KATAN, Humming bird, SIMON, and RECTANGLE and stream ciphers, TRIVIUM, GRAIN, CHACHA, WG-8 and ESPRESSO.
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Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“Block ciphers consume a large footprint of Gate Equivalents (GE) when compared to stream ciphers.”
From Analysis of Area-Efficiency vs. Unrolling for eSTREAM Hardware Portfolio Stream Ciphers (2020) · cites this paper as [1]
In the citing paper
“For instance, the traditional Advanced Encryption Standard consumes about 2400-3500 GE whereas the lightweight stream ciphers take approximately 2000 GE.”
From Analysis of Area-Efficiency vs. Unrolling for eSTREAM Hardware Portfolio Stream Ciphers (2020) · cites this paper as [1]
Citations
Cites
KATAN and KTANTAN — A Family of Small and Efficient Hardware-Oriented Block Ciphers
De Cannière, C., Dunkelman, O., & Knežević, M. (2009) · Lecture Notes in Computer Science · doi:10.1007/978-3-642-04138-9_20 · Cited by 678
Grain: A stream cipher for constrained environments
Hell, M., Johansson, T., & Meier, W. (2007) · International Journal of Wireless and Mobile Computing · doi:10.1504/ijwmc.2007.013798 · Cited by 568
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- canniere christophe, 2005, TRIVIUM -a stream cipher construction inspired by block cipher design principles, ESTREAM the ECRYPT Stream Cipher Project Report 2005/066
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Cited by
Analysis of Area-Efficiency vs. Unrolling for eSTREAM Hardware Portfolio Stream Ciphers
Alharbi, F., Hameed, M. K., Chowdhury, A., Khalid, A., Chattopadhyay, A., & Javed, I. T. (2020) · Electronics · doi:10.3390/electronics9111935 · Cited by 5
“In [1], authors discuss the efficiency of stream ciphers Trivium, Grain and Mickey.”
BackgroundMethod
Metadata
- Authors
- Philip, M. A., & Vaithiyanathan
- Affiliations
- Amrita Vishwa Vidyapeetham (IN)
- ORCID
- Philip, Merly Annie
- Venue
- 2017 International Conference on Technological Advancements in Power and Energy ( TAP Energy)
- Publisher
- IEEE
- Published
- 2017-12
- Pages
- 1-4
- OpenAlex
- W2810564382
- Cited by
- 65
- References
- 2
- Citations by year
- 2026: 1 · 2025: 2 · 2024: 10 · 2023: 12 · 2022: 12 · 2021: 11 · 2020: 9 · 2019: 6 · 2018: 2
- FWCI
- 2.12
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- International Conference on Technological Advancements in Power and Energy (TAP Energy) (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Cryptographic Implementations and Security
- Physical Sciences › Mathematics › Discrete Mathematics and Combinatorics › Coding theory and cryptography
- Physical Sciences › Computer Science › Information Systems › Cryptography and Residue Arithmetic
- Keywords
- lightweight cryptography, Internet of Things security, resource-constrained devices, block cipher, stream ciphers, present moment, hummingbirds, Simon, rectangles, trivium, grain, ChaCha, espresso, embedded systems security
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- Philip, M. A., & Vaithiyanathan. (2017). A survey on lightweight ciphers for IoT devices. 2017 International Conference on Technological Advancements in Power and Energy ( TAP Energy). https://doi.org/10.1109/tapenergy.2017.8397271
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.