Abstract

Small IoT devices can only support light protocols since they lack significant processing or storage power. Lightweight encryption standards or techniques will be utilized for encryption and decryption to prevent hackers from accessing the data in order to increase the security of IoT devices' network connections and commands. The encryption has to be robust enough to safeguard and lightweight enough to enable light processing hardware. There aren't many standards for lightweight cryptography that are used to safeguard devices in an existing network. If the network is not secured properly, an intruder can get in and take control of the devices without making a visible appearance. A hybrid lightweight cryptographic methodology have been proposed to address this problem. LWC algorithms are designed to provide strong security while minimizing the computational and memory resources required for encryption and decryption. This is particularly important for IoT devices, which often have limited processing power, storage capacity, and battery life. LWC algorithms offer a range of benefits for IoT devices, including improved security, reduced power consumption, and increased battery life. They are also designed to be easy to implement and integrate with existing IoT platforms and protocols. Proposed system's analytical work implementation will combine Salsa20 and AES algorithms to provide greater security and making it well-suited for real-time cryptography.

Keywords:
Computer science Encryption Cryptography Embedded system Cryptographic protocol Computer security Computer network Cryptographic primitive Distributed computing

Metrics

5
Cited By
1.28
FWCI (Field Weighted Citation Impact)
20
Refs
0.79
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Cryptographic Implementations and Security
Physical Sciences →  Computer Science →  Artificial Intelligence
Chaos-based Image/Signal Encryption
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Advanced Malware Detection Techniques
Physical Sciences →  Computer Science →  Signal Processing

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