Hardware Intrusion Detection Using FPGA

Quantum computing creates widespread threats to the traditional cryptographic strategies used in the rapid development system that detects the infiltration system (IDS). Quantity -coming opponents can undoubtedly benefit from the weaknesses of traditional encryption, and threaten the journal protection and oral exchange integrity. This challenge addresses these demanding conditions by integrating the BRLWE-based submission quality cryptography in the ID, causing a clear opposition to quantum attacks. Brlwe-Mainly-A Quantum-resistant algorithm provides a stable observation for protection of touch data. However, the calculation of cryptographic schemes after volume is delayed in complexity, which may interfere with performance -time requirements for ID. To win this question, the task proposes the distribution of advanced hardware architecture, mainly Double Linear Feedback Change Register (Dual-LFSR) and Quad Line Line Feedback Shift Register (Quad-LFSR). This architecture allows parallel processing of cryptographic operation, and reduces mass calculation overheads and machines increases responsibility. By optimizing encryption and decryption method through gender equality, this answer ensures that IDS can function properly without compromising safety. This technique balances alternative links between calculation performance and cryptographic strength, and provides a scalable and realistic solution for the next generation ID in a quantum -competent global. The findings of the challenge detect viability to integrate quantum cryptography presented with customized hardware architecture to preserve high performance and stable operations, and protect important infrastructure for both classic and quantum threats.

Authors

Publication Details

Published
2025-03-04
DOI
https://doi.org/10.1109/icvadv63329.2025.10961853
Primary Topic
Advanced Malware Detection Techniques
Type
article
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article

Hardware Intrusion Detection Using FPGA

S Saravanan, R. Poornima, P. Sandeep, V Samyuktha
Advanced Malware Detection Techniques
article

Hardware Intrusion Detection Using FPGA

S Saravanan, R. Poornima, P. Sandeep, V Samyuktha
article en

Abstract

Quantum computing creates widespread threats to the traditional cryptographic strategies used in the rapid development system that detects the infiltration system (IDS). Quantity -coming opponents can undoubtedly benefit from the weaknesses of traditional encryption, and threaten the journal protection and oral exchange integrity. This challenge addresses these demanding conditions by integrating the BRLWE-based submission quality cryptography in the ID, causing a clear opposition to quantum attacks. Brlwe-Mainly-A Quantum-resistant algorithm provides a stable observation for protection of touch data. However, the calculation of cryptographic schemes after volume is delayed in complexity, which may interfere with performance -time requirements for ID. To win this question, the task proposes the distribution of advanced hardware architecture, mainly Double Linear Feedback Change Register (Dual-LFSR) and Quad Line Line Feedback Shift Register (Quad-LFSR). This architecture allows parallel processing of cryptographic operation, and reduces mass calculation overheads and machines increases responsibility. By optimizing encryption and decryption method through gender equality, this answer ensures that IDS can function properly without compromising safety. This technique balances alternative links between calculation performance and cryptographic strength, and provides a scalable and realistic solution for the next generation ID in a quantum -competent global. The findings of the challenge detect viability to integrate quantum cryptography presented with customized hardware architecture to preserve high performance and stable operations, and protect important infrastructure for both classic and quantum threats.

Openalex Percentile: Top 91%
Advanced Malware Detection Techniques
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Hardware Intrusion Detection Using FPGA — S Saravanan, R. Poornima, et al. · (2025) | TGRS Research Map | TGRS