Design and Analysis of Multi-Bit Linear Feedback Shift Register based PRNG with FPGA Implementation using different Primitive Polynomials

Sony, Smitha; P, Anirudh; R.S., Geethu

doi:10.1109/conit55038.2022.9848174

Cited by 3 publications

(2 citation statements)

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“…Applications that utilize cryptography, such as data encryption keys and secure communication channels, frequently rely on PRNGs based on LFSR. This preference is justified by the superior performance of LFSR-based PRNGs in terms of hardware, area, and speed compared to alternative counters [14].…”

Section: A Session Key Generationmentioning

confidence: 99%

“…The LFSR, a type of feedback shift register (FSR), executes the feedback function through the XOR operation on a subset of the register bits, forming a "tap sequence" [2,13,14]. Figure 1 illustrates a standard LFSR structure, and Table 1 provides an interface link between the tap sequence bits and the maximum length of the generated sequence.…”

Section: A Session Key Generationmentioning

confidence: 99%

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Evaluation of Image Cryptography by Using Secret Session Key and SF Algorithm

Kareem Jumaa,

Muhammed Allawy

2023

ijci

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In the unreliable domain of data communication, safeguarding information from unauthorized access is imperative. Given the widespread application of images across various fields, ensuring the confidentiality of image data holds paramount importance. This study centers on the session keys concept, addressing the challenge of key exchange between communicating parties through the development of a random-number generator based on the Linear Feedback Shift Register. Both encryption and decryption hinge on the Secure Force algorithm, supported by a generator. The proposed system outlined in this paper focuses on three key aspects. First, it addresses the generation of secure and randomly generated symmetric encryption keys. Second, it involves the ciphering of the secret image using the SF algorithm. Last, it deals with the extraction of the image by deciphering its encrypted version. The system’s performance is evaluated using image quality metrics, including histograms, peak signal-to-noise ratio, mean square error, normalized correlation, and normalized absolute error (NAE). These metrics provide insights into both encrypted and decrypted images, analyzing the extent to which the system preserves image quality. This assessment underscores the system’s capability to safeguard and maintain the confidentiality of images during data transmission.

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Section: A Session Key Generationmentioning

confidence: 99%

Section: A Session Key Generationmentioning

confidence: 99%