Fast Algebraic Immunity of $2^m+2$  &amp; $2^m+3$  Variables Majority Function

Chen, Yindong; Zhang, Liu; Guo, Fei; Cai, Wei

doi:10.1109/access.2019.2923456

Cited by 9 publications

(4 citation statements)

References 23 publications

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“…The study provides insights into the use of machine learning for security surveillance. In [3], the author M. Hasanuzzaman et al developed a Real-Time Video-Based Monitoring System for Security Guards. This paper presents a real-time video-based monitoring system for security guards using machine learning techniques like SVM and Haar Cascades.…”

Section: Literature Surveymentioning

confidence: 99%

A Real-Time IoT-based Model to Detect and Alert Security Guards’ Drowsiness

Poornima,

Kumar,

Katukam

et al. 2023

E3S Web Conf.

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In the security industry, it is critical to ensure that security guards remain alert and attentive throughout their shifts. Drowsiness and inattention can lead to security breaches and endanger the safety of the premises and the people within them. To address this issue, a hybrid system is being developed to detect security guards' drowsiness and alert them using sound buzzers and water sprinklers to prevent security breaches. The system uses advanced machine learning and deep learning techniques like OpenCV and DCNN, along with a UHD camera, to detect signs of drowsiness using algorithms like Eye Aspect Ratio/Mouth Aspect Ratio (EAR)/(MAR). By analysing behavioural indicators, the system determines whether a security guard displays signs of drowsiness and alerts them using sound buzzers to remain attentive. Overall, the hybrid system provides an effective solution to enhance security guard monitoring and prevent potential security threats caused by drowsiness and inattention.

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Section: Literature Surveymentioning

confidence: 99%

A Real-Time IoT-based Model to Detect and Alert Security Guards’ Drowsiness

Poornima,

Kumar,

Katukam

et al. 2023

E3S Web Conf.

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“…Currently exact FAI is still only available for majority function on some special n [18], [19], and for our function, we're only able to analyze for small n. With the computer program in [42] we can get that, for odd n < 17, FAI(f ) = FAI(f ) = n − 1. As proved in [39], this is the highest possible value for RSBFs with optimal AI.…”

Section: E Fast Attack Immunitymentioning

confidence: 99%

Constructing Higher Nonlinear Odd-Variable RSBFs With Optimal AI and Almost Optimal FAI

Chen

Liao

et al. 2019

IEEE Access

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Rotation symmetric Boolean functions (RSBFs) are nowadays studied a lot because of its easy operations and good performance in cryptosystem. This paper constructs a new class of odd-variable RSBFs with optimal algebraic immunity (AI). The nonlinearity of the new function, 2 n−1 − n−1 k +2 k−4 (k−3)(k−2), is the highest among all existing RSBFs with optimal AI and known nonlinearity, and its algebraic degree is also almost highest. Besides, the class of functions have almost optimal fast algebraic immunity (FAI) at least for n < 17, which is actually the highest possible value for the designated number of variables.

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“…Optimal AI and high FAI are attributes that Boolean functions should have in order to resist (fast) algebraic attacks. Many efforts have been made to investigate symmetric Boolean functions [8]- [15], rotation symmetric Boolean functions [16]- [19], and other Boolean functions [20]- [24], which possess optimal AI and high FAI. But, as everyone knows, it is very difficult to calculate the FAI of given Boolean function with high algebraic degree when the variable is larger than 18 [25].…”

Section: Introductionmentioning

confidence: 99%

A Lower Bound of Fast Algebraic Immunity of a Class of 1-Resilient Boolean Functions

Chen

Zhang

et al. 2019

IEEE Access

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Boolean functions should possess high fast algebraic immunity when used in stream ciphers in order to stand up to fast algebraic attacks. However, in previous research, the fast algebraic immunity of Boolean functions was usually calculated by the computer. In 2017, Tang, Carlet, and Tang first mathematically proved that every function belonging to a class of 1-resilient Boolean functions has the fast algebraic immunity no less than n − 6. Inspired by the Tang's method, we also demonstrate that the fast algebraic immunity of another class of the 1-resilient Boolean functions is no less than n − 6. Meanwhile, we also prove some combinator facts originated from the Tu-Deng Conjecture. INDEX TERMS Fast algebraic immunity, algebraic immunity, resiliency, Boolean functions.

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Fast Algebraic Immunity of $2^m+2$ & $2^m+3$ Variables Majority Function

Cited by 9 publications

References 23 publications

A Real-Time IoT-based Model to Detect and Alert Security Guards’ Drowsiness

A Real-Time IoT-based Model to Detect and Alert Security Guards’ Drowsiness

Constructing Higher Nonlinear Odd-Variable RSBFs With Optimal AI and Almost Optimal FAI

A Lower Bound of Fast Algebraic Immunity of a Class of 1-Resilient Boolean Functions

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