Two-stage data encryption using chaotic neural networks

Srivastava, Gautam; Kumar, Chiranjeev; Kavitha, Veeraruna; Parthiban, N.; Venkataraman, Revathi

doi:10.3233/jifs-179543

Cited by 25 publications

(10 citation statements)

References 40 publications

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“…The authors of [26] proposed a machine learning algorithm to identify malicious uniform resource locators by combining URL lexical selections, payload size, and python supply parameters. A Chaotic Hopfield Neural Network combined with an adaptive encoding approach may provide a more secure model for keeping private information; the proposed approach enhances the safety of a shared key among any number of nodes [27][28][29][30][31][32].…”

Section: Related Workmentioning

confidence: 99%

Dual Authentication for Payment Request Verification Over Cloud using Bilinear Dual Authentication Payments Transaction Protocol

Saranya¹,

Naresh²

2022

IJACSA

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There has been a recent explosion in the number of mobile network payment gateways that enable users to access services through a variety of devices. Mobile payment gateway security is complicated by a number of difficult-to-solve issues. As digital technology has progressed over the last decade, mobile payment mechanisms have gained a lot of interest. In the internet industry, these standards might have a significant impact on service quality. However, the most important aspect to consider when using these systems is their accountability, which assures confidence between the parties engaged in the financial transactions. Mobile payments may be easy, quick and secure. On the other hand, they may be rather pricey and are still susceptible to problems caused by technology. Specifically, mobile payments won't be able to go through at all if there are any problems with the host phone. For this reason, in this article a mobile payment mechanism that uses secure bilinear dual authentication. Using Bullet hash Maximum distance separable (MDS) and the mutate Hellman algorithm, our payment protocol incorporates all of the essential security characteristics to establish confidence between the parties. To put it another way, accountability is assured by mutual authentication and nonrepudiation. Conflicts that may emerge in the course of a payment transaction may be resolved using our strategy. Scyther is used to test our suggested protocol's empirical performance.

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Section: Related Workmentioning

confidence: 99%

Dual Authentication for Payment Request Verification Over Cloud using Bilinear Dual Authentication Payments Transaction Protocol

Saranya¹,

Naresh²

2022

IJACSA

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“…Srivastava et al [15] in 2020 presented a novel algorithm to control data security using a hybrid model that used an adaptive encoding technique alongside Chaotic Hopfield Neural Network. The proposed computation upgraded the security of a key shared between any nodes.…”

Section: Previous Researchesmentioning

confidence: 99%

The Efficacy of Choosing Strategy with General Regression Neural Network on Evolutionary Markov Games

Kordnoori

Mostafaei

Ostadrahimi

et al. 2021

JTS

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Nowadays, Evolutionary Game Theory which studies the learning model of players, has attracted more attention than before. These Games can simulate the real situation and dynamic during processing time. This paper creates the Evolutionary Markov Games, which maps players' strategy-choosing to a Markov Decision Processes (MDPs) with payoffs. Boltzmann distribution is used for transition probability and the General Regression Neural Network (GRNN) simulating the strategy-choosing in Evolutionary Markov Games. Prisoner's dilemma is a problem that uses the method and output results showing the overlapping the human strategy-choosing line and GRNN strategy-choosing line after 48 iterations, and they choose the same strategies. Also, the error rate of the GRNN training by Tit for Tat (TFT) strategy is lower than similar work and shows a better result.

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“…Following the impressive results of deep learning on the task of image classification [34] and other research fields [35,36], many efforts have been made to train deep networks for the task of action recognition. Fernando et al [3] proposed a temporal pooling function, which uses the evolution of video temporal structure to represent the videos.…”

Section: Related Workmentioning

confidence: 99%

Fine-Grained Action Recognition by Motion Saliency and Mid-Level Patches

et al. 2020

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Effective extraction of human body parts and operated objects participating in action is the key issue of fine-grained action recognition. However, most of the existing methods require intensive manual annotation to train the detectors of these interaction components. In this paper, we represent videos by mid-level patches to avoid the manual annotation, where each patch corresponds to an action-related interaction component. In order to capture mid-level patches more exactly and rapidly, candidate motion regions are extracted by motion saliency. Firstly, the motion regions containing interaction components are segmented by a threshold adaptively calculated according to the saliency histogram of the motion saliency map. Secondly, we introduce a mid-level patch mining algorithm for interaction component detection, with object proposal generation and mid-level patch detection. The object proposal generation algorithm is used to obtain multi-granularity object proposals inspired by the idea of the Huffman algorithm. Based on these object proposals, the mid-level patch detectors are trained by K-means clustering and SVM. Finally, we build a fine-grained action recognition model using a graph structure to describe relationships between the mid-level patches. To recognize actions, the proposed model calculates the appearance and motion features of mid-level patches and the binary motion cooperation relationships between adjacent patches in the graph. Extensive experiments on the MPII cooking database demonstrate that the proposed method gains better results on fine-grained action recognition.

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Two-stage data encryption using chaotic neural networks

Cited by 25 publications

References 40 publications

Dual Authentication for Payment Request Verification Over Cloud using Bilinear Dual Authentication Payments Transaction Protocol

Dual Authentication for Payment Request Verification Over Cloud using Bilinear Dual Authentication Payments Transaction Protocol

The Efficacy of Choosing Strategy with General Regression Neural Network on Evolutionary Markov Games

Fine-Grained Action Recognition by Motion Saliency and Mid-Level Patches

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