Design a Crime Detection System based Fog Computing and IoT

Waheed, Safa Riyadh; Sakran, Ammar AbdRoba; Mohd Rahim, Mohd Shafry; Mohd Suaib, Norhaida; H Najjar, Fallah; A Kadhim, Karrar; Salim, Ali Aqeel; Adnan, Myasar Mundher

doi:10.11113/mjfas.v19n3.2906

Cited by 3 publications

(2 citation statements)

References 49 publications

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“…The Entropy is an analytical measure of the randomness level in a cryptographic system. Shannon [47] proposed the following mathematical equation to calculate the entropy:…”

Section: Analysis Of Information Entropymentioning

confidence: 99%

WAM 3D Discrete Chaotic Map for Secure Communication Applications

Abdul-Kareem,

Mahmoud Al-Jawher

2023

Int J Innov Comp

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Chaotic systems have become widely adopted as an effective way for secure data communications, because of its simple mathematical complexity and good security. The relationship between encryption algorithms and chaos systems has gained a lot of attention in the past few years, since it avoids the data spreading as well as lower the transmission delay and costs. In this paper a novel 3D discrete chaotic map is proposed for data encryption and secure communication and named as WAM. For secure communication, the Pecora and Carroll (P-C) method was utilized to achieve synchronization between the master system and the slave system. The simulation results of WAM 3D discrete chaotic map showed that the system has a chaotic behavior and a characteristic randomness and can pass 0-1, Lyapunov exponent (LE) and NIST tests which are usually used to check chaotic behavior. The statistical outcomes of the LE test were 0.0193, the frequency test (FT) was 0.4237, and the run test (RT) yielded a value of 0.0607. As a result, it enrich the theoretical basis of the equations and implementation of chaos, and it is superior for encryption algorithms and communication security applications.

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“…The Entropy is an analytical measure of the randomness level in a cryptographic system. Shannon [47] proposed the following mathematical equation to calculate the entropy:…”

Section: Analysis Of Information Entropymentioning

confidence: 99%

WAM 3D Discrete Chaotic Map for Secure Communication Applications

Abdul-Kareem,

Mahmoud Al-Jawher

2023

Int J Innov Comp

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“…Depending on the sand's strength, images in sand dust are yellowish or reddish. Therefore, color balancing and correction are necessary for enhancing the sand-dusty image [4,[18][19][20].…”

Section: Introductionmentioning

confidence: 99%

Fast Dust Sand Image Enhancement Based on Color Correction and New Fuzzy Intensification Operators

Hakem Alsaeedi,

Alazzawi,

Mohammed Hadi

2023

Int J Innov Comp

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Images captured in dusty environments suffering from poor visibility and quality. Enhancement of these images such as sand dust images plays a critical role in various atmospheric optics applications. In this work, proposed a new model based on Color Correction and New Fuzzy Intensification Operators to enhance san dust images. The proposed model consists of three phases: correction of color shift, removal of haze, and enhancement of contrast and brightness. The color shift is corrected using a fuzzy intensification operator to adjust the values of U and V in the YUV color space. The Adaptive Dark Channel Prior (A-DCP) is used for haze removal. The stretching contrast and improving image brightness are based on Contrast Limited Adaptive Histogram Equalization (CLAHE). The proposed model tests and evaluates through many real sand dust images. The experimental results show that the proposed solution is outperformed the current studies in terms of effectively removing the red and yellow cast and provides high quality and quantity dust images.

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A Review Load balancing algorithms in Fog Computing

Mahdi,

Hassan,

Abdulsaheb

2024

BIO Web Conf.

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With the rapid advance of the Internet of Things (IoT), technology has entered a new era. It is changing the way smart devices relate to such fields as healthcare, smart cities, and transport. However, such rapid expansion also challenges data processing, latency, and QoS. This paper aims to consider fog computing as a key solution for addressing these problems, with a special emphasis on the function of load balancing to improve the quality of service in IoT environments. In addition, we study the relationship between IoT devices and fog computing, highlighting why the latter acts as an intermediate layer that can not only reduce delays but also achieve efficient data processing by moving the computational resources closer to where they are needed. Its essence is to analyze various load balancing algorithms and their impact in fog computing environments on the performance of IoT applications. Static and dynamic load balancing strategies and algorithms have been tested in terms of their impact on throughput, energy efficiency, and overall system reliability. Ultimately, dynamic load balancing methods of this sort are better than static ones for managing load in fog computing scenarios since they are sensitive to changing workloads and changes in the system. The paper also discusses the state of the art of load balancing solutions, such as secure and sustainable techniques for Edge Data Centers (EDCs), It manages the allocation of resources for scheduling. We aim to provide a general overview of important recent developments in the literature while also pointing out limitation where improvements might be made. To this end, we set out to better understand and describe load balancing in fog computing and its importance for improving QoS. We thus hope that a better understanding of load balancing technologies can lead us towards more resilient and secure systems.

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Design a Crime Detection System based Fog Computing and IoT

Cited by 3 publications

References 49 publications

WAM 3D Discrete Chaotic Map for Secure Communication Applications

WAM 3D Discrete Chaotic Map for Secure Communication Applications

Fast Dust Sand Image Enhancement Based on Color Correction and New Fuzzy Intensification Operators

A Review Load balancing algorithms in Fog Computing

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