Unmanned Aerial Vehicles Routing Formation Using Fisheye State Routing for Flying Ad-hoc Networks

Hassan, Muhammad Abul; Ullah, Syed Irfan; Khan, Inam Ullah; Shah, Syed Bilal Hussain; Salam, Abdus; Khan, Arbab Wajid Ullah

doi:10.1145/3440749.3442600

Cited by 14 publications

(5 citation statements)

References 10 publications

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“…ML approaches like supervised [41], unsupervised [42], as well as reinforcement learning, can be used to detect unique threats in IoT devices and establish a good protection strategy. Multiple machine learning methods for IoT device protection.…”

Section: Machine Learning Techniques In Iot Detectionmentioning

confidence: 99%

Design a framework for IoT- Identification, Authentication and Anomaly detection using Deep Learning: A Review

Shoukat

Hassan

Rizwan

et al. 2023

EAI Endorsed Trans Smart Cities

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The Internet of Things (IoT) connects billions of smart gadgets so that they may communicate with one another without the need for human intervention. With an expected 50 billion devices by the end of 2020, it is one of the fastest-growing industries in computer history. On the one hand, IoT technologies are critical in increasing a variety of real-world smart applications that can help people live better lives. The cross-cutting nature of IoT systems, on the other hand, has presented new security concerns due to the diverse components involved in their deployment. For IoT devices and their inherent weaknesses, security techniques such as encryption, authentication, permissions, network monitoring, \& application security are ineffective. To properly protect the IoT ecosystem, existing security solutions need to be strengthened. Machine learning and deep learning (ML/DL) have come a long way in recent years, and machine intelligence has gone from being a laboratory curiosity to being used in a variety of significant applications. The ability to intelligently monitor IoT devices is an important defense against new or negligible assaults. ML/DL are effective data exploration techniques for learning about 'normal' and 'bad' behavior in IoT devices and systems. Following a comprehensive literature analysis on Machine Learning methods as well as the importance of IoT security within the framework of different sorts of potential attacks, multiple DL algorithms have been evaluated in terms of detecting attacks as well as anomaly detection in this work. We propose a taxonomy of authorization and authentication systems in the Internet of Things based on the review, with a focus on DL-based schemes. The authentication security threats and problems for IoT are thoroughly examined using the taxonomy supplied. This article provides an overview of projects that involve the use of deep learning to efficiently and automatically provide IoT applications.

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Section: Machine Learning Techniques In Iot Detectionmentioning

confidence: 99%

Design a framework for IoT- Identification, Authentication and Anomaly detection using Deep Learning: A Review

Shoukat

Hassan

Rizwan

et al. 2023

EAI Endorsed Trans Smart Cities

Self Cite

View full text Add to dashboard Cite

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“…From classical data security requirements to modern applications like Energy efficient routing protocols [30], unmanned aerial vehicles [31], block chain technology [32], efficient operations in data storage [33], mobile communication networks [34], the cryptographic algorithm plays a vital role in data security. By examining the effects of the Chaos base approach on block ciphers, Jakimoski et al [9] produced a Chaos-based S-box.…”

Section: Literature Reviewmentioning

confidence: 99%

An Efficient Substitution Box design with a chaotic logistic map and Linear Congruential Generator for secure communication in Smart cities

Hashmi

Tariq²

2023

EAI Endorsed Trans Smart Cities

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The study provides a unique method for creating an efficient substitution box (S-box) for advanced encryption standards using a Chaotic Logistic Map (CLM) and a Linear Congruential Generator (LCG) (AES) for secure communications in a smart city. The Pseudo-Random Number Generator (PRNG), which is further examined, is constructed using an extensive search of reasonable possibilities for the initial seed and set parameters. Using statistical testing, the performance analysis of the new S-box is assessed. Additionally, the resilience of differential, as well as linear cryptanalysis, is shown. It is derived using other features, including nonlinearity, the Bit Independence Criterion (BIC), and the Strict Avalanche Criterion (SAC). The suggested S-box has good potential and is usable for symmetric key cryptography, according to the features of the new S-cryptographic box.

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“…While the mentioned research, manage data sharing which boosts cloud computing efficiency through space-intensive applications, such as distributed data mining. In addition, natured inspired evolutionary computational technique (E-AntHocNet) and Fisheye State routing (FSR) can be considered for further improvements [35][36][37].…”

Section: Background Studymentioning

confidence: 99%

Secure and Efficient Data Storage Operations by Using Intelligent Classification Technique and RSA Algorithm in IoT-Based Cloud Computing

Sajid

Hassan

Khan

et al. 2022

Scientific Programming

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In mobile cloud services, smartphones may depend on IoT-based cloud infrastructure and information storage tools to conduct technical errands, such as quest, information processing, and combined networks. In addition to traditional finding institutions, the smart IoT-cloud often upgrades the normal impromptu structure by treating mobile devices as corporate hubs, e.g., by identifying institutions. This has many benefits from the start, with several significant problems to be overcome in order to enhance the unwavering consistency of the cloud environment while Internet of things connects and improves decision support system of the entire network. In fact, similar issues apply to monitor loading, resistance, and other security risks in the cloud state. Right now, we are looking at changed arrangement procedures in MATLAB utilizing cardiovascular failure information and afterward protecting that information with the assistance of RSA calculation in mobile cloud. The calculations tried are SVM, RF, DT, NB, and KNN. In the outcome, the order strategies that have the best exactness result to test respiratory failure information will be recommended for use for enormous scope information. Instead, the collected data will be transferred to the mobile cloud for preservation using the RSA encryption algorithm.

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Unmanned Aerial Vehicles Routing Formation Using Fisheye State Routing for Flying Ad-hoc Networks

Cited by 14 publications

References 10 publications

Design a framework for IoT- Identification, Authentication and Anomaly detection using Deep Learning: A Review

Design a framework for IoT- Identification, Authentication and Anomaly detection using Deep Learning: A Review

An Efficient Substitution Box design with a chaotic logistic map and Linear Congruential Generator for secure communication in Smart cities

Secure and Efficient Data Storage Operations by Using Intelligent Classification Technique and RSA Algorithm in IoT-Based Cloud Computing

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