An Efficient Security Solution for Industrial Internet of Things Applications

Almagrabi, Alaa Omran

doi:10.32604/cmc.2022.026513

Cited by 2 publications

(1 citation statement)

References 34 publications

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“…Hence, all these advancements in the field of computer science is paving way for progressions in manufacturing field, healthcare, smart-homes, transportation, etc. [16][17][18][19][20][21].…”

Section: Introductionmentioning

confidence: 99%

Mutated Leader Sine-Cosine Algorithm for Secure Smart IoT-Blockchain of Industry 4.0

Abidi¹,

Alkhalefah²,

Mohammed³

2022

Computers, Materials &Amp; Continua

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In modern scenarios, Industry 4.0 entails invention with various advanced technology, and blockchain is one among them. Blockchains are incorporated to enhance privacy, data transparency as well as security for both large and small scale enterprises. Industry 4.0 is considered as a new synthesis fabrication technique that permits the manufacturers to attain their target effectively. However, because numerous devices and machines are involved, data security and privacy are always concerns. To achieve intelligence in Industry 4.0, blockchain technologies can overcome potential cybersecurity constraints. Nowadays, the blockchain and internet of things (IoT) are gaining more attention because of their favorable outcome in several applications. Though they generate massive data that need to be effectively optimized and in this research work, deep learning-based techniques are employed for this. This paper proposes a novel mutated leader sine cosine algorithm-based deep convolutional neural network (MLSC-DCNN) in order to attain a secure and optimized IoT blockchain for Industry 4.0. Here, an MLSC is hybridized using a mutated leader and sine cosine algorithm to enhance the weight function and minimize the loss factor of DCNN. Finally, the experimentation is carried out for various simulation measures. The comparative analysis is made for Best Tip Selection Method (BTSM), Smart Block-Software Defined Networking (SDN), and the proposed approach. The evaluation results show that the proposed approach attains better performances than BTSM and SDN.

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Section: Introductionmentioning

confidence: 99%

Mutated Leader Sine-Cosine Algorithm for Secure Smart IoT-Blockchain of Industry 4.0

Abidi¹,

Alkhalefah²,

Mohammed³

2022

Computers, Materials &Amp; Continua

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A Review of State-of-the-Art Malware Attack Trends and Defense Mechanisms

Ferdous,

Islam,

Mahboubi

et al. 2023

IEEE Access

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The increasing sophistication of malware threats has led to growing concerns in the antimalware community, as malware poses a significant danger to online users despite the availability of numerous defense solutions. This study aims to comprehensively review malware evolution and current attack trends to identify effective defense mechanisms. It reviews the most recent journal articles, conference proceedings, reports, and online resources published during the last five years. We extensively review the malware landscape from 1970 to the present and analyze malware types, operational mechanisms, attack vectors, and vulnerabilities. Furthermore, we explore different defensive strategies developed in response to these evolving threats. Our findings highlight the increasing sophistication of malware attack trends, including a surge in cryptojacking, attacks on mobile devices, Internet of Things devices, ransomware, advanced persistent threats, supply chain attacks, fileless malware, cloud-based attacks, exploitation of remote employees, and attack trends on edge networks. Defense strategies have also evolved in parallel, emphasizing multilayered security measures to counter these dynamic threats. This study highlights the critical need for robust, multilayered security measures to combat dynamic malware. Despite these advancements, some open challenges and significant research gaps remain, which require further innovation. This review serves as a valuable guide for cybersecurity professionals by identifying the key trends, challenges, limitations, and future cybersecurity research opportunities.INDEX TERMS Malware evolution, malware attack trends, defense mechanisms, malware detection, machine learning, deep learning. D. INCREASED NUMBER OF TARGETED RANSOMWARE ATTACKSRecent malware trends have highlighted increased targeted ransomware attacks, in which hackers access a network or system, encrypt data, and demand a ransom to restore access. This increase in ransomware attacks is driven by several factors, including potential financial gains, easy operation, the rise of ransomware-as-a-service platforms, and the popularity of cryptocurrencies like Bitcoin [97]. Ransomware attacks are wide-ranging, targeting everything from desktops and mobile devices and increasingly involving IoT devices.

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An Efficient Security Solution for Industrial Internet of Things Applications

Cited by 2 publications

References 34 publications

Mutated Leader Sine-Cosine Algorithm for Secure Smart IoT-Blockchain of Industry 4.0

Mutated Leader Sine-Cosine Algorithm for Secure Smart IoT-Blockchain of Industry 4.0

A Review of State-of-the-Art Malware Attack Trends and Defense Mechanisms

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