Design and Implementation of High-Performance Computing Unit for Internet of Things (IoT) Applications

Nan, Andrew Ashraf; Shawky, Mustafa Mohamed; Ahmed, Ahmed Mohamed; Ellaithy, Dina M.

doi:10.1109/icm52667.2021.9664933

Cited by 2 publications

(1 citation statement)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This surge in data production and accessibility has made safeguarding sensitive information from unauthorized access more challenging. Consequently, developing analytics and innovative models to mitigate threats posed by attackers and scammers to private data stored online has become imperative [20].…”

mentioning

confidence: 99%

Detection and Prevention of Cyber Defense Attacks using Machine Learning Algorithms

Shang

2024

SCPE

View full text Add to dashboard Cite

Recent advancements in computing power, memory capacities, and connectivity have led to a corresponding surge in the utilization of big data, online platforms' prevalence, and machine learning's sophistication. Concerns regarding safety and the need for state-of-the-art security tools and methods to counter evolving cybercrime are amplified by the swift digitization of the world. This study investigates defensive and offensive applications of machine learning in cybersecurity. Additionally, it explores potential strategies to mitigate cyberattacks on machine learning models. The focus is on how machine learning facilitates cyberattacks, including developing intelligent botnets, advanced phishing using spear techniques, and deploying stealthy malware. Furthermore, the paper highlights the significance of artificial intelligence in digital safety, emphasizing its role in malware analysis, network vulnerability assessment, and threat prediction.

show abstract

mentioning

confidence: 99%