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<div><p>The dynamical growth of cyber threats in IoT setting requires smart and scalable intrusion detection systems. In this paper, a Lean-based hybrid Intrusion Detection framework using Particle Swarm Optimization and Genetic Algorithm (PSO-GA) to select the features and Extreme Learn...

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محفوظ في:

التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Islam Zada (21755819) (author)
مؤلفون آخرون:	Esraa Omran (6392693) (author), Salman Jan (21755822) (author), Hessa Alfraihi (21755825) (author), Seetah Alsalamah (21755828) (author), Abdullah Alshahrani (9458515) (author), Shaukat Hayat (14634285) (author), Nguyen Phi (21755831) (author)
منشور في:	2025
الموضوعات:	Space Science Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified visual evaluation metrics visual analytics approach optimal detection efficiency minimal computational overhead important attack categories 100 percent accuracy extreme learning machine enhancing iot cybersecurity changing cyber threats cyber threats ensemble learning xlink "> world usage statistical verification sql injection smart cities provides scalable making process like portscan industrial internet greatly minimized genetic algorithm false positives efficiently ported dynamical growth brute force bootstrap aggregation 2017 dataset
الوسوم:	إضافة وسم لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!

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