Lightweight Deep Learning Untuk Intrusion Detection System

• IHUD HAFID
• 14210208

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ABSTRAK

ABSTRAK

Nama              : Ihud Hafid

NIM                 : 14210208

Program Studi : Ilmu komputer

Fakultas          : Teknologi Informasi

Jenjang           : Strata Dua (S2)

Konsentrasi     : Data Mining

Judul               : “Lightweight Deep Learning Untuk Intrusion Detection System”

Internet of Things (IoT) rentan terhadap berbagai ancaman. Penelitian ini mengembangkan lightweight intrusion detection system untuk meningkatkan keamanan IoT. Lightweight Deep Learning berfokus pada pengembangan model yang dioptimalkan untuk efisiensi dengan menggunakan TensorFlow Lite, sehingga ukuran model yang dihasilkan lebih kecil, dan footprint memori yang lebih rendah. Model ini dirancang agar lebih ramah sumber daya, membuatnya cocok untuk diterapkan pada perangkat dengan sumber daya terbatas seperti edge computing. Berdasarkan hasil Accuracy sebesar 0.95 dan penilaian terhadap hasil Model runtime, Memory usage increase, CPU usage increase, Storage usage increase dan Save model size terbaik didapatkan oleh model Lightweight Artificial Neural Network.

KATA KUNCI

Deep Learning,Lightweight,Internet of things,Edge computing

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DAFTAR PUSTAKA

DAFTAR PUSTAKA

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