<![CDATA[Cybersecurity threats are escalating due to the evolution of LockBit 3.0 ransomware, which has disrupted national vital sectors. This study aims to demonstrate the implementation of the MITRE D3FEND framework to mitigate these attacks within a Windows 11 environment. An experimental method using a technical comparative analysis approach was applied and validated through 50 test iterations to ensure data reliability. The results indicate that the baseline unprotected system is completely vulnerable to the entire LockBit 3.0 attack chain. However, the deployment of MITRE D3FEND controls proactively enhances system resilience, achieving a 75% effectiveness score by successfully executing passive detection and real-time active blocking at critical attack vectors. This study concludes that a digital artifact-based defense strategy significantly hardens cyber infrastructure, while recommending future developments in artificial intelligence (AI) based adaptive mitigation automation.Kata kunci: MITRE D3FEND; LockBit 3.0; Cybersecurity; Ransomware; Mitigation AbstrakAncaman keamanan siber meningkat akibat evolusi ransomware LockBit 3.0 yang melumpuhkan berbagai sektor vital nasional. Penelitian ini bertujuan mendemonstrasikan implementasi kerangka kerja MITRE D3FEND dalam memitigasi serangan tersebut pada Windows 11. Metode eksperimen diterapkan melalui pendekatan analisis komparatif teknis yang divalidasi lewat 50 kali iterasi pengujian guna menjamin reliabilitas data. Hasil pengujian menunjukkan bahwa sistem standar tanpa proteksi sepenuhnya rentan terhadap seluruh rangkaian serangan LockBit 3.0. Namun, penerapan kontrol pertahanan MITRE D3FEND terbukti proaktif meningkatkan resiliensi sistem dengan skor efektivitas mencapai 75% melalui keberhasilan fungsi deteksi pasif serta pemblokiran aktif secara real-time di titik-titik krusial serangan. Penelitian ini menyimpulkan bahwa strategi pertahanan berbasis artefak digital secara signifikan memperkeras keamanan infrastruktur siber, sekaligus merekomendasikan pengembangan otomatisasi mitigasi adaptif berbasis kecerdasan buatan (AI) di masa depan. ]]>
