博碩士論文 111522096 完整後設資料紀錄

DC 欄位 語言
DC.contributor資訊工程學系zh_TW
DC.creator朱席靚zh_TW
DC.creatorHsi-Ching Chuen_US
dc.date.accessioned2024-7-22T07:39:07Z
dc.date.available2024-7-22T07:39:07Z
dc.date.issued2024
dc.identifier.urihttp://ir.lib.ncu.edu.tw:444/thesis/view_etd.asp?URN=111522096
dc.contributor.department資訊工程學系zh_TW
DC.description國立中央大學zh_TW
DC.descriptionNational Central Universityen_US
dc.description.abstract網路威脅情報 (CTI) 透過提供來自不同資料來源的可行見解,顯著增強組織網路安全防禦。本研究研究了 CTI 分析與 MITRE ATT&CK 框架之間的相關性,重點關注它們的結合以增強威脅偵測和回應能力。這項研究的一個關鍵方面涉及開發一個分類器,使用基於 BERT 的模型將 CTI 報告映射到特定的ATT&CK 技術。我們的模型比基線 SecBERT 有了顯著的改進,F1-score 提高了 2.6%,Top-3 Accuracy 提高了 4.2%。透過 CTI 與 MITRE ATT&CK 框架的整合,研究人員可以從被動式網路安全策略轉向主動式網路安全策略。這種整合可以快速偵測新出現的威脅,提高事件回應效率,並強化針對不斷變化的網路威脅的防禦措施。最終,CTI 和 ATT&CK 之間的協同效應在當今動態的威脅環境中形成了一種全面的網路安全管理方法。zh_TW
dc.description.abstractCyber Threat Intelligence (CTI) significantly enhances organizational cybersecurity defenses by providing actionable insights from diverse data sources. This research studies the correlation between CTI analysis and the MITRE ATT&CK framework, focusing on their alignment to strengthen threat detection and response capabilities. A pivotal aspect of this study involves developing a classifier using a fine-tuned BERT-based model to map CTI reports to specific ATT&CK techniques. Our model demonstrated substantial improvements over the baseline SecBERT, achieving a 2.6% higher F1-score and a 4.2% improvement in Top-3 Accuracy. By integrating CTI with the MITRE ATT&CK framework, researchers can shift from reactive to proactive cybersecurity strategies. This integration enables swift detection of emerging threats, enhances incident response effectiveness, and fortifies defensive measures against evolving cyber threats. Ultimately, the synergy between CTI and ATT&CK fosters a comprehensive approach to cybersecurity management in today′s dynamic threat landscape.en_US
DC.subject網路威脅zh_TW
DC.subject自然語言處理zh_TW
DC.subject機器學習zh_TW
DC.subjectCyber Threat Intelligenceen_US
DC.subjectMITRE ATT&CKen_US
DC.subjectNatural Language Processingen_US
DC.subjectMachine Learningen_US
DC.titleFrom Data to Action: CTI Analysis and ATT&CK Technique Correlationen_US
dc.language.isoen_USen_US
DC.type博碩士論文zh_TW
DC.typethesisen_US
DC.publisherNational Central Universityen_US

若有論文相關問題,請聯絡國立中央大學圖書館推廣服務組 TEL:(03)422-7151轉57407,或E-mail聯絡  - 隱私權政策聲明