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蘇彥儒
員工門禁行為模式偵測
員工門禁行為模式偵測
員工門禁行為模式偵測
By
蘇彥儒
Deep Learning Engineer
・
Kaohsiung City, Taiwan
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傳統感應式門禁系統記錄員工刷卡資訊,然而門禁系統僅記錄資訊,必須透過異常規則或人工判讀才能偵測異常門禁行為。換言之,若有新不當行為模式發生,傳統感應式門禁系統將無法偵測不當行為,必須等到監控人員察覺或該行為被舉發,方能針對該行為模式手動訂定規則進行防範。因此傳統感應式門禁系統對新型不當行為不僅易發生遺漏情況,且不一定能夠在關鍵時刻偵測不當行為,容易造成門禁系統漏洞。 本專案利用機器學習技術,利用過往刷卡門禁資料建立員工刷卡行為模型,自動歸納推導異常行為模式,偵測員工每一筆刷卡紀錄,判斷是否為不當刷卡行為,建立全方位且快速門禁行為偵測系統。該演算法不僅強化傳統門禁系統安全性,並且已在實務中驗證並成功找出異常行為,為企業安全把關
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蘇彥儒
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Published: May 19th 2020
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Tools
Python
Python
Access Control Patterns Detection
Machine learning
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