電話詐騙的手法層出不窮，全球每年因被詐騙而損失的金額越來越高，在台灣每年被電話詐騙的金額已經超過四億，電話詐騙的問題日益嚴重，影響社會甚鉅。在這篇論文中，我們分析知名防詐騙App公司的資料，分析台灣行動電話使用者的通話記錄與封鎖清單之紀錄，從這些記錄中觀察並且區分詐騙電話與一般民眾的通話行為，進而達到防治的作用。本篇論文從社會網路分析為出發點，觀察行動電話的通話網路，從中找出了四項可以區分一般電話與詐騙電話的數值，分別為撥號次數、通話時間區間、共同撥號次數與撥號對象。建立一檢測異常通話行為之演算法，檢測之精確率達(88.48%)。比過去只依靠撥號次數異常或是通話時間長短來的方式來判斷詐騙電話，新的檢測方法可以更快速且更準確的檢測詐騙電話。

Telephone scams exact a huge toll on consumers and society, with at large annual costs in the Taiwan alone can exceeding $4 billion. The global proliferation of the Internet has enabled con artists to export their craft to a rapidly expanding market and reach previously untapped consumers. For example, fraud gangs can make a call from China using the fake phone number to Taiwan. People in Taiwan will average received a fraud phone each month. In this paper, we analyze the call detail records and Blocked record of the mobile phone user. More precisely, we identify the fraud calls and analyze the calling behavior of these scammers. To detect scammers, we use statistics and social network analysis, developed four features: Call Count, Call Friend, Call Relevance and Call Duration Interval. Based on the analysis of calling behavior, we build an algorithm. Our results show that this model can detect and predict abnormal calling behavior with high precision (76.1%). We can block fraud phone numbers faster than ever before.

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