臺灣博碩士論文加值系統

驗證碼(Completely Automated Public Turing test to Tell Computers and Humans Apart, CAPTCHA)是一種預防惡意使用者利用自動機器人程式濫用網路服務的安全措施，其中又以文字型態的驗證碼最為普遍；然而文字型態的驗證碼仍可透過電腦程式加以辨識而破解。因此驗證碼的設計均透過不同的干擾設計，使電腦不易辨識，以達到區分使用者是電腦還是人類的目標，但過度的干擾設計可能會增加人類在辨識時視覺與認知的負荷。此外，隨著社會高齡化的趨勢，中老年族群網路使用者日益增加，文字驗證碼的設計更需考量該族群在視覺及認知方面與其它族群的差異。因此本研究將年齡族群分別為青少年和中老年，比較年齡族群和干擾設計在辨識文字驗證碼時，文字驗證碼績效、視覺疲勞及心智負荷量等方面的差異。

實驗結果顯示，受測者在辨識字體破碎及不完整的干擾類型時，辨識績效較差，且視覺疲勞及心智負荷量都較高，其中又以中老年族群受到的影響最為嚴重。此外，中老年族群在辨識彩色背景與文字搭配的干擾設計時有頗高的成功率。因此，本研究建議使用不會破壞字體完整性的干擾設計，並增加遮蔽元素(如線條、圓圈等)及搭配彩色背景，如此除了可有效防止文字驗證碼被破解外，又能減少使用者在辨識文字驗證碼時所面臨的負荷。

CAPTCHA, the acronym of “Completely Automatic Public Turning test to tell Computers and Human Apart”, is a security measures that guards internet against automated exploitations with abusive purposes by ill-motivated users. Among them, text-based CAPTCHA is the most common type. However, text-based CAPTCHA can be breached by character recognition programs. Therefore, to effectively tell whether a user in question is a human being or a robot program, most text-based CAPTCHA designs employ distortion techniques to defend the attack by character recognition programs. Yet, the distortion techniques themselves may increase the loading on the visual system and cognitive system of human solvers. In addition, given the trend of our aging society, the design of text-based CAPTCHA should take into account the differences between the senior and young users in terms of visual and cognitive systems. This study considered participants of two age groups (young and senior) and some common types of text-based CAPTCHA. Comparisons were made between the two groups in terms of task performance, visual fatigue, and mental workload.

The results indicated that when recognizing CAPTCHAs whose contours were incomplete due to the distortions, participants had poorer accuracy, higher visual fatigue, and higher workload; the senior group underwent more serious impact than the young group did. In addition, the senior group had higher accuracy than the young group in the recognition of CAPTCHAs that emploied color background and character distortion techniques. Therefor, this study suggests the use of distortions that do not break the character contour, extra obscure elements (such as lines or circles), and color background, in the design of CAPTCHAs to ensure the effectiveness of CAPTCHAs in terms of security and to reduce the workload real users may face when they encounter CAPTCHAs online.

目錄
摘要 I
Abstract III
誌謝 IV
目錄 V
圖目錄 IX
表目錄 XI
第一章 緒論 1
1.1研究背景 1
1.2研究動機與目的 4
1.3研究架構 5
1.4研究限制 6
第二章 文獻探討 7
2.1 驗證碼 7
2.1.1 驗證碼的類型 8
2.1.2 常見的文字驗證碼干擾 12
2.2年齡相關影響 13
2.2.1老化對生理機能的影響 14
2.2.2 年齡與人機介面 14
2.3文字視覺辨識處理 17
第三章 研究方法 20
3.1研究對象 22
3.2實驗設備 23
3.3實驗環境配置 24
3.4實驗設計 26
3.5標準作業程序 36
3.6研究假設 42
3.7資料統計分析 46
第四章 研究分析與討論 47
4.1受測者基本資料 47
4.1.1受測者基本資料之敘述性統計 47
4.2閃光融合閾值 48
4.2.1閃光融合閾值之敘述性統計與無母數檢定 49
4.3視覺疲勞主觀評量 51
4.3.1視覺疲勞主觀評量之敘述性統計與無母數檢定 51
4.4 NASA-TLX心智負荷量 53
4.4.1 NASA-TLX心智負荷量之敘述性統計與無母數檢定 53
4.5實驗反應時間 57
4.5.1實驗反應時間之敘述性統計與無母數檢定 57
4.6錯誤 63
4.6.1錯誤之敘述性統計與無母數檢定 63
4.7相關係數分析 76
4.8討論 77
第五章 結論 81
參考文獻 82
附錄A 91
受測者基本資料調查問卷 91
附錄B 92
CFF與視覺疲勞主觀評量表 92
附錄C 93
NASA-TLX 主觀心智評量表 93
附錄D 94
色盲檢查卡 94
附錄E 95
實驗用之字型特徵 95
附錄F 95
實驗開始前黑色十字圖 95
附錄G 96
練習用之文字驗證碼 96
正式用之文字驗證碼 99
練習用之原始資料 102
正式用之原始資料 102
附錄H 103
字母數字出現頻率平均化 103
附錄I 104
型別順序 104
圖片出現順序(1/2) 105
圖片出現順序(2/2) 106


圖目錄
圖1-1 ReCAPTCHA 2
圖1-2 Hotmail CAPTCHA 2
圖1-3 研究架構 5
圖2-1 文字驗證碼 11
圖2-2 針對work文字的文字視覺辨識處理流程 18
圖2-3 Google CAPTCHA 19
圖2-4 Microsoft CAPTCHA 19
圖3-1 實驗說明階段流程圖 20
圖3-2 實驗正式階段流程圖 22
圖3-3 實驗設備 24
圖3-4 電腦作業操作姿勢 25
圖3-5 環境照度測量模擬圖 26
圖3-6 實驗之文字驗證碼 28
圖3-7 測量CFF 30
圖3-8 測量視力值 38
圖3-9 檢測色盲 39
圖3-10 人類訊息處理模式階段 42
圖4-1 型別分組對實驗干擾設計的CFF變化量 51
圖4-2 型別分組對實驗干擾設計的視覺疲勞主觀量 53
圖4-3 年齡分組對顯著實驗干擾設計的心智負荷量 55
圖4-4 型別分組對實驗干擾設計的心智負荷量 57
圖4-5 年齡分組對顯著實驗干擾設計的實驗反應時間 61
圖4-6 型別分組對實驗干擾設計的實驗反應時間 63
圖4-7 年齡分組對顯著實驗干擾設計的錯誤個數 66
圖4-8 型別分組對實驗干擾設計的錯誤個數 67
圖4-9 年齡分組對顯著實驗干擾設計的錯誤組數 70
圖4-10 型別分組對實驗干擾設計的錯誤組數 71
圖4-11 年齡分組對型別一的相似因素 74


表目錄
表3-1 錯誤個數範例 33
表3-2 錯誤組數範例 34
表3-3 錯誤因素定義 34
表3-4 相似因素錯誤範例 35
表3-5 記憶因素錯誤範例 35
表3-6 干擾因素錯誤範例 35
表3-7 記憶相似因素錯誤範例 35
表3-8 干擾相似因素錯誤範例 35
表3-9 干擾記憶因素錯誤範例 36
表3-10 每個型別之練習機制與正式實驗休息時間 41
表4-1 年齡分組之受測者基本資料 47
表4-2 年齡分組對文字驗證碼的認知 48
表4-3 年齡分組對文字驗證碼之目前為止通過機率 48
表4-4 年齡分組對實驗干擾設計的CFF變化量之無母數檢定 49
表4-5 型別分組對實驗干擾設計的CFF變化量之無母數檢定 50
表4-6 型別分組對於實驗干擾設計的CFF變化量 50
表4-7 年齡分組對實驗干擾設計的視覺疲勞主觀量之無母數檢定 52
表4-8 型別分組對實驗干擾設計的視覺疲勞主觀評量之無母數檢定 52
表4-9 型別分組對實驗干擾設計的視覺疲勞主觀量 53
表4-10 年齡分組對實驗干擾設計的心智負荷量之無母數檢定 54
表4-11 年齡分組對顯著實驗干擾設計的心智負荷量值 54
表4-12 型別分組對實驗干擾設計的心智負荷量之無母數檢定 56
表4-13 型別分組對實驗干擾設計的心智負荷量值 56
表4-14 年齡分組對實驗干擾設計的實驗反應時間之無母數檢定 58
表4-15 年齡分組對顯著實驗干擾設計的實驗反應時間 58
表4-16 型別分組對實驗干擾設計的實驗反應時間之無母數檢定 62
表4-17 型別分組對實驗干擾設計的實驗反應時間 62
表4-18 年齡分組對實驗干擾設計的錯誤個數之無母數檢定 64
表4-19 年齡分組對顯著實驗干擾設計的錯誤個數 64
表4-20 型別分組對實驗干擾設計的錯誤個數之無母數檢定 67
表4-21 型別分組對實驗干擾設計的錯誤個數 67
表4-22 年齡分組對實驗干擾設計的錯誤組數之無母數檢定 68
表4-23 年齡分組對顯著實驗干擾設計的錯誤組數 68
表4-24 型別分組對實驗干擾設計的錯誤組數之無母數檢定 71
表4-25 型別分組對實驗干擾設計的錯誤組數 71
表4-26 年齡分組對實驗干擾設計的錯誤類型之無母數檢定 72
表4-27 年齡分組對實驗干擾設計的錯誤類型 73
表4-28 中老年對實驗干擾設計的錯誤類型之平均個數 73
表4-29 青少年對實驗干擾設計的錯誤類型之平均個數 74
表4-30 型別分組對實驗干擾設計的錯誤類型之無母數檢定 75
表4-31 型別分組對實驗干擾設計的錯誤類型 76
表4-32 Peason相關係數分析 77

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