{"id":27065,"date":"2022-04-07T00:18:47","date_gmt":"2022-04-06T16:18:47","guid":{"rendered":"https:\/newsletter.sinica.edu.tw\/?p=27065"},"modified":"2022-04-07T06:52:42","modified_gmt":"2022-04-06T22:52:42","slug":"%e3%80%90%e5%b0%88%e6%ac%842%e3%80%91%e6%b7%b1%e5%81%bd%e5%81%b5%e6%b8%ac-%e5%9c%a8%e6%b7%b1%e5%81%bd%e5%85%a7%e5%ae%b9%ef%bc%88deepfake%ef%bc%89%e6%b0%be%e6%bf%ab%e7%9a%84%e6%99%82%e4%bb%a3","status":"publish","type":"post","link":"https:\/newsletter.sinica.edu.tw\/27065\/","title":{"rendered":"\u3010\u5c08\u6b042\u3011\u6df1\u507d\u5075\u6e2c\u2014\u5728\u6df1\u507d\u5167\u5bb9\uff08Deepfake\uff09\u6c3e\u6feb\u7684\u6642\u4ee3\uff0c\u773c\u898b\u4ecd\u70ba\u6191\u55ce?"},"content":{"rendered":"<p><strong>\u6df1\u507d\u5167\u5bb9\uff08Deepfake\uff09<\/strong><\/p>\n<p>\u96a8\u8457\u8fd1\u5e74\u4f86\u6df1\u5ea6\u5b78\u7fd2\u6280\u8853\u8207\u76f8\u95dc\u751f\u6210\u6a21\u578b\u7684\u5feb\u901f\u767c\u5c55\uff0c\u591a\u5a92\u9ad4\uff08\u5305\u62ec\u5f71\u50cf\u3001\u8072\u97f3\u3001\u6587\u5b57\uff09\u5167\u5bb9\u751f\u6210\u7cfb\u7d71\u6548\u80fd\u5927\u5e45\u63d0\u5347\uff0c\u8457\u540d\u7684\u65b9\u6cd5\u5982NVIDIA\u7684StyleGAN\uff08Karras et al. 2019\u3001Karras et al. 2021\uff09\u548cGauGAN\uff08Park et al. 2019\uff09\u3002\u80fd\u505a\u51fa\u9ad8\u4eff\u771f\u5167\u5bb9\u507d\u9020\u5df2\u7d93\u4e0d\u50c5\u4fb7\u9650\u65bc\u719f\u6089\u591a\u5a92\u9ad4\u7de8\u8f2f\u8edf\u9ad4\u7684\u5275\u4f5c\u8005\uff0c\u666e\u7f85\u5927\u773e\u4e5f\u80fd\u900f\u904e\u7db2\u8def\u4e0a\u5404\u5f0f\u57fa\u65bc\u6df1\u5ea6\u751f\u6210\u6a21\u578b\uff0c\u5982\u751f\u6210\u5c0d\u6297\u7db2\u8def\uff08Generative Adversarial Network\uff09\u4e4b\u958b\u6e90\u8edf\u9ad4\u8f15\u6613\u4fee\u6539\u5716\u7247\u3001\u8072\u97f3\u3001\u8207\u6587\u5b57\u7b49\u6578\u4f4d\u5167\u5bb9\uff0c\u5982\u4f7f\u7528DeepFace Lab\u8207FaceApp\u7b49\u8edf\u9ad4\uff08FaceApp, 2021\u3001FaceSwap, 2021\u3001DeepFaceLab, 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aria-describedby=\"caption-attachment-21652\" class=\"alignnone size-full wp-image-27066\" src=\"https:\/newsletter.sinica.edu.tw\/wp-content\/uploads\/2022\/04\/3-2-1.png\" alt=\"\" width=\"832\" height=\"600\" srcset=\"https:\/newsletter.sinica.edu.tw\/wp-content\/uploads\/2022\/04\/3-2-1.png 832w, https:\/newsletter.sinica.edu.tw\/wp-content\/uploads\/2022\/04\/3-2-1-300x216.png 300w, https:\/newsletter.sinica.edu.tw\/wp-content\/uploads\/2022\/04\/3-2-1-768x554.png 768w\" sizes=\"(max-width: 832px) 100vw, 832px\" \/><p id=\"caption-attachment-21652\" class=\"wp-caption-text\">\u5716\u4e00\u3001<br \/>\uff08a\uff09\u900f\u904e\u6df1\u5ea6\u9020\u5047\u7684\u6280\u8853\u4f86\u4fee\u6539\u4eba\u81c9\uff1a\u63db\u81c9\u3001\u4eba\u81c9\u5fae\u8abf\uff0c\u5176\u4e2d\u5982\u5716\u6240\u793a\u3002\u5f71\u50cf\u4f86\u6e90\uff1aR\u00f6ssler et al. 2019\u3002<br \/>\uff08b\uff09\u660e\u661fTom Cruise\u7684\u6df1\u507d\u5f71\u7247\u54c1\u8cea\u4e4b\u9ad8\uff0c\u771f\u5047\u96e3\u8fa8\u3002\u5f71\u50cf\u4f86\u6e90\uff1aChris Ume and Miles Fisher, 2021\u3002<br \/>\uff08c\uff09\u5404\u7a2e\u4e0d\u540c\u7684\u6df1\u5ea6\u751f\u6210\u6a21\u578b\u7684\u7455\u75b5\uff0c\u5982\u6df1\u507d\u751f\u6210\u7684\u4eba\u81c9\u5176\u7259\u9f52\u4e0d\u6703\u8ddf\u8457\u982d\u64fa\u52d5\u3001\u6216\u77b3\u5b54\u4e0d\u662f\u6a62\u5713\u5f62\u3001\u5f71\u50cf\u6216\u4eba\u81c9\u63a5\u5408\u8655\u6709\u660e\u986f\u7684\u7455\u75b5\u3002\u5f71\u50cf\u4f86\u6e90\uff1aR\u00f6ssler et al. 2019\u3001Karras et al. 2019\u3001Hui et al. 2022\u3001Qi et al. 2020\u3002<\/p><\/div>\n<p><strong>\u6df1\u507d\u5075\u6e2c\u8207\u5176\u4ed6\u53ef\u80fd\u7684\u53cd\u5236\u624b\u6bb5<\/strong><\/p>\n<p>\u96a8\u8457\u6df1\u5ea6\u9020\u5047\u7684\u6280\u8853\u4e0d\u65b7\u9032\u5316\uff0c\u507d\u9020\u5167\u5bb9\u7684\u6c3e\u6feb\u6709\u53ef\u80fd\u6703\u6f14\u8b8a\u6210\u4e0d\u53ef\u5ffd\u8996\u7684\u8cc7\u8a0a\u5b89\u5168\u5371\u6a5f\uff0c\u6709\u9452\u65bc\u6b64\uff0c\u7f8e\u570bDARPA\u65e9\u57282016\u5e74\u5373\u958b\u59cbMedia Forensics\u7814\u7a76\u8a08\u756b\uff0c\u958b\u767c\u95dc\u9375\u6280\u8853\u4ee5\u904f\u6b62\u76f8\u95dc\u591a\u5a92\u9ad4\u507d\u9020\u5167\u5bb9\u7684\u6c3e\u6feb\u3002\u540c\u6642DARPA\u4e5f\u8a08\u756b\u57282020\u5e74\u4e2d\u958b\u555fSemantic Forensics\u7814\u7a76\u8a08\u756b\uff0c\u8a08\u756b\u8b93\u6a5f\u5668\u80fd\u4e86\u89e3\u5716\u50cf\u53ca\u5f71\u7247\u4e2d\uff0c\u6240\u860a\u542b\u7684\u8a9e\u610f\uff0c\u505a\u51fa\u66f4\u7cbe\u6e96\u7684\u507d\u9020\u5167\u5bb9\u8fa8\u8b58\u548c\u4e8b\u4ef6\u5075\u6e2c\u3002\u800c\u81c9\u66f8\uff08Meta\uff09\u3001\u8c37\u6b4c\uff08Google\uff09\u3001\u5fae\u8edf\uff08Microsoft\uff09\u7b49\u5927\u516c\u53f8\u6301\u7e8c\u6295\u5165\u5927\u91cf\u8cc7\u6e90\u65bc\u76f8\u95dc\u9451\u8b58\u7814\u7a76\uff0c\u81c9\u66f8\u57282020\u5e74\u6642\uff0c\u66fe\u8209\u8fa6\u7e3d\u734e\u91d1\u9ad8\u9054100\u842c\u7f8e\u5143\u7684\u6df1\u507d\u5075\u6e2c\u7af6\u8cfd\uff0c\u5438\u5f15\u5168\u7403\u8d85\u904e300\u500b\u968a\u4f0d\u5831\u540d\u53c3\u52a0\uff0c\u7531\u6b64\u53ef\u898b\u76f8\u95dc\u7814\u7a76\u7684\u91cd\u8981\u6027\u8207\u65e5\u4ff1\u589e\uff0c\u4e26\u9010\u6f38\u7372\u5f97\u5404\u754c\u7684\u95dc\u6ce8\u3002\u800c\u6df1\u507d\u5075\u6e2c\u662f\u76ee\u524d\u6700\u71b1\u9580\u7684\u9632\u79a6\u65b9\u6cd5\u4e4b\u4e00\uff0c\u4ee5\u6df1\u507d\u5f71\u50cf\u70ba\u4f8b\uff0c\u5982\u679c\u8981\u5075\u6e2c\u6578\u4f4d\u5167\u5bb9\u662f\u5426\u88ab\u7ac4\u6539\uff0c\u6700\u7c21\u55ae\u7684\u65b9\u5f0f\uff0c\u53ef\u4ee5\u900f\u904e\u76e3\u7763\u5b78\u7fd2\u7684\u65b9\u5f0f\uff0c\u6536\u96c6\u5305\u542b\u6df1\u507d\u5f71\u50cf\u548c\u6b63\u5e38\u5f71\u50cf\u7684\u8a13\u7df4\u8cc7\u6599\uff0c\u4e26\u4f7f\u7528\u6df1\u5ea6\u5b78\u7fd2\u6216\u5176\u4ed6\u6a5f\u5668\u5b78\u7fd2\u6a21\u578b\u5efa\u7acb\u4e00\u500b\u300c\u4e8c\u5143\u5206\u985e\u5668\u300d\uff08Binary Classifier\uff09\uff0c\u5c07\u4efb\u4f55\u8f38\u5165\u5716\u50cf\u5f71\u7247\u5206\u70ba\u5169\u985e\uff1a\u771f\u5be6\u6216\u507d\u9020\u3002\u4f46\u56e0\u70ba\u6df1\u507d\u6f14\u7b97\u6cd5\u4e0d\u65b7\u5feb\u901f\u63a8\u51fa\u65b0\u7684\u6a21\u578b\uff0c\u6b64\u985e\u65b9\u6cd5\u9700\u8981\u6536\u96c6\u5927\u91cf\u6df1\u507d\u8cc7\u6599\u4ee5\u76e1\u53ef\u80fd\u5305\u542b\u5404\u7a2e\u60c5\u6cc1\uff0c\u4e0d\u50c5\u6536\u96c6\u8207\u6a19\u8a3b\u8cbb\u6642\u8cbb\u529b\uff0c\u5be6\u52d9\u4e0a\u57f7\u884c\u4e5f\u6709\u76f8\u7576\u7684\u56f0\u96e3\u5ea6\u3002<\/p>\n<p>\u56e0\u6b64\uff0c\u4e5f\u6709\u7814\u7a76\u8457\u91cd\u65bc\u63a2\u7d22\u6df1\u5ea6\u751f\u6210\u6a21\u578b\u7684\u751f\u6210\u6975\u9650\uff0c\u5982\u76ee\u524d\u6df1\u507d\u6280\u8853\u751f\u6210\u7684\u5f71\u7247\u4ecd\u5b58\u5728\u4e00\u4e9b\u8996\u89ba\u7455\u75b5\u6216\u4e0d\u7b26\u5408\u5e38\u7406\uff0c\u53ef\u4f9b\u8fa8\u8b58\u548c\u5075\u6e2c\u4e4b\u7528\uff0c\u5f88\u591a\u7814\u7a76\u5247\u5229\u7528\u9019\u4e9b\u7455\u75b5\u4ee5\u8a2d\u8a08\u6cdb\u5316\u80fd\u529b\u5f37\u7684\u5075\u6e2c\u6a21\u578b\uff0c\u5e38\u898b\u7684\u7455\u75b5\u5982\u5716\u4e00\uff08c\uff09\u6240\u793a\uff0c\u751f\u6210\u7684\u5716\u50cf\u5f71\u7247\u88e1\u662f\u5426\u80cc\u666f\u5340\u57df\u6a21\u7cca\u3001\u4eba\u81c9\u5340\u584a\u6709\u6c92\u6709\u9583\u720d\uff08\u5c24\u5176\u662f\u773c\u775b\u90e8\u5206\uff0c\u4eba\u7684\u77b3\u5b54\u662f\u6a62\u5713\u5f62\uff0c\u4f46\u751f\u6210\u6a21\u578b\u751f\u6210\u7684\u77b3\u5b54\u901a\u5e38\u70ba\u4e0d\u898f\u5247\uff0c\u800c\u4e14\u96d9\u773c\u770b\u5230\u7684\u4e8b\u7269\u4e0d\u4e00\u81f4\uff09\u3001\u81c9\u90e8\u8f2a\u5ed3\u908a\u7de3\u7684\u7d0b\u7406\u662f\u5426\u81ea\u7136\u3001\u63a5\u5408\u8655\u662f\u5426\u6709\u660e\u986f\u7455\u75b5\u3001\u5f71\u7247\u8de8\u5e40\u6642\u81c9\u90e8\u8f2a\u5ed3\u6216\u7d0b\u7406\u662f\u5426\u6709\u5931\u771f\uff0c\u6216\u8b1b\u8005\u5728\u6709\u5927\u5e45\u5ea6\u79fb\u52d5\u52d5\u4f5c\u6642\u5176\u5f71\u50cf\u7d0b\u7406\u662f\u5426\u6b63\u5e38\u7b49\u8996\u89ba\u7455\u75b5\u3002\u53e6\u5916\uff0c\u50cf\u67d0\u4e9b\u6df1\u507d\u6280\u8853\uff0c\u4e26\u6c92\u6709\u8fa6\u6cd5\u8b93\u8aaa\u8a71\u8005\u7684\u8072\u97f3\u8207\u5634\u90e8\u5f71\u50cf\u9054\u5230\u5341\u5206\u543b\u5408\u8207\u540c\u6b65\uff0c\u56e0\u6b64\uff0c\u53ef\u4ee5\u900f\u904e\u9010\u798e\u6aa2\u9a57\u5f71\u50cf\u8207\u5c0d\u61c9\u97f3\u6a94\uff0c\u770b\u770b\u662f\u5426\u6709\u5730\u65b9\u662f\u4e0d\u543b\u5408\u7684\u3002\u56e0\u70ba\u76ee\u524d\u6df1\u507d\u9020\u5047\u6280\u8853\u9084\u6c92\u8fa6\u6cd5\u505a\u5230\u540c\u6642\u6a21\u4eff\u4e00\u500b\u4eba\u7684\u8868\u60c5\u8207\u8072\u97f3\u60c5\u7dd2\uff0c\u6211\u5011\u4e5f\u53ef\u4ee5\u900f\u904e\u6aa2\u9a57\u8072\u97f3\u4e2d\u7684\u60c5\u7dd2\uff0c\u4ee5\u53ca\u4ed6\u7684\u9762\u90e8\u8868\u60c5\u662f\u5426\u543b\u5408\u4f86\u8fa8\u5225\u771f\u507d\u3002\u800c\u6df1\u507d\u5f71\u7247\u8981\u9054\u5230\u826f\u597d\u7684\u751f\u6210\u54c1\u8cea\u4e5f\u9700\u8981\u5927\u91cf\u7684\u8cc7\u6599\uff0c\u6240\u4ee5\u540d\u4eba\u7b49\u64c1\u6709\u8f03\u591a\u516c\u958b\u5f71\u7247\u8cc7\u6599\uff0c\u7b49\u540c\u63d0\u4f9b\u6df1\u507d\u7b97\u6cd5\u7684\u8c50\u5bcc\u7d20\u6750\uff0c\u6211\u5011\u53ef\u5c07\u5c07\u8f03\u6709\u540d\u7684\u540d\u4eba\u5efa\u7acb\u4e00\u500b\u5b57\u5178\uff0c\u91dd\u5c0d\u7279\u5b9a\u7684\u65b0\u805e\u6587\u7ae0\u6216\u5f71\u7247\u5b57\u5e55\u4e2d\u6709\u51fa\u73fe\u9019\u4e9b\u540d\u4eba\uff0c\u5247\u6211\u5011\u61c9\u8003\u616e\u5230\u53ef\u80fd\u6703\u6709\u88ab\u9032\u884c\u6df1\u507d\u9020\u5047\u7684\u53ef\u80fd\uff0c\u4e26\u9032\u4e00\u6b65\u5c0d\u53ef\u7591\u65b0\u805e\u5f71\u7247\u4f5c\u5206\u6790\uff0c\u5982\u6b64\u4e00\u4f86\u4e5f\u53ef\u4ee5\u5f9e\u6d77\u91cf\u5f85\u5075\u6e2c\u7684\u6578\u64da\u7576\u4e2d\u5148\u7be9\u9078\u51fa\u4e00\u4e9b\u8f03\u53ef\u80fd\u88ab\u9020\u5047\u7684\u7d20\u6750\u3002\u9664\u4e86\u6df1\u507d\u5075\u6e2c\u7684\u9632\u79a6\u624b\u6bb5\uff0c\u4e5f\u6709\u76f8\u95dc\u7814\u7a76\u900f\u904e\u5c0d\u6297\u6a23\u672c\uff08Adversarial Example\uff09\u653b\u64ca\uff08GoodFellow et al. 2014\uff09\uff0c\u5728\u8f38\u5165\u8a0a\u865f\u6dfb\u52a0\u4eba\u773c\u4e0d\u53ef\u898b\u7684\u64fe\u52d5\uff0c\u9019\u4e9b\u5c0d\u6297\u6a23\u672c\u53ef\u4ee5\u5c0d\u57fa\u65bc\u6df1\u5ea6\u5b78\u7fd2\u6a21\u578b\u7684\u8f38\u51fa\u7522\u751f\u5de8\u5927\u5f71\u97ff\uff0c\u4ee5\u7522\u751f\u932f\u8aa4\u7684\u8fa8\u8b58\u7d50\u679c\uff0c\u6211\u5011\u53ef\u4ee5\u53cd\u5229\u7528\u9019\u7a2e\u653b\u64ca\u8b93\u6df1\u507d\u751f\u6210\u6a21\u578b\u7684\u751f\u6210\u5f71\u50cf\u548c\u8a9e\u97f3\u54c1\u8cea\u5927\u5e45\u4e0b\u964d\u6216\u4e0d\u8d77\u4f5c\u7528\uff0c\u9032\u800c\u4fdd\u8b77\u5167\u5bb9\u4e0d\u88ab\u76dc\u7528\uff08Ruiz et al. 2020\u3001Yeh et al. 2020\u3001Yeh et al. 2020\uff09\uff0c\u5982\u5716\u4e8c\uff08a\uff09\u6240\u793a\u3002\u53e6\u4e00\u65b9\u9762\uff0c\u5728\u5f71\u7247\u5167\u5bb9\u6dfb\u52a0\u4e0d\u53ef\u8996\u6578\u4f4d\u6d6e\u6c34\u5370\uff0c\u8b93\u5167\u5bb9\u64c1\u6709\u8005\u6216\u666e\u7f85\u5927\u773e\u53ef\u4ee5\u66f4\u6709\u6548\u5730\u900f\u904e\u5167\u5d4c\u7684\u6d6e\u6c34\u5370\u8a0a\u606f\u4ee5\u5224\u65b7\u5167\u5bb9\u7684\u771f\u507d\uff0c\u5176\u4e2d\u6709\u76f8\u95dc\u7814\u7a76\u900f\u904e\u5728\u8a13\u7df4\u8cc7\u6599\u6dfb\u52a0\u96b1\u5f62\u6578\u4f4d\u6d6e\u6c34\u5370\uff08Yu et al. 2021\uff09\uff0c\u8b93\u7528\u9019\u4e9b\u8cc7\u6599\u8a13\u7df4\u7684\u6df1\u507d\u751f\u6210\u6a21\u578b\uff0c\u5176\u751f\u6210\u7684\u5167\u5bb9\u90fd\u5305\u542b\u6d6e\u6c34\u5370\uff0c\u900f\u904e\u62bd\u53d6\u6d6e\u6c34\u5370\u5373\u53ef\u8fa8\u5225\u5167\u5bb9\u771f\u507d\uff0c\u5982\u5716\u4e8c\uff08b\uff09\u6240\u793a\u3002<\/p>\n<div id=\"attachment_21652\" style=\"width: 789px\" class=\"wp-caption aligncenter\"><img loading=\"lazy\" decoding=\"async\" aria-describedby=\"caption-attachment-21652\" class=\"alignnone size-full wp-image-27067\" src=\"https:\/newsletter.sinica.edu.tw\/wp-content\/uploads\/2022\/04\/3-2-2.png\" alt=\"\" width=\"779\" height=\"506\" srcset=\"https:\/newsletter.sinica.edu.tw\/wp-content\/uploads\/2022\/04\/3-2-2.png 779w, https:\/newsletter.sinica.edu.tw\/wp-content\/uploads\/2022\/04\/3-2-2-300x195.png 300w, https:\/newsletter.sinica.edu.tw\/wp-content\/uploads\/2022\/04\/3-2-2-768x499.png 768w\" sizes=\"(max-width: 779px) 100vw, 779px\" \/><p id=\"caption-attachment-21652\" class=\"wp-caption-text\">\u5716\u4e8c\u3001<br \/>\uff08a\uff09\u7522\u751f\u5c0d\u6297\u6a23\u672c\u8b93\u5f71\u50cf\u9077\u79fb\u6a21\u578b\u751f\u6210\u5f71\u50cf\u58de\u6389\u3002\u5f71\u50cf\u4f86\u6e90\uff1aRuiz et al. 2020\u3002<br \/>\uff08b\uff09\u57fa\u65bc\u96b1\u5f62\u6578\u4f4d\u6d6e\u6c34\u5370\u4e4b\u6df1\u507d\u5167\u5bb9\u8ffd\u8e64\u8207\u9a57\u8b49\u7cfb\u7d71\u67b6\u69cb\u5716\uff0c\u5728\u8a13\u7df4\u8cc7\u6599\u6bcf\u5f35\u5716\u50cf\u6dfb\u52a0\u4e8c\u5143\u5b57\u4e32\u6d6e\u6c34\u5370\u3002\u5f71\u50cf\u4f86\u6e90\uff1aYu et al. 2021\u3002<\/p><\/div>\n<p><strong>\u672a\u4f86\u7684\u6311\u6230<\/strong><\/p>\n<p>\u76ee\u524d\u57fa\u65bc\u6df1\u5ea6\u5b78\u7fd2\u4e4b\u6df1\u507d\u5075\u6e2c\u5668\uff0c\u5118\u7ba1\u5c0d\u5df2\u77e5\u6df1\u507d\u7b97\u6cd5\u6240\u7522\u751f\u7684\u5167\u5bb9\uff0c\u6709\u975e\u5e38\u597d\u7684\u6027\u80fd\uff0c\u4f46\u5c0d\u65bc\u8a13\u7df4\u8cc7\u6599\u672a\u51fa\u73fe\u904e\u7684\u6df1\u507d\u5167\u5bb9\uff0c\u5c24\u5176\u662f\u7531\u65b0\u7684\u6df1\u507d\u6f14\u7b97\u6cd5\u751f\u6210\u7684\u5167\u5bb9\uff0c\u5176\u5075\u6e2c\u6548\u679c\u5e38\u5927\u6253\u6298\u6263\uff0c\u56e0\u70ba\u6a21\u578b\u904e\u64ec\u5408\u8a13\u7df4\u8cc7\u6599\u5c0e\u81f4\uff0c\u6700\u7c21\u55ae\u7684\u89e3\u6c7a\u65b9\u6cd5\u662f\u4f9d\u8cf4\u6536\u96c6\u66f4\u5927\u91cf\u7684\u8a13\u7df4\u6578\u64da\u4f86\u8a13\u7df4\u66f4\u5f37\u6df1\u507d\u5075\u6e2c\u5668\uff0c\u4f46\u9019\u7a2e\u4f5c\u6cd5\u4e0d\u50c5\u4f7f\u5f97\u7dad\u8b77\u548c\u6536\u96c6\u9019\u6a23\u7684\u8a13\u7df4\u6578\u64da\u96c6\u8b8a\u5f97\u975e\u5e38\u56f0\u96e3\uff0c\u4e5f\u5f88\u96e3\u61c9\u5c0d\u4e0d\u65b7\u5feb\u901f\u63a8\u9673\u51fa\u65b0\u7684\u6df1\u507d\u6f14\u7b97\u6cd5\u3002\u53e6\u4e00\u65b9\u9762\uff0c\u56e0\u70ba\u65b0\u7684\u6df1\u507d\u7b97\u6cd5\u525b\u63a8\u51fa\u7684\u6642\u5019\uff0c\u5176\u751f\u6210\u5167\u5bb9\u4e00\u958b\u59cb\u5728\u7db2\u8def\u4e0a\u66dd\u5149\u9084\u4e0d\u5920\u591a\uff0c\u53ef\u6536\u96c6\u548c\u4f9b\u8a13\u7df4\u5229\u7528\u7684\u8cc7\u6599\u6578\u91cf\u4e0d\u591a\u3002\u56e0\u6b64\uff0c\u5982\u4f55\u50c5\u7528\u5c11\u91cf\u7684\u8cc7\u6599\u6709\u6548\u8a13\u7df4\u6df1\u507d\u5075\u6e2c\u5668\u6216\u662f\u6cdb\u5316\u80fd\u529b\u66f4\u5f37\u7684\u6a21\u578b\uff0c\u662f\u4e00\u500b\u975e\u5e38\u6311\u6230\u4e14\u4e9f\u5f85\u89e3\u6c7a\u7684\u7814\u7a76\u554f\u984c\uff0c\u6216\u662f\u5982\u4f55\u5229\u7528\u591a\u6a21\u614b\u8cc7\u6599\u9593\u7684\u76f8\u95dc\u6027\uff08\u8996\u89ba\u3001\u6587\u5b57\u3001\u76f8\u7247\u6a19\u8a3b\u8cc7\u6599\u7b49\uff09\uff0c\u5efa\u69cb\u8cc7\u6599\u9593\u7684\u95dc\u4fc2\u5716\uff0c\u4e26\u4ee5\u6b64\u4f86\u9a57\u8b49\u8cc7\u8a0a\u7684\u6b63\u78ba\u6027\uff0c\u4e5f\u662f\u591a\u5a92\u9ad4\u9451\u8b58\u7814\u7a76\uff08Multimedia Forensics\uff09\u4e2d\u9700\u8981\u7814\u7a76\u7e7c\u7e8c\u6311\u6230\u7684\u8ab2\u984c\u3002<\/p>\n<p>\u800c\u5176\u4ed6\u9632\u79a6\u65b9\u6cd5\u5982\u57fa\u65bc\u6df1\u5ea6\u5b78\u7fd2\u4e4b\u4e0d\u53ef\u8996\u6578\u4f4d\u6d6e\u6c34\u5370\uff0c\u5176\u53ef\u5d4c\u5165\u7684\u4fe1\u606f\u91cf\u4ecd\u6709\u9650\u5236\uff0c\u73fe\u884c\u7814\u7a76\u4e3b\u8981\u5d4c\u5165\u4e8c\u5143\u5b57\u4e32\uff0c\u4f46\u4e8c\u5143\u5b57\u4e32\u662f\u5426\u53ef\u4ee5\u8db3\u5920\u7576\u4f5c\u4f86\u6e90\u5f71\u7247\u8207\u5167\u5bb9\u64c1\u6709\u8005\u7684\u6191\u8b49\uff0c\u662f\u4e9f\u5f85\u89e3\u7b54\u7684\u554f\u984c\uff0c\u56e0\u6b64\uff0c\u7576\u52d9\u4e4b\u6025\u662f\u8981\u5982\u4f55\u6539\u9032\u67b6\u69cb\uff0c\u589e\u52a0\u53ef\u5d4c\u5165\u7684\u4fe1\u606f\u91cf\uff0c\u5982\u6b64\uff0c\u53ef\u4ee5\u8003\u616e\u9664\u4e86\u4e8c\u5143\u5b57\u4e32\u4ee5\u5916\u7684\u6191\u8b49\uff0c\u5982QR code\u3001\u6216\u6578\u4f4d\u5370\u7ae0\u7b49\u6191\u8b49\u3002\u6d6e\u6c34\u5370\u5c0d\u65bc\u4e0d\u540c\u5f71\u50cf\u64cd\u4f5c\u7684\u5f37\u5065\u6027\uff0c\u5c24\u5176\u662f\u672a\u77e5\u7684\u64cd\u4f5c\uff0c\u5927\u90e8\u5206\u6d6e\u6c34\u5370\u7d93\u904e\u64cd\u4f5c\u6703\u640d\u5931\u5927\u91cf\u8a0a\u606f\uff0c\u5982\u4f55\u5728\u4e0d\u540c\u5f71\u7247\u7de8\u8f2f\u64cd\u4f5c\u4e0b\uff0c\u4fdd\u5b58\u8db3\u5920\u8cc7\u8a0a\u4f9b\u4f86\u6e90\u8ffd\u8e64\u6216\u5167\u5bb9\u9a57\u8b49\uff0c\u4e5f\u662f\u4e00\u5927\u6311\u6230\u3002\u800c\u76ee\u524d\u6df1\u507d\u5167\u5bb9\uff0c\u5f71\u7247\u4f54\u5927\u5b97\uff0c\u57fa\u65bc\u6df1\u5ea6\u5b78\u7fd2\u4e4b\u6578\u4f4d\u6d6e\u6c34\u5370\u7814\u7a76\u4ecd\u4ee5\u5f71\u50cf\u70ba\u4e3b\uff0c\u5982\u4f55\u8a2d\u8a08\u5feb\u901f\u6709\u6548\u7684\u5f71\u7247\u6578\u4f4d\u6d6e\u6c34\u5370\uff0c\u4ecd\u662f\u4e00\u5927\u96e3\u984c\u3002\u540c\u6a23\u5730\uff0c\u76ee\u524d\u57fa\u65bc\u5c0d\u6297\u6a23\u672c\u7684\u9632\u79a6\u65b9\u6cd5\u4e3b\u8981\u4e5f\u4ecd\u662f\u4ee5\u55ae\u5f35\u5f71\u50cf\u70ba\u4e3b\uff0c\u5f71\u7247\u7684\u5c0d\u6297\u6a23\u672c\u9700\u8981\u8003\u616e\u5e40\u8207\u5e40\u4e4b\u524d\u7684\u9023\u7e8c\u6027\u8207\u4e00\u81f4\u6027\uff0c\u624d\u4e0d\u6703\u8b93\u6dfb\u52a0\u7684\u5c0d\u6297\u64fe\u52d5\u56b4\u91cd\u5f71\u97ff\u5f71\u7247\u539f\u4f86\u7684\u54c1\u8cea\uff0c\u4e26\u4fdd\u6301\u8db3\u5920\u7684\u653b\u64ca\u80fd\u529b\u8b93\u6df1\u507d\u751f\u6210\u6a21\u578b\u7121\u6548\uff0c\u9700\u8981\u66f4\u6df1\u5165\u7684\u7814\u7a76\u2027\u76ee\u524d\u6709\u7684\u653b\u64ca\u6a21\u578b\u4e3b\u8981\u4ecd\u662f\u91dd\u5c0d\u5df2\u77e5\u7684\u751f\u6210\u6a21\u578b\u9032\u884c\u767d\u76d2\u653b\u64ca\uff0c\u5c0d\u65bc\u672a\u77e5\u6a21\u578b\uff0c\u9700\u8981\u8a2d\u8a08\u6709\u6548\u7684\u9ed1\u76d2\u653b\u64ca\u6a21\u578b\uff0c\u5982\u4f55\u78ba\u4fdd\u5c0d\u6297\u6a23\u672c\u653b\u64ca\u7684\u53ef\u9077\u79fb\u6027\uff0c\u5247\u662f\u53e6\u5916\u4e00\u9805\u6311\u6230\u3002<\/p>\n<hr \/>\n<p><strong>\u53c3\u8003\u6587\u737b<\/strong><br \/>\n[News 2019-1]https:\/qz.com\/1699819\/a-new-kind-of-cybercrime-uses-ai-and-your-voice-against-you\/<br \/>\n[Yu et al. 2021]Yu, Ning, Vladislav Skripniuk, Sahar Abdelnabi, and Mario Fritz. \u201cArtificial fingerprinting for generative models: Rooting deepfake attribution in training data.\u201d In <em>IEEE\/CVF International Conference on Computer Vision (CVPR)<\/em>, pp. 14448-14457. 2021.<br \/>\n[Ruiz et al. 2020] Ruiz, Nataniel, Sarah Adel Bargal, and Stan Sclaroff. \u201cDisrupting deepfakes: Adversarial attacks against conditional image translation networks and facial manipulation systems.\u201d In <em>European Conference on Computer Vision (ECCV)<\/em>, pp. 236-251. Springer, Cham, 2020.<br \/>\n[Khalid et al. 2021] Khalid, Hasam, Shahroz Tariq, Minha Kim, and Simon S. Woo. \u201cFakeAVCeleb: A Novel Audio-Video Multimodal Deepfake Dataset.\u201d <em>arXiv preprint arXiv:2108.05080<\/em> (2021).<br \/>\n[Yeh et al. 2020] Yeh, Chin-Yuan, Hsi-Wen Chen, Shang-Lun Tsai, and Sheng-De Wang. \u201cDisrupting image-translation-based deepfake algorithms with adversarial attacks.\u201d In <em>IEEE\/CVF Winter Conference on Applications of Computer Vision Workshops (WACVW)<\/em>, pp. 53-62. 2020.<br \/>\n[Yeh et al. 2021] Yeh, Chin-Yuan, Hsi-Wen Chen, Hong-Han Shuai, De-Nian Yang, and Ming-Syan Chen. \u201cAttack as the Best Defense: Nullifying Image-to-image Translation GANs via Limit-aware Adversarial Attack.\u201d In <em>IEEE\/CVF International Conference on Computer Vision (ICCV)<\/em>, pp. 16188-16197. 2021.<br \/>\n[GoodFellow et al. 2014] Goodfellow, Ian J., Jonathon Shlens, and Christian Szegedy. \u201cExplaining and harnessing adversarial examples.\u201d arXiv preprint arXiv:1412.6572 (2014).<br \/>\n[Karras et al. 2019] Karras, Tero, Samuli Laine, and Timo Aila. \u201cA style-based generator architecture for generative adversarial networks.\u201d In <em>IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)<\/em>, pp. 4401-4410. 2019.<br \/>\n[Karras et al. 2021] Karras, Tero, Miika Aittala, Samuli Laine, Erik H\u00e4rk\u00f6nen, Janne Hellsten, Jaakko Lehtinen, and Timo Aila. \u201cAlias-free generative adversarial networks.\u201d In <em>Neural Information Processing Systems<\/em> (NeurIPS). 2021.<br \/>\n[R\u00f6ssler et al. 2019] Rossler, Andreas, Davide Cozzolino, Luisa Verdoliva, Christian Riess, Justus Thies, and Matthias Nie\u00dfner. \u201cFaceforensics++: Learning to detect manipulated facial images.\u201d In <em>IEEE\/CVF International Conference on Computer Vision<\/em> (ICCV), pp. 1-11. 2019.<br \/>\n[FaceApp 2021] https:\/www.faceapp.com\/<br \/>\n[DeepFaceLab, 2021] https:\/github.com\/iperov\/DeepFaceLab<br \/>\n[FaceSwap, 2021] https:\/faceswap.dev\/<br \/>\n[Chris Ume and Miles Fisher, 2021]https:\/www.today.com\/news\/man-tom-cruise-deepfakes-tiktok-speaks-ethics-technology-rcna10163<br \/>\n[Li et al. 2020] Li, Lingzhi, Jianmin Bao, Ting Zhang, Hao Yang, Dong Chen, Fang Wen, and Baining Guo. &#8220;Face x-ray for more general face forgery detection.&#8221; In <em>IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)<\/em>, pp. 5001-5010. 2020.<br \/>\n[Hui et al. 2022] Guo, Hui, Shu Hu, Xin Wang, Ming-Ching Chang, and Siwei Lyu. &#8220;Eyes Tell All: Irregular Pupil Shapes Reveal GAN-generated Faces.&#8221; In <em>International Conference on Acoustics, Speech, and Signal Processing (ICASSP)<\/em>, 2022.<br \/>\n[Park et al. 2019] Park, Taesung, Ming-Yu Liu, Ting-Chun Wang, and Jun-Yan Zhu. &#8220;GauGAN: semantic image synthesis with spatially adaptive normalization.&#8221; In <em>ACM SIGGRAPH 2019 Real-Time Live!<\/em>, pp. 1-1. 2019.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u6df1\u507d\u5167\u5bb9\uff08Deepfake\uff09 \u96a8\u8457\u8fd1\u5e74\u4f86\u6df1\u5ea6\u5b78\u7fd2\u6280\u8853\u8207\u76f8\u95dc\u751f\u6210\u6a21\u578b\u7684\u5feb\u901f\u767c\u5c55\uff0c\u591a\u5a92\u9ad4\uff08\u5305\u62ec\u5f71\u50cf\u3001\u8072\u97f3\u3001\u6587\u5b57\uff09\u5167 [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":27068,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_et_pb_use_builder":"","_et_pb_old_content":"","_et_gb_content_width":"","footnotes":""},"categories":[990,983],"tags":[],"acf":[],"_links":{"self":[{"href":"https:\/newsletter.sinica.edu.tw\/wp-json\/wp\/v2\/posts\/27065"}],"collection":[{"href":"https:\/newsletter.sinica.edu.tw\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/newsletter.sinica.edu.tw\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/newsletter.sinica.edu.tw\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/newsletter.sinica.edu.tw\/wp-json\/wp\/v2\/comments?post=27065"}],"version-history":[{"count":1,"href":"https:\/newsletter.sinica.edu.tw\/wp-json\/wp\/v2\/posts\/27065\/revisions"}],"predecessor-version":[{"id":27069,"href":"https:\/newsletter.sinica.edu.tw\/wp-json\/wp\/v2\/posts\/27065\/revisions\/27069"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/newsletter.sinica.edu.tw\/wp-json\/wp\/v2\/media\/27068"}],"wp:attachment":[{"href":"https:\/newsletter.sinica.edu.tw\/wp-json\/wp\/v2\/media?parent=27065"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/newsletter.sinica.edu.tw\/wp-json\/wp\/v2\/categories?post=27065"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/newsletter.sinica.edu.tw\/wp-json\/wp\/v2\/tags?post=27065"}],"curies":[{"name":"wp","href":"https:\/api.w.org\/{rel}","templated":true}]}}