Kramer Robin S S, Mireku Michael O, Flack Tessa R, Ritchie Kay L
School of Psychology, University of Lincoln, Lincoln, LN6 7TS, UK.
Cogn Res Princ Implic. 2019 Jul 29;4(1):28. doi: 10.1186/s41235-019-0181-4.
In recent years, fraudsters have begun to use readily accessible digital manipulation techniques in order to carry out face morphing attacks. By submitting a morph image (a 50/50 average of two people's faces) for inclusion in an official document such as a passport, it might be possible that both people sufficiently resemble the morph that they are each able to use the resulting genuine ID document. Limited research with low-quality morphs has shown that human detection rates were poor but that training methods can improve performance. Here, we investigate human and computer performance with high-quality morphs, comparable with those expected to be used by criminals.
Over four experiments, we found that people were highly error-prone when detecting morphs and that training did not produce improvements. In a live matching task, morphs were accepted at levels suggesting they represent a significant concern for security agencies and detection was again error-prone. Finally, we found that a simple computer model outperformed our human participants.
Taken together, these results reinforce the idea that advanced computational techniques could prove more reliable than training people when fighting these types of morphing attacks. Our findings have important implications for security authorities worldwide.
近年来，欺诈者开始使用容易获取的数字处理技术来实施面部变形攻击。通过提交一张变形图像（两张人脸各占50%的平均图像）以纳入护照等官方文件，有可能这两个人都与变形后的图像足够相似，以至于他们都能够使用由此生成的真实身份证件。对低质量变形图像的有限研究表明，人工检测率很低，但训练方法可以提高检测性能。在此，我们研究了高质量变形图像的人工和计算机检测性能，这些图像与犯罪分子可能使用的图像相当。
在四项实验中，我们发现人们在检测变形图像时极易出错，而且训练并没有带来改进。在现场匹配任务中，变形图像被接受的程度表明它们对安全机构构成了重大担忧，而且检测再次容易出错。最后，我们发现一个简单的计算机模型的表现优于我们的人类参与者。
综上所述，这些结果强化了这样一种观点，即在对抗这类变形攻击时，先进的计算技术可能比训练人员更可靠。我们的研究结果对全球安全当局具有重要意义。
