目的 数字图像的真实性问题备受人们关注，被动取证是解决该问题的有效途径。然而，如果伪造者在篡改图像的同时利用反取证技术对篡改的痕迹进行消除或伪造，那么已有的大量被动取证技术都将失效。回顾图像反取证技术的研究现状（包括兴起原因、实现原理、技术特点以及应用前景），并根据已有文献总结反取证技术面临的主要挑战和机遇。方法 由于现有的被动取证技术大都基于遗留痕迹和固有特征的异同来辨识图像真伪，因此本文以不同的取证特征为线索来评述和比较反取证技术的原理和策略。结果 根据取证特征的不同，将反取证技术归纳为遗留痕迹隐藏、固有特征伪造和反取证检测等三类，并展示了当前各类反取证技术面临的难点和挑战。结论 对数字图像反取证技术进行总结和展望，并指出其算法未来在通用性、安全性、可靠性等方面将有待进一步的深入研究。

Objective At present, digital images are suffering a serious credibility crisis. While existing passive forensic techniques are able to successfully detect multiple types of standard image manipulations, many forensic techniques do not account for the possibility that a forger with advanced knowledge of signal processing techniques may attempt to disguise their forgery. As a result, researchers have begun studying anti-forensic operations that are capable of deceiving forensic techniques. This study attempts to review the state-of-the-art image anti-forensic techniques (including rising reasons, implementation principles, technical characteristics, and application prospects) and summarizes the challenges and opportunities associated with anti-forensic techniques.Method Most studies on passive forensic techniques in image forgeries have focused on identifying different tampered traces and inherent characteristics. The present study examines different characteristics to review and compare previous studies on image anti-forensic techniques. Result Based on different forensic characteristics, the anti-forensic techniques of digital images are summarized as three research topics:hiding left traces, inherent characteristic forgery, and anti-forensic detection. The related research progress and challenges are surveyed according to different characteristics. Conclusion Main problems in the current research on image anti-forensic techniques were pointed out, and further research directions are presented.