Steganography is typically used by law enforcement agencies to prevent unauthorized persons from becoming aware of the existence of a message communicated by military or other government organizations outside their network. Illegal uses of steganography such as fraud, gambling, criminal communications, hacking, electronic payments, harassment, offenses on intellectual property and viruses pose a great threat to society. Such illicit steganographers communicate with each other through stego files to exchange their plan without getting noticed by law enforcement. This paper presents a novel Deep Clustering Network for Steganographer Detection (DCNSD) based on convolutional autoencoders and a clustering model for identifying such steganographers since plenty of digital images are transferred over the internet that could carry hidden secret messages. Mostly the existing techniques involving deep learning networks for steganographer detection involves supervised learning approach which makes them unsuitable for real-world deployment. The foremost characteristic of this proposed network lies in its ability to segregate images transmitted from a steganographer from those innocent users’ images in an unsupervised approach. Thereby making the proposed DCNSD system plausible for real-world deployment. Based on the experimental results, it is shown that the proposed DCNSD framework excels in detecting steganographers who use content-adaptive steganography to embed secrets with 100% accuracy.

隐写术通常由执法机构使用，以防止未经授权的人意识到军事或其他政府组织在其网络之外传达的消息的存在。欺诈、赌博、犯罪通信、黑客攻击、电子支付、骚扰、知识产权犯罪和病毒等非法使用隐写术对社会构成巨大威胁。这些非法隐写术者通过隐写文件相互交流，以交换他们的计划，而不会被执法部门注意到。本文提出了一种新颖的基于卷积自动编码器的用于隐写器检测的深度聚类网络 (DCNSD) 和用于识别此类隐写器的聚类模型，因为大量的数字图像通过互联网传输，可能携带隐藏的秘密信息。大多数涉及用于隐写器检测的深度学习网络的现有技术都涉及监督学习方法，这使得它们不适合实际部署。这个提议的网络的最重要特征在于它能够以无监督的方法将隐写器传输的图像与那些无辜用户的图像分离。从而使提议的 DCNSD 系统在实际部署中是合理的。基于实验结果，表明所提出的 DCNSD 框架在检测使用内容自适应隐写术以 100% 准确率嵌入秘密的隐写术者方面表现出色。这个提议的网络的最重要特征在于它能够以无监督的方法将隐写器传输的图像与那些无辜用户的图像分离。从而使提议的 DCNSD 系统在实际部署中是合理的。基于实验结果，表明所提出的 DCNSD 框架在检测使用内容自适应隐写术以 100% 准确率嵌入秘密的隐写术者方面表现出色。这个提议的网络的最重要特征在于它能够以无监督的方法将隐写器传输的图像与那些无辜用户的图像分离。从而使提议的 DCNSD 系统在实际部署中是合理的。基于实验结果，表明所提出的 DCNSD 框架在检测使用内容自适应隐写术以 100% 准确率嵌入秘密的隐写术者方面表现出色。