Deepfake and Image Forgery Detection: Cybersecurity, Multimedia Forensics, Image Manipulation

When an image or video becomes evidence, the question is not simply whether it looks convincing. It is how to examine its content, context, technical traces, and possible history of manipulation. Deepfake and Image Forgery Detection brings those lines of inquiry together, tracing the subject from foundational forensic principles to authentication methods and the legal and ethical questions that follow.

From image manipulation to forensic examination

Chad R. Johnson begins with the changing landscape of deepfakes and image forgeries, including their effects on public trust, security, journalism, and other areas of society. The book then develops the principles of multimedia forensics and surveys how images can be altered—an important foundation for understanding what signs of manipulation may mean.

Read the evidence from more than one angle

The chapters cover image-authentication methods, contextual analysis, feature extraction, compression and encoding, and sensor and optical signatures. Motion and temporal analysis extends the discussion to video, while learned detection and hybrid systems introduce approaches that combine automated methods with other forms of examination. Taken together, these topics frame detection as a process of weighing different kinds of evidence rather than relying on one clue alone.

For practice, research, and responsible interpretation

Best practices and forensic procedure sit alongside coverage of legal and ethical considerations. This wider perspective matters: conclusions about an image can affect investigations, institutions, and the people depicted. A case-report template, glossary, sources, and index support reference and practical use.

Who may find it useful

The book is aimed at readers concerned with digital and multimedia forensics, cybersecurity, image authentication, and the integrity of digital evidence. Its broad structure can also help students and researchers see how technical detection methods connect with the context in which evidence is created and assessed.

For a subject where techniques keep changing, Johnson offers a structured route through the evidence, the methods used to evaluate it, and the responsibilities that come with interpreting it.