Stegnography

Course Overview:

Steganography is the art and science of hiding information within other seemingly harmless data. This course provides hands-on training in traditional and digital steganography techniques, using images, audio, video, and network protocols to hide information securely. By the end of this course, you’ll be able to implement and detect steganographic techniques in real-world scenarios.

Duration: 4–6 weeks (Self-paced or instructor-led)

Prerequisites:

• Basic understanding of computer science
• Familiarity with Python (for hands-on sessions)
• Introductory knowledge of cybersecurity is helpful

Course Structure

Module 1: Introduction to Steganography

• What is steganography?
• Steganography vs Cryptography
• History and evolution of steganography
• Use cases: From ancient times to cybersecurity

Module 2: Fundamentals of Digital Steganography

• Data representation: Bits, bytes, and encoding
• Cover mediums: Images, audio, video, and text
• LSB (Least Significant Bit) method
• Compression and file formats (PNG vs JPG, WAV vs MP3)

Module 3: Image-Based Steganography

• RGB pixels and LSB modification
• Hands-on: Hide and extract messages in PNG images
• Tools: Steghide, OpenStego, Python PIL and OpenCV
• Detection techniques (Steganalysis basics)

Module 4: Audio and Video Steganography

• Audio file structures (WAV vs MP3)
• Echo hiding and phase coding techniques
• Video steganography using frame-by-frame encoding
• Tools and libraries: FFmpeg, Audacity, PyDub

Module 5: Text and Network Steganography

• Whitespace manipulation
• Unicode steganography
• Hiding data in HTTP headers, DNS requests, TCP/IP packets
• Covert channels and tunneling techniques

Module 6: Steganography with Python

• Building a simple image steganography tool (hands-on project)
• Using Pillow, NumPy, wave, opencv-python
• Encrypting messages before embedding
• Creating a command-line interface

Module 7: Detection & Counter-Steganography (Steganalysis)

• Steganalysis tools and techniques
• Signature detection
• Statistical analysis
• AI/ML approaches to steganography detection

Module 8: Legal, Ethical, and Real-World Use Cases

• Ethical use of steganography
• Cybercrime and anti-forensic techniques
• Real-world cases (espionage, journalism, malware)
• Legal implications