The document discusses and compares different steganographic algorithms and steganalysis techniques. It defines steganography and steganalysis, describing various steganographic schemes like LSB embedding, Outguess, F5, and Model-based steganography. It also covers past and modern work in steganalysis, including statistical methods for detecting hidden messages. The document concludes by discussing the future of steganography and its potential limitations under laws.

1. PERFORMANCE EVALUATION ON
DIFFERENT STEGNOGRAPHIC
ALGORITHMS
JAYESH S, AP , Archana College Of Engineering – ALAPPUZHA
AJAL.A.J , ASSISTANT PROFESSOR , FISAT – KOCHI
VINOTHKUMAR.S , Scholar at PRIST University, Thanjavur
HRIDYA K S - A P , K R G C E W – ALAPPUZHA

2. http://edition.cnn.com/video/?/video/world/2012/04/30/pkg-robertson-al-qaeda-documen

3. http://www.usatoday.com/tech/news/2001-02-05-binladen.htm

4. Contents
Steganography and Steganalysis
Steganographic schemes
System Features
Improvement / Comparison
Conclusion and Future Work

5. What is Steganography?
 Origin of the term: steganos: secret – graphy:
writing

6. Steganalysis
♦ Passive steganalysis
– detect the presence or absence of a message
♦ Active Steganalysis
– Estimate the message length and location
– Estimate the Secret Key in embedding
– Extract the message
crypto + graphy ( secret + writing )
stegano + graphy ( cover + writing )

7. Types of Steganalysis
 Targeted Steganalysis
 Relys on knowing the method used to hide the data & using
known distinguishing statistics to detect stego images
 Sometimes steganalysts reverse engineer steganographic
methods
 Blind Steganalysis
 Most beneficial to forensics because it’s not based on
knowing the algorithm
 Most difficult because the type of images and method of
hiding data are enormous and continuously changing.
 The current trend is to develop a neural network using
training images and multiple statistical features. A method
beyond the scope of this talk.

8. Other previous work
in steganalysis
 Provos analyzed two million eBay images (jpeg) but although he
identified thousands of “suspicious” images, nothing conclusive was
recovered from any of them
 A statistical method based on pairs of values (POVs) was
introduced by Pfitzmann and Westfeld, providing very reliable
results if the message was placed in sequential pixel locations in the
image
 Fridrich et al has a statistical method called RS steganalysis for
detection of LSB embedding
 It uses dual statistics derived from spatial correlations in an image
 In a typical cover image the LSB plane can (to some degree) be
predicted from the remaining 7 bit planes
 This intuitive idea is formulated mathematically resulting in the RS
method
 The safe-bit rate for the LSB embedding algorithms is less than

9. Modern Stego Techniques
Outguess
 Stego framework is created by embedding
hidden data using redundancy of cover image.
 Outguess preserves statistics of the BDCT
coefficients histogram
 Stego takes two measures before embedding
data
- Redundant BDCT coefficients, which has least
effect on cover image.
- Adjusts the untouched coefficients.
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10. Modern Stego Techniques (cont’d.)
F5
• Works on JPEG format only.
• Two main security actions against steganalysis
attacks:
- Straddling: scatters message uniformly over
the cover
image
- Matrix Embedding: Improves embedding
efficiency (no. of bits/ change of BDCT coeff.)
10

11. Modern Stego Techniques (cont’d.)
MB (Model-based Steganography)
• Correlates embedded data with cover
image
• Splits cover image into two parts
- Models parameter of distribution of second given first
part
- Encodes second part using model and hidden message
- Combine these two parts to form stego image
• MB1 operates on JPEG images, uses Cauchy
distribution to model JPEG histogram
11

12. Future of Steganography
 The most important use of
steganographic techniques will
probably lie in the field of digital
watermarking
 Might become limited under laws -
governments claimed that
criminals use steganography to
communicate
...the End