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answer Question 3 3. Consider the following Substitution Box (Sbox) which maps a...

May 20, 2024

answer Question 3

Sure, let's break down the questions and provide the answers accordingly. Question 3 (i) State the linear expression that you used to approximate the first Sbox. The linear expression for approximating the first Sbox can be derived from the Linear Approximation Table. We need to find the most significant bias in the table for the first Sbox. From the Linear Approximation Table, the highest bias for the first Sbox is found at the intersection of X=0 and Y=F, which is +8. So, the linear expression for the first Sbox is:

P_1 \oplus P_2 \oplus P_3 \oplus P_4 = U_1 \oplus U_2 \oplus U_3 \oplus U_4

Question 3 (ii) State the linear expression that you used to approximate the second Sbox. Similarly, for the second Sbox, we look for the highest bias in the Linear Approximation Table. The highest bias for the second Sbox is also found at the intersection of X=0 and Y=F, which is +8. So, the linear expression for the second Sbox is:

U_1 \oplus U_2 \oplus U_3 \oplus U_4 = C_1 \oplus C_2 \oplus C_3 \oplus C_4

Question 3 (iii) State the overall approximation from the plaintext P to the intermediate ciphertext U and the various K values. Combining the linear expressions from the first and second Sboxes, we get the overall approximation:

P_1 \oplus P_2 \oplus P_3 \oplus P_4 = C_1 \oplus C_2 \oplus C_3 \oplus C_4

Question 3 (iv) State Matsui's Lemma. Then, using Matsui's Lemma, calculate the probability with which your overall approximation holds.Matsui's Lemma: Matsui's Lemma states that if a linear approximation holds with a bias of

\epsilon

, then the probability that the approximation holds is given by:

P = \frac{1}{2} + \epsilon

Using the highest bias from the Linear Approximation Table, which is +8, we can calculate the probability:

\epsilon = \frac{8}{16} = 0.5

P = \frac{1}{2} + 0.5 = 1

So, the probability with which the overall approximation holds is 1. Summary of Answers

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Sure, let's break down and answer each part of the question from the exam paper on Digital Forensics and Anti-Forensics. 4. Digital Forensics and Anti-Forensics # a) Steganography and Other Anti-Forensic Techniques (i) Explain briefly what steganography is. Provide a diagram illustrating the agents who participate in a steganographic system. Include those who seek to communicate using the steganographic channel and those who seek to compromise such communications. Identify also the processing carried out by agents and the inputs to such processes.

Key Concept

Steganography

Explanation

Steganography is the practice of hiding information within other non-secret text or data. The agents involved include the sender, receiver, and adversary. The sender embeds the secret message into a cover medium (e.g., image, audio), and the receiver extracts it. The adversary attempts to detect or alter the hidden message.

(ii) Outline how Least Significant Bit (LSB) steganography works. Assume that relevant images are grayscale with pixel values in the range 0...255.

Key Concept

LSB Steganography

Explanation

LSB steganography involves modifying the least significant bits of pixel values in a grayscale image to embed secret data. For example, if a pixel value is 100 (binary 01100100), changing the least significant bit to 1 would make it 101 (binary 01100101).

(iii) One of the goals of an adversary is to detect the use of steganography. State whether you think the use of LSB steganography is easily detected or not and whether the number of least significant bits used by an LSB scheme (e.g., single least significant bit or least significant 2 bits) affects detectability. Justify your answers.

Key Concept

Detectability of LSB Steganography

Explanation

The use of LSB steganography can be detected through statistical analysis. The more bits used (e.g., 2 LSBs vs. 1 LSB), the easier it is to detect because it introduces more noticeable changes in the image's statistical properties.

(iv) Steganography can be regarded as an anti-forensics technique. Briefly outline 3 other anti-forensic techniques.

Key Concept

Anti-Forensic Techniques

Explanation

Three other anti-forensic techniques include data wiping (securely deleting data), file obfuscation (renaming or altering file headers), and encryption (making data unreadable without a key).

# b) Camera Forensics (i) Briefly explain what is meant by source classification, device identification, and device linking.

Key Concept

Camera Forensics

Explanation

Source classification involves determining the type of device used to capture an image. Device identification is pinpointing the exact device. Device linking connects multiple images to the same device.

(ii) Outline one technical means of identifying the use of a specific camera.

Key Concept

Technical Means of Camera Identification

Explanation

One method is analyzing the sensor pattern noise (SPN) unique to each camera sensor, which acts like a fingerprint.

# c) Traffic Analysis (i) An operational military unit communicates via a radio frequency multi-hop network. Explain how traffic analysis can be used to gain information on the network. Identify clearly what information can be gained in this way.

Key Concept

Traffic Analysis

Explanation

Traffic analysis involves monitoring and analyzing communication patterns to infer information such as network topology, node roles, and communication frequency. This can reveal critical nodes and potential vulnerabilities.

(ii) Briefly outline one technical means of identifying the use of a specific camera.

Key Concept

Technical Means of Camera Identification

Explanation

As mentioned earlier, sensor pattern noise (SPN) can be used to identify a specific camera. This noise pattern is unique to each camera sensor and can be extracted from images.

I hope this helps you understand and answer the various parts of the question!

answer Question 5