1.3.1 Compression, encryption and hashing

• What is the primary difference between lossy and lossless compression?

  Data restoration
• Encryption converts data into a form that is unreadable without the correct key
• Hashing converts data into a fixed-length output called a hash value
• Hashing is the process of converting data into a fixed-length, unique output called a hash value or hash code.
• Hashing is reversible, unlike encryption.

  False
• Match the compression type with its characteristic:

  Lossless compression ↔️ No data loss

  Lossy compression ↔️ Higher compression ratio
• Lossy compression allows for full restoration of the original data.

  False
• MP3 audio is an example of lossy compression.
• The LZW compression algorithm replaces repeated strings of characters with a single code
• The LZW algorithm exploits patterns in data to achieve compression
• Integrity in encryption prevents data from being altered or tampered
• Lossy compression achieves greater compression ratios by removing some data.


  True
• Steps in the Huffman Coding algorithm

  1️⃣ Calculate frequency of characters

  2️⃣ Build a binary tree

  3️⃣ Assign codes based on tree structure
• What is the role of Predictive Coding in lossy compression?

  Encode the difference between samples
• The purpose of encryption that ensures only authorized parties can access and read the data is called confidentiality
• Asymmetric encryption is faster than symmetric encryption.

  False
• Hashing is reversible like encryption.

  False
• How does hashing ensure data integrity?

  Compares hash values
• Lossless compression reduces data size without losing any information
• Lossless compression reduces data size without losing any information
• Lossy compression achieves higher compression ratios by removing some data
• What is Transform Coding used in lossy compression?

  Discrete Cosine Transform
• Match the type of encryption with its key management method:

  Symmetric Encryption ↔️ Single shared key

  Asymmetric Encryption ↔️ Public and private key pair
• Hashing is reversible, unlike encryption

  False
• Hash functions are one-way, meaning it is computationally infeasible to recover the original input from the hash value.
• Data indexing using hashing can suffer from hash collisions.
• Symmetric encryption uses a single shared key for both encryption and decryption.
• One key property of hash functions is that they are collision-resistant.
• What is the primary purpose of data compression?

  Reduce storage space
• Match the compression type with its characteristic:

  Lossless ↔️ No information loss

  Lossy ↔️ Information loss
• Steps in transform coding as used in lossy compression:

  1️⃣ Convert signal into a different domain

  2️⃣ Discard high-frequency components
• Transform Coding is an example of a lossy compression algorithm.


  True
• Match the compression type with its characteristic:

  Lossless ↔️ Fully restores original data

  Lossy ↔️ Removes some data permanently
• What does authentication in encryption verify?

  Identity of the sender
• What happens to data in lossless compression?

  Data can be perfectly reconstructed
• What is the primary purpose of the LZW algorithm in lossless compression?

  Exploit patterns in data
• What is the integrity purpose in encryption?

  Prevent data tampering
• Encryption is essential for securing financial transactions and personal data.


  True
• Hashing converts data into a fixed-length, unique output called a hash value
• Match the characteristic with the corresponding process:

  Hashing ↔️ One-way, not reversible

  Encryption ↔️ Reversible with the correct key