पीबीकेएस बनाम DC
Let's break down the comparison between PBKDF2 and bcrypt in detail, covering the strengths and weaknesses of each, along with examples and practical applications.
Salting: Adding a unique, random value (the salt) to each password before hashing. This prevents attackers from using pre-computed rainbow tables.
Key Stretching: Repeatedly hashing the password (and salt) many times. This increases the computational cost of each password attempt, slowing down attackers significantly.
1. Input: Password (P), Salt (S), Iteration Count (c), Key Length (dkLen), Pseudorandom Function (PRF, usually HMAC).
2. Pre-processing: The salt is usually prepended or appended to the password.
3. Iteration: The core of PBKDF2 involves repeatedly applying the PRF to the password and salt, with the output of each iteration feeding back into the next. The number of iterations is crucial.
4. Output: A derived key of the specified length (dkLen). This is the "hashed" password.
```python
import hashlib
import hmac
def pbkdf2(password, salt, iterations, dklen, prf = "sha256"):
"""Simple conceptual PBKDF2 implementation (for illustration ONLY,
DO NOT use in production)."""
password = password.encode('utf-8') # Encode to bytes
salt = salt.encode('utf-8')
def f(i): #Inner function
u = hmac.new(hashlib.new(prf, password).digest(), salt + i.to_bytes(4, 'big'), hashlib.new).digest()
t = u
for j in range(1, iterations):
u = hmac.new(hashlib.new(prf, password).digest(), u, hashlib.new).digest()
t = bytes(a ^ b for a, b in zip(t, u)) # XOR bytes
return t
l = (dklen + hashlib.new(prf).digest_size - 1) // hashlib.new(prf).digest_size
dk = b''
for i in range(1, l + 1):
dk += f(i)
return dk[:dklen] #truncate
#Example Usage
password = "mysecretpassword"
salt = "somesaltvalue"
iterations = 100000
dklen = 32 # 256-bit key
derived_key = pbkdf2(password, salt, iterations, dklen, "sha256")
print(derived_key.hex())
```
Important: This is a simplified example for understanding. Use a well-vetted library in production (like `hashlib.pbkdf2_hmac` in Python).
1. Salting: The salt is unique per password. This means even if two users have the same password, their hashed passwords will be different, defeating rainbow table attacks.
2. Iteration Count: The repeated hashing (key stretching) dramatically increases the time it takes to crack the password. If it takes 1 millisecond to hash a password once, and you use 100,000 iterations, it takes 100 seconds. Attackers need to perform this calculation for every password they try.
3. HMAC (or other PRF): The pseudorandom function ensures that the output appears random and unpredictable, even if the input has some patterns. HMAC (Hash-based Message Authentication Code) is commonly used because it's well-understood and relatively fast.
Password Storage: The most common use case. Store the salt and the derived key (hashed password) in the database, not the original password.
Key Derivation: Generate cryptographic keys from user-supplied passwords or passphrases. This is useful for encrypting data on a device.
Creating Master Keys: Derive a master key from a password that can then be used to encrypt other keys.
Standardized: PBKDF2 is defined in RFC 2898 and is widely supported in many programming languages and libraries.
Configurable: You can adjust the iteration count and key length to control the security level and computational cost.
Relatively Fast (for password hashing): While deliberately slow compared to simple hashing, it can be tuned for performance.
HMAC-based: HMAC provides a strong foundation for the pseudorandom function.
Susceptible to Parallelization (to some extent): Attackers can potentially use multiple processors or GPUs to speed up the cracking process, although the iteration count helps mitigate this. Modern algorithms like Argon2 are designed to be memory-hard, making parallelization more difficult.
Relies on CPU (mostly): Its security depends primarily on CPU processing power. Attackers with specialized hardware (like ASICs) might gain an advantage.
Needs Proper Parameter Selection: If the salt is too short, or the iteration count is too low, the password is still vulnerable.
Not as Memory-Hard as Newer Alternatives: PBKDF2 has relatively low memory requirements compared to bcrypt or Argon2. This makes it easier for attackers to use massive amounts of memory to speed up their attacks.
Salting: Uses a salt value to randomize the hashing process.
Key Stretching (Work Factor): Has a built-in work factor (cost parameter) that controls the number of rounds of Blowfish encryption. This significantly increases the time required to hash a password.
Adaptive Hashing: bcrypt's design makes it more difficult to parallelize attacks efficiently.
1. Input: Password (P), Salt (S), Cost Parameter (work factor).
2. Salt Encoding: The salt is encoded into the hashed password string itself.
3. Key Expansion: The password and salt are expanded into a key schedule used by the Blowfish cipher.
4. Blowfish Encryption: The expanded key is used to repeatedly encrypt a fixed string (or a series of strings) using the Blowfish block cipher. The number of rounds is determined by the work factor.
5. Output: A string containing the salt, work factor, and the final encrypted output (the hashed password).
```python
# This is a highly simplified and incomplete illustration.
# DO NOT use this in production!
import bcrypt # Requires the 'bcrypt' package (pip install bcrypt)
password = "mysecretpassword"
salt = bcrypt.gensalt() # Generates a random salt
hashed_password = bcrypt.hashpw(password.encode('utf-8'), salt)
print(f"Hashed password: {hashed_password.decode('utf-8')}")
#To verify:
password_to_check = "mysecretpassword"
if bcrypt.checkpw(password_to_check.encode('utf-8'), hashed_password):
print("Password matches!")
else:
print("Password does NOT match.")
#Example using a cost factor of 12:
salt = bcrypt.gensalt(rounds=12)
hashed_password = bcrypt.hashpw(password.encode('utf-8'), salt)
print(f"Hashed password (cost 12): {hashed_password.decode('utf-8')}")
```
Important: Always use a dedicated bcrypt library (like the one in the example) for proper implementation and security. Don't try to roll your own!
1. Salting: Prevents rainbow table attacks. The salt is stored alongside the hashed password, so it's always available for verification.
2. Work Factor (Cost Parameter): The work factor directly controls the computational cost. Each increment doubles the amount of time required to compute the hash. This makes brute-force attacks significantly slower.
3. Blowfish Encryption: The use of a well-established block cipher (Blowfish) provides a secure foundation for the hashing process.
4. Adaptive Design: The way bcrypt uses Blowfish makes it harder to parallelize efficiently. This means that attackers can't simply throw more hardware at the problem to crack passwords faster.
Password Storage: The primary and intended use case. It's considered a very good choice for storing user passwords.
Other Security-Sensitive Applications: Can be used in other situations where a computationally expensive and secure hashing function is required.
Strong Security: Generally considered a very secure password hashing algorithm.
Adaptive: Designed to be resistant to parallel attacks.
Automatic Salting: Handles salt generation and storage automatically.
Widely Available: Implementations are available in many programming languages.
Good Reputation: Has a solid track record and is well-respected in the security community.
Blowfish Vulnerabilities (Theoretical): While not directly impacting password hashing with bcrypt, there have been theoretical attacks against Blowfish in other contexts. This is one reason why newer algorithms like Argon2 are being considered.
Slower than PBKDF2 (with low iteration count): For very low work factors, bcrypt might be faster than PBKDF2 with a low iteration count. But for comparable security levels (modern recommended iteration counts), bcrypt can be slower. Speed is relative and depends on the parameters.
Memory Usage: Uses more memory than a simply hashed password, though this is generally not a significant concern on modern systems.
Work Factor Adjustment: Increasing the work factor to increase security is more disruptive. It requires re-hashing all stored passwords, which might be complicated in practice. With PBKDF2, you can adjust iteration count and re-hash.
| Feature | PBKDF2 | bcrypt |
|--------------------|---------------------------------------------|-----------------------------------------------|
| Underlying Algorithm | HMAC (usually based on SHA-256 or SHA-512) | Modified Blowfish block cipher |
| Salting | Requires explicit salt generation and passing | Handles salt generation and storage internally |
| Key Stretching | Achieved through iteration count | Achieved through the work factor (cost) |
| Parallelization Resistance | Lower | Higher |
| Memory Hardness| Low | Low |
| Configuration | Iteration count, salt length, key length | Work factor |
| Standardization | Defined in RFC 2898 | No formal standard, but widely implemented |
| Speed | Can be tuned for performance; depends on iteration count | Generally slower than PBKDF2 (with low iteration count), comparable speed depending on the implementation.
| Security | Good, if iteration count is sufficiently high | Very good |
| Code Complexity| Can be implemented from scratch (but avoid) | Requires a dedicated library |
| Upgrading | Changing iteration count during upgrade is easier | Changing work factor needs re-hashing all passwords|
Both PBKDF2 and bcrypt are significantly better than simple hashing algorithms like MD5 or SHA-1 for password storage. bcrypt offers stronger protection against parallel attacks and handles salt generation automatically. PBKDF2 is more configurable and standardized. Argon2 is emerging as the new standard due to its memory hardness and resistance to side channel attacks. Always use a robust and well-maintained library for implementation and keep your parameters updated as hardware capabilities evolve. Password security is an ongoing process, not a one-time event.
PBKDF2 (Password-Based Key Derivation Function 2)
Definition: PBKDF2 is a key derivation function. It's not a hashing algorithm in the strictest sense, but it's often used for password hashing. It uses a pseudorandom function (typically HMAC) to repeatedly hash the password along with a salt. The repetition (iteration count) is a critical parameter that determines the computational cost.
Purpose: To strengthen password security by making it harder for attackers to crack passwords through brute-force or dictionary attacks. It achieves this by:
Salting: Adding a unique, random value (the salt) to each password before hashing. This prevents attackers from using pre-computed rainbow tables.
Key Stretching: Repeatedly hashing the password (and salt) many times. This increases the computational cost of each password attempt, slowing down attackers significantly.
Algorithm:
1. Input: Password (P), Salt (S), Iteration Count (c), Key Length (dkLen), Pseudorandom Function (PRF, usually HMAC).
2. Pre-processing: The salt is usually prepended or appended to the password.
3. Iteration: The core of PBKDF2 involves repeatedly applying the PRF to the password and salt, with the output of each iteration feeding back into the next. The number of iterations is crucial.
4. Output: A derived key of the specified length (dkLen). This is the "hashed" password.
Example (Conceptual):
```python
import hashlib
import hmac
def pbkdf2(password, salt, iterations, dklen, prf = "sha256"):
"""Simple conceptual PBKDF2 implementation (for illustration ONLY,
DO NOT use in production)."""
password = password.encode('utf-8') # Encode to bytes
salt = salt.encode('utf-8')
def f(i): #Inner function
u = hmac.new(hashlib.new(prf, password).digest(), salt + i.to_bytes(4, 'big'), hashlib.new).digest()
t = u
for j in range(1, iterations):
u = hmac.new(hashlib.new(prf, password).digest(), u, hashlib.new).digest()
t = bytes(a ^ b for a, b in zip(t, u)) # XOR bytes
return t
l = (dklen + hashlib.new(prf).digest_size - 1) // hashlib.new(prf).digest_size
dk = b''
for i in range(1, l + 1):
dk += f(i)
return dk[:dklen] #truncate
#Example Usage
password = "mysecretpassword"
salt = "somesaltvalue"
iterations = 100000
dklen = 32 # 256-bit key
derived_key = pbkdf2(password, salt, iterations, dklen, "sha256")
print(derived_key.hex())
```
Important: This is a simplified example for understanding. Use a well-vetted library in production (like `hashlib.pbkdf2_hmac` in Python).
Step-by-Step Reasoning (Why it works):
1. Salting: The salt is unique per password. This means even if two users have the same password, their hashed passwords will be different, defeating rainbow table attacks.
2. Iteration Count: The repeated hashing (key stretching) dramatically increases the time it takes to crack the password. If it takes 1 millisecond to hash a password once, and you use 100,000 iterations, it takes 100 seconds. Attackers need to perform this calculation for every password they try.
3. HMAC (or other PRF): The pseudorandom function ensures that the output appears random and unpredictable, even if the input has some patterns. HMAC (Hash-based Message Authentication Code) is commonly used because it's well-understood and relatively fast.
Practical Applications:
Password Storage: The most common use case. Store the salt and the derived key (hashed password) in the database, not the original password.
Key Derivation: Generate cryptographic keys from user-supplied passwords or passphrases. This is useful for encrypting data on a device.
Creating Master Keys: Derive a master key from a password that can then be used to encrypt other keys.
Pros:
Standardized: PBKDF2 is defined in RFC 2898 and is widely supported in many programming languages and libraries.
Configurable: You can adjust the iteration count and key length to control the security level and computational cost.
Relatively Fast (for password hashing): While deliberately slow compared to simple hashing, it can be tuned for performance.
HMAC-based: HMAC provides a strong foundation for the pseudorandom function.
Cons:
Susceptible to Parallelization (to some extent): Attackers can potentially use multiple processors or GPUs to speed up the cracking process, although the iteration count helps mitigate this. Modern algorithms like Argon2 are designed to be memory-hard, making parallelization more difficult.
Relies on CPU (mostly): Its security depends primarily on CPU processing power. Attackers with specialized hardware (like ASICs) might gain an advantage.
Needs Proper Parameter Selection: If the salt is too short, or the iteration count is too low, the password is still vulnerable.
Not as Memory-Hard as Newer Alternatives: PBKDF2 has relatively low memory requirements compared to bcrypt or Argon2. This makes it easier for attackers to use massive amounts of memory to speed up their attacks.
bcrypt
Definition: bcrypt is a password hashing function based on the Blowfish block cipher. It's specifically designed for password storage and is more resistant to brute-force attacks than simple hashing algorithms.
Purpose: Similar to PBKDF2, bcrypt's goal is to make password cracking computationally expensive. It achieves this through:
Salting: Uses a salt value to randomize the hashing process.
Key Stretching (Work Factor): Has a built-in work factor (cost parameter) that controls the number of rounds of Blowfish encryption. This significantly increases the time required to hash a password.
Adaptive Hashing: bcrypt's design makes it more difficult to parallelize attacks efficiently.
Algorithm (Simplified):
1. Input: Password (P), Salt (S), Cost Parameter (work factor).
2. Salt Encoding: The salt is encoded into the hashed password string itself.
3. Key Expansion: The password and salt are expanded into a key schedule used by the Blowfish cipher.
4. Blowfish Encryption: The expanded key is used to repeatedly encrypt a fixed string (or a series of strings) using the Blowfish block cipher. The number of rounds is determined by the work factor.
5. Output: A string containing the salt, work factor, and the final encrypted output (the hashed password).
Example (Conceptual - Very Simplified):
```python
# This is a highly simplified and incomplete illustration.
# DO NOT use this in production!
import bcrypt # Requires the 'bcrypt' package (pip install bcrypt)
password = "mysecretpassword"
salt = bcrypt.gensalt() # Generates a random salt
hashed_password = bcrypt.hashpw(password.encode('utf-8'), salt)
print(f"Hashed password: {hashed_password.decode('utf-8')}")
#To verify:
password_to_check = "mysecretpassword"
if bcrypt.checkpw(password_to_check.encode('utf-8'), hashed_password):
print("Password matches!")
else:
print("Password does NOT match.")
#Example using a cost factor of 12:
salt = bcrypt.gensalt(rounds=12)
hashed_password = bcrypt.hashpw(password.encode('utf-8'), salt)
print(f"Hashed password (cost 12): {hashed_password.decode('utf-8')}")
```
Important: Always use a dedicated bcrypt library (like the one in the example) for proper implementation and security. Don't try to roll your own!
Step-by-Step Reasoning (Why it works):
1. Salting: Prevents rainbow table attacks. The salt is stored alongside the hashed password, so it's always available for verification.
2. Work Factor (Cost Parameter): The work factor directly controls the computational cost. Each increment doubles the amount of time required to compute the hash. This makes brute-force attacks significantly slower.
3. Blowfish Encryption: The use of a well-established block cipher (Blowfish) provides a secure foundation for the hashing process.
4. Adaptive Design: The way bcrypt uses Blowfish makes it harder to parallelize efficiently. This means that attackers can't simply throw more hardware at the problem to crack passwords faster.
Practical Applications:
Password Storage: The primary and intended use case. It's considered a very good choice for storing user passwords.
Other Security-Sensitive Applications: Can be used in other situations where a computationally expensive and secure hashing function is required.
Pros:
Strong Security: Generally considered a very secure password hashing algorithm.
Adaptive: Designed to be resistant to parallel attacks.
Automatic Salting: Handles salt generation and storage automatically.
Widely Available: Implementations are available in many programming languages.
Good Reputation: Has a solid track record and is well-respected in the security community.
Cons:
Blowfish Vulnerabilities (Theoretical): While not directly impacting password hashing with bcrypt, there have been theoretical attacks against Blowfish in other contexts. This is one reason why newer algorithms like Argon2 are being considered.
Slower than PBKDF2 (with low iteration count): For very low work factors, bcrypt might be faster than PBKDF2 with a low iteration count. But for comparable security levels (modern recommended iteration counts), bcrypt can be slower. Speed is relative and depends on the parameters.
Memory Usage: Uses more memory than a simply hashed password, though this is generally not a significant concern on modern systems.
Work Factor Adjustment: Increasing the work factor to increase security is more disruptive. It requires re-hashing all stored passwords, which might be complicated in practice. With PBKDF2, you can adjust iteration count and re-hash.
PBKDF2 vs. bcrypt: Key Differences and Comparison
| Feature | PBKDF2 | bcrypt |
|--------------------|---------------------------------------------|-----------------------------------------------|
| Underlying Algorithm | HMAC (usually based on SHA-256 or SHA-512) | Modified Blowfish block cipher |
| Salting | Requires explicit salt generation and passing | Handles salt generation and storage internally |
| Key Stretching | Achieved through iteration count | Achieved through the work factor (cost) |
| Parallelization Resistance | Lower | Higher |
| Memory Hardness| Low | Low |
| Configuration | Iteration count, salt length, key length | Work factor |
| Standardization | Defined in RFC 2898 | No formal standard, but widely implemented |
| Speed | Can be tuned for performance; depends on iteration count | Generally slower than PBKDF2 (with low iteration count), comparable speed depending on the implementation.
| Security | Good, if iteration count is sufficiently high | Very good |
| Code Complexity| Can be implemented from scratch (but avoid) | Requires a dedicated library |
| Upgrading | Changing iteration count during upgrade is easier | Changing work factor needs re-hashing all passwords|
Which one to choose?
bcrypt: A good choice if security is paramount, and you want a relatively simple and well-established algorithm. The adaptive design makes it more resistant to parallel attacks.
PBKDF2: A solid choice if you need a standardized algorithm with flexible configuration and need to tune the performance by choosing appropriate iterations. However, you need to be very careful to set the iteration count high enough and choose appropriate salt lengths.
Argon2: In the context of password hashing, consider Argon2. Argon2 is the winner of the Password Hashing Competition (PHC). It is designed to be resistant to side-channel attacks and offers memory-hardness as well as tunable parallelism.
Ultimately: Use a modern password hashing library like `bcrypt` or `argon2-cffi` (Python) or their equivalents in other languages. They handle the complexities of salt generation, iteration counts, and secure implementation for you. The choice between `bcrypt` and `argon2` comes down to performance and advanced security features, which in turn depends on specific requirements. If in doubt, `argon2` provides an extra layer of security.
Recommendations for Practical Applications:
Salt Length: Use a salt of at least 16 bytes (128 bits) for both PBKDF2 and bcrypt. Larger salts are generally better.
Iteration Count (PBKDF2): Start with a high iteration count (e.g., 100,000 or more) and increase it as hardware gets faster. Measure the hashing time to ensure it's taking an acceptable amount of time (e.g., around 100-200 milliseconds per hash).
Work Factor (bcrypt): Start with a work factor of 12 and increase it over time as hardware improves. Similar to PBKDF2, measure the hashing time.
Storage: Store the salt (for PBKDF2) and the hashed password securely in your database.
Regularly Rehash: Periodically rehash your passwords with a higher iteration count or work factor to stay ahead of attackers.
Use Libraries: Always use well-vetted and maintained libraries for implementing PBKDF2 or bcrypt. Don't attempt to write your own implementation.
In Summary:
Both PBKDF2 and bcrypt are significantly better than simple hashing algorithms like MD5 or SHA-1 for password storage. bcrypt offers stronger protection against parallel attacks and handles salt generation automatically. PBKDF2 is more configurable and standardized. Argon2 is emerging as the new standard due to its memory hardness and resistance to side channel attacks. Always use a robust and well-maintained library for implementation and keep your parameters updated as hardware capabilities evolve. Password security is an ongoing process, not a one-time event.
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