Information Security Lab. Dept. of Computer Engineering 182/203 PART I Symmetric Ciphers CHAPTER 7 Confidentiality Using Symmetric Encryption 7.1 Placement.

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PART I Symmetric CiphersCHAPTER 7 Confidentiality Using Symmetric Encryption

7.1 Placement of Encryption Function

7.2 Traffic Confidentiality

7.3 Key Distribution

7.4 Random Number Generation

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7.1 Placement of Encryption 7.1 Placement of Encryption FunctionFunction

Symmetric encryption is used to provide message confidentiality; We need to decide what to encrypt and where the encryption function should be located.

Potential Location for Confidentiality Attacks

Fig. 7.1 Point of Vulnerability

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7.1 Placement of Encryption 7.1 Placement of Encryption FunctionFunction

Link versus End-to-End Encryption Have two major placement alternatives link encryption

Encryption occurs independently on every link; Message is vulnerable at each node. Requires many encryption devices; many keys must

be provided

end-to-end encryption Encryption occurs between original source and final destination Need devices at each end with shared keys

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7.1 Placement of Encryption 7.1 Placement of Encryption FunctionFunction

Link versus End-to-End Encryption

Fig. 7.2 Encryption Across a Packet Switching Network

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7.1 Placement of Encryption 7.1 Placement of Encryption FunctionFunction

Table 7.1 Characteristic of Link and End-to-End Encryption

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7.1 Placement of Encryption 7.1 Placement of Encryption FunctionFunction

Fig. 7.4 Encryption Coverage Implementations of Store-and-Forward Communications

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7.2 7.2 Traffic Traffic ConfidentialityConfidentiality is monitoring of communications flows between parties

useful both in military & commercial spheres can also be used to create a covert channel

link encryption obscures header details but overall traffic volumes in networks and at end- points is still visible

traffic padding can further obscure flows but at cost of continuous traffic

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7.3 7.3 Key DistributionKey Distribution Symmetric schemes require both parties to share common secret key. Issue is how to securely distribute this key Often secure system failure due to a break in the key distribution scheme. Given parties A and B have various key distribution alternatives:

1) A can select key and physically deliver to B2) Third party can select & deliver key to A & B3) If A & B have communicated previously, They can

use previous key to encrypt a new key4) If A & B have secure communications with a third

party C, C can relay key between A & B

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7.3 Key Distribution7.3 Key Distribution Typically have a hierarchy of keys Session key

temporary key; used for encryption of data between users for one logical session then discarded.

Master key used to encrypt session keys shared by user & key distribution center

A Key Distribution Scenario The key distribution concept can be deployed in a number of ways. Popek, G. Kline, C. “Encryption and Secure Computer networks,” ACM Computer Surveys, Dec., 1979

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7.3 Key Distribution7.3 Key Distribution

Fig. 7.9 Key Distribution Scenario

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7.3 Key Distribution7.3 Key DistributionKey Distribution Issues Hierarchies of KDC’s required for large networks, but must trust each other.

Session key lifetimes should be limited for greater security

A Transparent Key Control Scheme Automatic Key distribution : useful for providing end-to-

end encryption at a network or transport level in a way that is transparent to end users.

See Fig. 7.10

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7.3 Key Distribution7.3 Key Distribution

Fig. 7.10 Automatic Key Distribution for Connection-Oriented Protocol

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7.3 Key Distribution7.3 Key DistributionDecentralizing Key Control

Controlling Key Usage

Need to be as many as n(n1)/2 master keys for a configuration with n end systems.

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7.4 Random Number Generation7.4 Random Number GenerationThe Use of Random Numbers Many uses of random numbers in cryptography

nonces in authentication protocols to prevent replay attacks Session keys generation Keys for the RSA public key encryption algorithm. Keystream for a one-time pad

Requirement for a random numbers: randomness and unpredictability

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7.4 Random Number Generation7.4 Random Number GenerationThe Use of Random Numbers Randomness : The following two criteria are used to validate that a sequence of numbers is random:

Uniform distribution : The frequency of occurrence of each of the numbers should be approximately the same. Independence : No one value in the sequence can be inferred from the other.

Unpredictability : With true random sequences, each number is statistically independent of other numbers in the sequence and therefore unpredictable.

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7.4 Random Number Generation7.4 Random Number GenerationPseudorandom Number Generators (PRNGs) often use deterministic algorithmic techniques to create “random numbers”

although are not truly random can pass many tests of “randomness” ENT, DieHard

known as “pseudorandom numbers”; created by “Pseudorandom Number Generators (PRNGs)”

Linear Congruential Generators common iterative technique using:

Xn+1 = (aXn + c) mod m The selection of values for a, c, and m is critical in developing a good random number generator

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7.4 Random Number Generation7.4 Random Number GenerationLinear Congruential Generators Given suitable values of parameters can produce a long

random-like sequence

Suitable criteria to have are: Function generates a full-period Generated sequence should appear random Efficient implementation with 32-bit arithmetic

Note that an attacker can reconstruct sequence given a small number of values

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7.4 Random Number Generation7.4 Random Number Generation

Fig. 7.13 Pseudorandom Number Generation from a Counter

Cryptographically Generated Random Numbers Cyclic Encryption

DES Output Feedback Mode

Xi = EKm[Xi-1]

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7.4 Random Number Generation7.4 Random Number GenerationCryptographically Generated Random Numbers ANSI X9.17 PRNG : One of the strongest PRNGs

Fig. 7.14 ANSI X9.17 PRNS

Data/time

ith seed value

DES keys

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7.4 Random Number Generation7.4 Random Number GenerationBlum Blum Shub Generator (BBS) Based on public key algorithms. Use least significant bit from iterative equation:

X0 = s2 mod n for i = 1 to Xi = Xi1

2 mod n Bi = Xi mod 2where n = pq, and primes p and q = 3 mod 4

Unpredictable, passes next-bit test Cryptographically secure pseudorandom bit generator Security rests on difficulty of factoring N Slow, since very large numbers must be used Too slow for cipher use, good for key generation

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SummarySummary

have considered: use and placement of symmetric encryption to protect

confidentiality need for good key distribution use of trusted third party KDC’s random number generation issues