Cryptography1 CPSC 3730 Cryptography Chapter 7 Confidentiality Using Symmetric Encryption.

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Presentation transcript:

Cryptography1 CPSC 3730 Cryptography Chapter 7 Confidentiality Using Symmetric Encryption

Cryptography2 Traffic Analysis 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

Cryptography3 Fig. 7.6 Traffic Padding Encryption Device

Cryptography4 Key Distribution symmetric schemes require both parties to share a common secret key issue is how to securely distribute this key often secure system failure due to a break in the key distribution scheme

Cryptography5 Key Distribution given parties A and B have various key distribution alternatives: 1.A can select key and physically deliver to B 2.third party can select & deliver key to A & B 3.if A & B have communicated previously can use previous key to encrypt a new key 4.if A & B have secure communications with a third party C, C can relay key between A & B

Cryptography6 Key Hierarchy 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

Cryptography7 Key Distribution Scenario

Cryptography8 Key Distribution Issues hierarchies of KDC’s required for large networks, but must trust each other session key lifetimes should be limited for greater security use of automatic key distribution on behalf of users, but must trust system use of decentralized key distribution controlling key usage

Cryptography9 Random Numbers many uses of random numbers in cryptography –nonces in authentication protocols to prevent replay –session keys –public key generation –keystream for a one-time pad in all cases its critical that these values be –statistically random, uniform distribution, independent –unpredictability of future values from previous values

Cryptography10 Pseudorandom Number Generators (PRNGs) often use deterministic algorithmic techniques to create “random numbers” –although are not truly random –can pass many tests of “randomness” known as “pseudorandom numbers” created by “ Pseudorandom Number Generators (PRNGs)”

Cryptography11 ANSI X9.17 PRG