Chapter 7 – Confidentiality Using Symmetric Encryption.

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Presentation transcript:

Chapter 7 – Confidentiality Using Symmetric Encryption

Confidentiality using Symmetric Encryption Assume that traditional symmetric encryption is used to provide message confidentiality consider typical scenario What are the possible points of vulnerability

Typical Scenario

Points of attacks consider attacks and placement in this scenario –snooping from another workstation LAN is a broadcast network Traffic visible to all workstations in the LAN –use dial-in to LAN or server to snoop If a server or a workstation offers dial-in service –router can be vulnerable If one has physical access to the router –monitor and/or modify traffic one external links

Placement of Security Devices

Two major placement alternatives link encryption –encryption occurs independently on every link –implies must decrypt traffic between links –One key per (node, node) pair –Message exposed in nodes –Transparent to user, done in hardware end-to-end encryption –encryption occurs between original source and final destination –One key per user pair –Message encrypted in nodes –User selects hardware, software implementation

Traffic Analysis when using end-to-end encryption must leave headers in clear –so network can correctly route information hence although contents protected, traffic pattern flows are not

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

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 As number of parties grow, some variant of 4 is only practical solution.

Key Distribution Scenario

Random Numbers many uses of random numbers in cryptography –Ns 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 with uniform distribution, independent –unpredictable cannot infer future sequence on previous values

Natural Random Noise best source is natural randomness in real world find a random event and monitor generally need special h/w to do this –eg. radiation counters, radio noise, audio noise, thermal noise, leaky capacitors, mercury discharge tubes etc

Published Sources a few published collections of random numbers Rand Co, in 1955, published 1 million numbers –generated using an electronic roulette wheel –has been used in some cipher designs cf Khafre earlier Tippett in 1927 published a collection issues are that: –these are limited –too well-known for most uses

Pseudorandom Number Generators (PRNGs) algorithmic technique to create “random numbers” –although not truly random

Linear Congruential Generator common iterative technique using: X n+1 = (aX n + c) mod m given suitable values of parameters can produce a long random-like sequence note that an attacker can reconstruct sequence given a small number of values

Using Block Ciphers as Stream Ciphers can use block cipher to generate numbers use Counter Mode X i = E Km [i] use Output Feedback Mode X i = E Km [X i-1 ] ANSI standard, uses output feedback 3- DES

Blum Blum Shub Generator use least significant bit from iterative equation: –Get prime p, q, such that p,q=3 mod 4 –Get n=p.q, and a random number s, gcd(s,n)=1 –X 0 = s 2 mod n –x i+1 = x i 2 mod n Output: binary sequence: (table 7.2) is unpredictable given any run of bits Passes the next-bit test –No poly-time algorithm that can predict the next bit with p>1/2 slow, since very large numbers must be used too slow for cipher use, good for key generation

Summary have considered: –use of symmetric encryption to protect confidentiality –need for good key distribution –use of trusted third party KDC –random number generation