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Gigabit Rate Packet Pattern-Matching Using TCAM Fang Yu and Randy H. Katz UC Berkeley T. V. Lakshman Bell Laboratories, Lucent Technologies

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Motivation Numerous malicious probes and worms End-host based solution is not sufficient It is hard for all end users to apply patches quickly Worms can contaminate millions of hosts within hours Network based solution – network intrusion detection systems (NIDS) Perform packet scanning for complicated worm patterns in the network Stop worms from reaching end hosts Easy to manage for network administrators

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Pattern Matching for NIDS Thousands of complicated patterns Patterns have variable lengths Patterns with correlation abc followed by cde within 3 bytes Patterns with negation user not followed by |0a| within 50 bytes Require packet payload scanning Not supported by most current network devices, which support packet header processing only

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Current Pattern Matching Schemes Software based solutions Speed is slow FPGA solutions Build large DFA or NFA for all patterns Build a KMP based search engine for each pattern Bloom Filters One bloom filter for each pattern length Not scalable when pattern lengths vary dramatically

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Ternary-CAM (TCAM) Fully associative memory compare input string with all the entries in parallel If multiple matches, report the index of the first match Each cell takes one of three logic states 0, 1, and ?(dont care) Current TCAM technology Fast Match Time: 4 ns Size: 1-2MB Width configurable 1024 entries *1024 bytes width 2048 entries *512 bytes width entry cell width

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Pattern Matching with TCAM Put all the patterns into the TCAM Assume patterns are less or equal to the TCAM width If less than the TCAM width, pad with ? Order the patterns according to lengths in reverse order When matching entry ABC, report matching of both pattern ABC and AB Shift one byte each time

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Analysis Scan speed: 4 ns per TCAM lookup, shift one byte at a time 8bits/4ns =2 Gbps worst case scan rate Limitation: require all the patterns to be shorter or equal to the TCAM width Set the TCAM width >= longest patterns length Pad all short patterns to TCAM width Waste TCAM resources Can we set TCAM width smaller and cut long patterns into smaller patterns?

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Long Patterns Cut long patterns into smaller patterns TCAM width w=4 bytes DEFGABCDL is split into DEFG, ABCD, and L Pad the last partial pattern with the tail of the second last partial pattern DEFGABCDL is split into DEFG, ABCD, and BCDL DEFGABCDL DEFG ABCD L DEFGABCDL DEFG ABCD BCDL Short partial patterns, many TCAM hits

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Concatenate Partial Patterns into Long Patterns Patterns: ABCDABCD DEFGABCDL DEFGDEF DEF, Matching Table Partial Hit List (PHL) PositionMatched entry Prefix Index Suffix Index Distance Matched Long Pattern Index 1(ABCD) 4ABCDABCD 2(DEFG)1(ABCD)43(DEGFABCD) 2(DEFG)3(GDEF)3(DEGFDEF 3(DEGFABCD)1(ABCD)4ABCDABCD 3(DEGFABCD)2(BCDL)1DEFDABCDL PositionMatched entry 12(DEFG) PositionMatched entry 53(DEFGABCD)

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Correlated Patterns One pattern after another E.g. ABCD followed by DEF within 10 bytes The matching result of ABCD has to be in PHL for 10 positions

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Matching Process TCAM reports a miss No extra memory lookup TCAM reports a hit If it is a partial pattern For every item in PHL One memory lookup into matching table to see whether it generates a valid pattern Examples based on statistical analysis n = 2000, m i = 200 bytes, w =4 bytes. Associate hit rate is 2.2e-5, PHL size is 8.8e-5 w = 8 bytes, associate hit rate is 2.6e-15, PHL size is 2.08e-14 Associate hit rate PHL size

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Malicious Attack? When j = 1, probability is: 1- E.g., n = 1000 and m=4, it is When j increases, the probability increases. If j=m, then probability =1 Window: distance between two correlated patterns After matching a pattern, what is possibility to match another at window size j positions later?. Worst case PHL size is at least: window size / m

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Simulation Results on ClamAV ClamAv virus signature database Version 0.15, which contains simple patterns only 1768 patterns, varying from 6 bytes to 2189 bytes

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Effect of TCAM Width Total TCAM space: Increase when w increases, because of padding Mapping Table Size Decreases as w increases because of fewer partial patterns

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PHL Size on Real Data For each packet, record average and maximum PHL size Avg: mean of the average PHL size over all packets AvgMax: mean of the maximum PHL sizes Max: maximum PHL size over all packets TCAM Width MIT DumpBerkeley Dump Avg Max Avg Max e-65.6e-481.e-61.9e e-75.8e-63

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Simulation Results on Snort SNORT system (v2.1.2) has 1991 rules 1039 simple patterns 527 correlated patterns Up to 7 sub-patterns Set TCAM width as 128 bytes Patterns fit into a TCAM size of 295KB Win- dow Size MIT DumpBerkeley Dump Avg Max Avg Max

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Conclusions Fast speed pattern matching is essential for building effective defenses against virus Multiple pattern matching with TCAM Achieve multi-gigabit rate Search for thousands, or tens of thousands patterns in parallel Support long patterns, correlated patterns, and also patterns with negation, wildcards Can be extended to support higher rates with larger TCAMs

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Backup Slides

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Long Patterns What if pattern is longer than the width of TCAM? Split it into multiple partial patterns For example, TCAM width k=4 Pattern index Pattern content 1ABCD 2DEFG ABCD L 3DEFG DEF 4DEF Short partial patterns, many TCAM hits L ? ? ?

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Statistical Analysis Example n = 2000, m i = 200 bytes, w =4 bytes. Associate hit rate is 2.2e-5, PHL size is 8.8e-5 w = 8 bytes, associate hit rate is 2.6e-15, PHL size is 2.08e-14 Assume random input string, independent patterns Number of patterns: n Pattern size: m i bytes for pattern i TCAM width: w Total entries for partial items in TCAM: Associate hit rate is Ignoring the dependency between neighboring positions, PHL size is

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Synthesized Worst-case Packets Four sets of synthesized data 1, 10, and 100 randomly inserted virus patterns per packet

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Memory Lookup Process TCAM reports a miss No extra memory lookup Memory lookup process is idle TCAM reports a hit One memory lookup in the combined pattern table Lookups in matching table if PHL is not empty

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Effects of Memory Ratio on Scan Rate Scan ratio Total scanning time (including memory lookups) vs. the time spent on TCAM lookups only. E.g., scan ratio=2 total scanning rate = TCAM access rate /2 Memory ratio SRAM to TCAM access times

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