Gigabit Rate Packet Pattern-Matching Using TCAM

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

2. 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

3. 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

4. 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

5. 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 ‘?’(don’t care) • Current TCAM technology • Fast Match Time:4 ns • Size: 1-2MB • Width configurable • 1024 entries *1024 bytes width • 2048 entries *512 bytes width cell entry width

6. 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

7. 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 pattern’s length • Pad all short patterns to TCAM width • Waste TCAM resources • Can we set TCAM width smaller and cut long patterns into smaller patterns?

8. 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 DEFGABCDL DEFG DEFG ABCD ABCD L BCDL Short partial patterns, many TCAM hits

9. Concatenate Partial Patterns into Long Patterns Patterns: ABCDABCD DEFGABCDL DEFGDEF DEF , Matching Table Partial Hit List (PHL)

10. 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

11. 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, mi = 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

12. When j = 1, probability is: 1- E.g., n = 1000 and m=4, it is 0.029 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? Malicious Attack? . • Worst case PHL size is at least: window size / m

13. 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

14. 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

15. 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

16. 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

17. 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

18. Backup Slides

19. Long Patterns What if pattern is longer than the width of TCAM? Split it into multiple partial patterns For example, TCAM width k=4 L ? ? ? Short partial patterns, many TCAM hits

20. Statistical Analysis • Example • n = 2000, mi = 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: mibytes 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

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

22. 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

23. 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