A High Throughput String Matching Architecture for Intrusion Detection and Prevention

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1 A Hig Trougput tring Matcing Arcitecture for Intruion Detection and Prevention Lin Tan, Timoty erwood Appeared in ICA 25 Preented by: aile Kumar Dicuion Leader: Max Podleny

2 Overview Overview of ID/IP ytem» tring matcing and regular expreion matcing tring matcing algoritm» Ao-Coraick algoritm Overview of te propoed arcitecture Analyi of te propoed arcitecture Concluion 2 - aile Kumar - 2/8/25

3 ID Overview Intruion detection ytem, ID mut be capable of ditinguiing between normal (not ecurity-critical) and abnormal uer activitie» However tranlating te uer beavior into a ecurity-related deciion i often not tat eay One approac i anomaly detection» Anomaly detector contruct profile tat repreent normal uage» If profile of current data doen t matc te normal profile => a poible attack» Typically reult in ig fale poitive and few negative too» An intelligent intruder can train te ytem to beave oterwie Normal Unpredictable Abnormal 3 - aile Kumar - 2/8/25

4 ID Overview Anoter approac i ome kind of ignature detection Mibeavior ignature fall into two categorie:» Attack ignature action pattern tat may poe a ecurity treat. Typically preented a a erie of activitie interleaved (may be) wit neutral one E.g. equence of flag et on ome pecific equence of packet» elected text tring ignature to matc text tring wic look for upiciou action (e.g. calling /etc/pawd). Effective againt attack tat exploit programming flaw. Effective but not immune to novel attack» Difficultie in updating information on new type of attack» till mot widely ued 4 - aile Kumar - 2/8/25

5 5 - aile Kumar - 2/8/25 ID Overview At te eart of mot ignature baed ID ytem, lie a tring (regular expreion) matcing engine» ince ti engine a to can every byte of data, it migt become te trougput bottleneck Ti paper preent a ig trougput tring matcing arcitecture Advantage of propoed ceme:» Claimed to be pace efficient Entire rule et can be tored on-cip» Claimed to be able to acieve ig trougput Limitation (will cover later)» New ytem do regex matcing, FM i typically too large to fit on cip, even wit te propoed ceme.» imple FM compreion ceme may beat te propoed idea

6 tring Matcing Algoritm (Ao-Coraick) For a et P of pattern, it build a DFA, wic accept all pattern in P. 6 - aile Kumar - 2/8/25

7 7 - aile Kumar - 2/8/25 tring Matcing Algoritm (Ao-Coraick) Let ay, P i {e, e, i, er} e i e r Initial tate Accepting tate tate Tranition Function i r Example from Lin Tan et. al.

8 8 - aile Kumar - 2/8/25 Propertie of DFA created by Ao-Coraick Conume one caracter per tate traveral» A modified automaton i alo ued in many ytem, wic recan a caracter if tere i no outgoing edge for it (fail ptr) Reduce te DFA ize tremendouly e i e r i r e i e r Example from Lin Tan et. al.

9 How to implement efficiently on-cip Problem: ize too big to be on-cip» ~, node for NORT rule et wit ~ tring» 256 out edge per node» Require,*256*4 = ~5MB 256 next tate pointer : <4>-bit <4>-bit <4>-bit <4>-bit... <4>-bit 9999 olution: partition eac tate macine into mall tate macine uc tat» Eac macine andle a ubet of tring only» Alo, eac macine a few outgoing edge only 9 - aile Kumar - 2/8/25

10 Bit-plitting Algoritm Overview Bit-plit tring Matcing Algoritm» Reduce out edge from 256 to 2. Partition te rule et P into maller et P to P n Build AC tate-macine for eac ubet P i For eac P i, rip it DFA apart into 8 tiny tatemacine, B i troug B i7 Eac binary FM operate on bit of te 8 bit input caracter» A matc i announced only if all 8 macine find a matc - aile Kumar - 2/8/25

11 Bit-plitting tring Matcing Arcitecture Let ay we ave 4 tring in P {e, e, i, er} Conider FM 3» It look at 3 rd bit of te input car and make tate tranition baed upon weter it i or Example, let ay our input tream i xe Example from Lin Tan et. al. - aile Kumar - 2/8/25

12 Bit FM Contruction Ue ubet contruction algoritm to build bit FM P B e r i 6 7 i r 3 4 e 5 b {} b {, } b2 {,3 } b3 {,,2,6} b4{,,4} {,3 } b6{,,2,5,6} b3{,,2,6} b5{,3,7,8} Example from Lin Tan et. al. b7{,3,9} 2 - aile Kumar - 2/8/25

13 3 - aile Kumar - 2/8/25 Bit FM Contruction Remove te non-accepting tate from te mall FM Example from Lin Tan et. al e i e r i r b { } P Pruned B 3 b { } b2 { } b3{ 2 } b4 { } b6{ 2,5 } b5{7} b7{9}

14 Bit-plitting tring Matcing Arcitecture Build all bit FM B i Matc announced, if all bit FM announce a matc 4 - aile Kumar - 2/8/25 Example from Lin Tan et. al.

15 An Example Matcing xe 2 e r 8 9 P B 3 i 6 7 i 5 - aile Kumar - 2/8/25 r 3 4 e 5 B 4 b {} b {} b{} b2{} b2{} b{} b4{2} b4 {} b3 {} b6{2,5} b6{2,5} b5 {} b3{2} b8{2,7} b5{7} b7 {} b7{9} b9{9} Only if all te tate macine agree, i tere actually a matc. Example from Lin Tan et. al.

16 How to map it to ardware efficiently Problem:» Every tate in te bit-fm B i migt ave up to accepting tate of te original FM D. Note tat # accepting of tate = # of tring =» Even if we keep bit-vector to repreent te accepting tate of te original D, we will need -bit per tate of B i.» i typically >, o not practical olution:» Partition te rule et P into maller ubet P i eac wit g rule Build FM D i for eac P i and bit-plice D i into B i, B i7» Now every tate in B ij can ave at mot g accepting tate, ence only g-bit are needed 6 - aile Kumar - 2/8/25

17 How to map it to ardware efficiently Alo note tat any D FM can be ripped into 2 or 4 bit-fm a well» Wen ripped into 4 different bit-fm, eac one conume 2- bit of te input caracter» Wen ripped into 2 different bit-fm, eac one conume 4- bit 7 - aile Kumar - 2/8/25

18 g = 6 Eac tate Macine Tile # of tate = 256 (8-bit tate encoding) D FM i ripped into 4 FM (eac accept 2-bit I/P) 8 - aile Kumar - 2/8/25 Example from Lin Tan et. al.

19 Hardware Implementation 9 - aile Kumar - 2/8/25 Example from Lin Tan et. al.

20 Non Interrupting Update Iue:» Mut copy te tate of every flip-flop of te affected module onto te replacement module E.g. te current tate pointer of te affected module mut be copied into te replacement module Tee iue are not mentioned in te paper 2 - aile Kumar - 2/8/25

21 Optimal partitioning Tere are two type of partition.» One i te partition of te et of tring» Anoter i te partition of eac D FM into multiple bit FM 8 binary partition i clearly eay to undertand However, it i poible to partition into 2 or 4 partition, and eac partition conume 4 and 2 input bit of te input caracter repectively. Terminology» = total # of tring» g = # of tring per group (# of partition = /g)» n = # of partition of tate macine (, 2, 4, 8)» L = Average # of caracter per tring How to cooe g and n?» wic conume minimum area 2 - aile Kumar - 2/8/25

22 Optimal partitioning Total number of bit needed i: # of FM partition # of bit to encode tate # of partial matc bit # of outgoing edge per tate Total # of tate in eac bit-fm Total # of module (tring et partition) 22 - aile Kumar - 2/8/25

23 Optimal partitioning Plot from te review of Mike Wilon ( ignature, average lengt 2)» Typical optimal # of FM partition = 2, aile Kumar - 2/8/25

24 Partitioning tring et In te analyi preented in te paper, it i claimed tat partitioning tring et alway reduce pace» Not quite rigt wen tere i overlap among te tring P = {e, er, er}, If we partition into 3 et e e e r r e 2 r Wit overlapping tring, fewer tate are needed w/o partitioning aile Kumar - 2/8/25

25 Performance Reult - Memory 25 - aile Kumar - 2/8/25 From Lin Tan et. al.

26 Performance Reult - Trougput 26 - aile Kumar - 2/8/25 From Lin Tan et. al.

27 trengt of te Algoritm Can be very effective for dene DFA, wen tere are plenty of outgoing edge from every tate In ti cae, pat compreion will not elp a lot However, ripping apart te tate macine into bit tate macine will reduce te number of outgoing edge to 6» (2 edge x 8 FM) or (4 edge x 4 FM)» For dene grap, upto 6 time reduction in tate pace 27 - aile Kumar - 2/8/25

28 ome Iue Tuck [3] ued bitmap compreion and pat compreion to reduce te amount of memory needed for NORT rule to.mb Note tat, Tuck didn t do any tring et partitioning» w/o any partitioning, bit-plitting will conume >2 MB 28 - aile Kumar - 2/8/25 From Lin Tan et. al.

29 Concluion Novel Bit-plit tring Matcing Algoritm» Reduce out edge from 256 to 2» Can be extremely effective for dene grap Performance/area beat te bet tecnique by a factor of or more..4mb and Gbp for nort rule et ( >, caracter) 29 - aile Kumar - 2/8/25

30 3 - aile Kumar - 2/8/25 Tank you and Quetion

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