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Efficient Memory Utilization on Network Processors for Deep Packet Inspection Piti Piyachon Yan Luo Electrical and Computer Engineering Department University of Massachusetts Lowell

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ANCS 2006U Mass Lowell Our Contributions Study parallelism of a pattern matching algorithm Propose Bit-Byte Aho-Corasick Deterministic Finite Automata Construct memory model to find optimal settings to minimize the memory usage of DFA

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ANCS 2006U Mass Lowell DPI and Pattern Matching Deep Packet Inspection –Inspect: packet header & payload –Detect: computer viruses, worms, spam, etc. –Network intrusion detection application: Bro, Snort, etc. Pattern Matching requirements 1.Matching predefined multiple patterns (keywords, or strings) at the same time 2.Keywords can be any size. 3.Keywords can be anywhere in the payload of a packet. 4.Matching at line speed 5.Flexibility to accommodate new rule sets

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ANCS 2006U Mass Lowell Classical Aho-Corasick (AC) DFA: example 1 A set of keywords –{he, her, him, his} accept state start state accept state Failure edges back to state 1 are shown as dash line. Failure edges back to state 0 are not shown.

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ANCS 2006U Mass Lowell Memory Matrix Model of AC DFA Snort (Dec’05): 2733 keywords 256 next state pointers –width = 15 bits > 27,000 states keyword-ID width = 2733 bits 27538 x (2733 + 256 x 15) = 22 MB 22 MB is too big for on-chip RAM

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ANCS 2006U Mass Lowell Bit-AC DFA ( Tan-Sherwood’s Bit-Split) Need 8 bit-DFA

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ANCS 2006U Mass Lowell Memory Matrix of Bit-AC DFA Snort (Dec’05): 2733 keywords 2 next state pointers –width = 9 bits 361 states keyword-ID width = 16 bits 1368 DFA 1368 x 361 x (16 + 2 x 9) = 2 MB

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ANCS 2006U Mass Lowell Bit-AC DFA Techniques Shrinking the width of keyword-ID –From 2733 to 16 bits –By dividing 2733 keywords into 171 subsets Each subset has 16 keywords Reducing next state pointers –From 256 to 2 pointers –By dividing each input byte into 1 bits –Need 8 bit-DFA Extra benefits –The number of states (per DFA) reduces from ~27,000 to ~300 states. –The width of next state pointer reduces from 15 to 9 bits. Memory –Reduced from 22 MB to 2 MB The number of DFA = ? –With 171 subsets, each subset has 8 DFA. –Total DFA = 171 x 8 = 1,368 DFA What can we do better to reduce the memory usage?

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ANCS 2006U Mass Lowell Classical AC DFA: example 2 Failure edges are not shown. 28 states

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Byte-AC DFA Considering 4 bytes at a time 4 DFA < 9 states / DFA 256 next state pointers! Similar to Dharmapurikar-Lockwood’s JACK DFA, ANCS’05

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ANCS 2006U Mass Lowell Bit-Byte-AC DFA 4 bytes at a time Each byte divides into bits. 32 DFA (= 4 x 8) < 6 states/DFA 2 next state pointers

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ANCS 2006U Mass Lowell Memory Matrix of Bit-Byte-AC DFA Snort (Dec’05): 2733 keywords 4 bytes at a time < 36 states/DFA 2 next state pointers –width = 6 bits keyword-ID width = 3 bits 29152 DFA (= 911 x 32) 29152 x 36 x (3 + 2 x 6) = 1.9 MB 1.9 MB is a little better than 2 MB. This is because It is not any optimal setting. Each DFA has different number of states. Don’t need to provide same size of memory matrix for every DFA.

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ANCS 2006U Mass Lowell Bit-Byte-AC DFA Techniques Still keeping the width of keyword-ID as low as Bit-DFA. Still keeping next state pointers as small as Bit-DFA. Reducing states per DFA by –Skipping bytes –Exploiting more shared states than Bit-DFA Results of reducing states per DFA –from ~27,000 to 36 states –The width of next state pointer reduces from 15 to 6 bits.

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ANCS 2006U Mass Lowell Construction of Bit-Byte AC DFA bit 3 of byte 0 4 bytes (considered) at a time

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ANCS 2006U Mass Lowell Construction of Bit-Byte AC DFA 4 bytes (considered) at a time

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ANCS 2006U Mass Lowell Construction of Bit-Byte AC DFA 4 bytes (considered) at a time

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ANCS 2006U Mass Lowell Construction of Bit-Byte AC DFA 4 bytes (considered) at a time

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ANCS 2006U Mass Lowell Construction of Bit-Byte AC DFA 4 bytes (considered) at a time

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ANCS 2006U Mass Lowell Construction of Bit-Byte AC DFA 4 bytes (considered) at a time

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ANCS 2006U Mass Lowell Construction of Bit-Byte AC DFA 4 bytes (considered) at a time

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ANCS 2006U Mass Lowell Construction of Bit-Byte AC DFA 4 bytes (considered) at a time

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ANCS 2006U Mass Lowell Construction of Bit-Byte AC DFA 4 bytes (considered) at a time

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ANCS 2006U Mass Lowell Construction of Bit-Byte AC DFA Failure edges are not shown.

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ANCS 2006U Mass Lowell Construction of Bit-Byte AC DFA

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ANCS 2006U Mass Lowell Construction of Bit-Byte AC DFA 32 bit-byte DFA need to be constructed.

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ANCS 2006U Mass Lowell Bit-Byte-DFA: Searching

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ANCS 2006U Mass Lowell A failure edge is shown as necessary. 0 Bit-Byte-DFA: Searching

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ANCS 2006U Mass Lowell Bit-Byte-DFA: Searching

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ANCS 2006U Mass Lowell A failure edge is shown as necessary. 0 Bit-Byte-DFA: Searching

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ANCS 2006U Mass Lowell Match=> (keyword) ‘memory’ Only all 32 bit-DFA find the match in their own! Bit-Byte-DFA: Searching

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ANCS 2006U Mass Lowell Find the optimal settings to minimize memory When k = keywords per subset –The width of keyword-ID = k bits –k = 1, 2, 3, …, K –when K = the number of keywords in the whole set. Snort (Dec.2005) : K = 2733 keywords b = bit(s) extracted for each byte –b = 1, 2, 4, 8 –# of next state pointers = 2 b –The example 2: b = 1 –Beyond b > 8 > 256 next state pointers B = Bytes considered at a time –B = 1, 2, 3, … –The example 2: B = 4 Total Memory (T) is a function of k, b, and B. –T = f (k, b, B)

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ANCS 2006U Mass Lowell T’s Formula Total memory of all bit-ACs in all subset when,,and

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ANCS 2006U Mass Lowell keywords per subset Find the optimal k Each pair of (b, B) has one optimal k for a minimal T. T_min at k=12

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ANCS 2006U Mass Lowell Find the optimal b keywords per subset Each setting of k, b, and B has different optimal point. –Choosing only the optimal setting to compare. b = 2 is the best.

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ANCS 2006U Mass Lowell Find the optimal B keywords per subset b = 2 T reduces while B increases. –Non-linearly B > 16, –T begins to increase. B = 16 is the best for Snort (Dec’05).

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ANCS 2006U Mass Lowell Comparing with Existing Works keywords per subset Tan-Sherwood’s, Brodie-Cytron-Taylor’s, and Ours Our Bit-Byte DFA when B=16 –The optimal point at b=2 and k=12 –272 KB –14 % of 2001 KB (Tan’s) –4 % of 6064 KB (Brodie’s)

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ANCS 2006U Mass Lowell Comparing with Existing Works keywords per subset Tan-Sherwood’s and Ours: At B = 1 (Tan’s on ASIC) –2001 KB –k = 16 is not the optimal setting for B=1. –Each bit-DFA uses same storage’s capacity, which fits the largest one (worst case). (Ours on NP) –396 KB < 2001 KB –k = 3 is the optimal setting for B=1. –Each bit-DFA uses exactly memory space to hold it.

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ANCS 2006U Mass Lowell Results with an NP Simulator keywords per subset NePSim2 –An open source IXP24xx/28xx simulator NP Architecture based on IXP2855 –16 MicroEngines (MEs) –512 KB –1.4 GHz Bit-Byte AC DFA: b=2, B=16, k=12 –T = 272 KB –5 Gbps

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ANCS 2006U Mass Lowell Conclusion keywords per subset Bit-Byte DFA model can reduce memory usage up to 86%. Implementing on NP uses on-chip memory more efficiently without wasting space, comparing to ASIC. NP has flexibility to accommodate The optimal setting of k, b, and B. Different sizes of Bit-Byte DFA. New rule sets in the future. The optimal setting may change. The performance (using a NP simulator) satisfies line speed up to 5 Gbps throughput.

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ANCS 2006U Mass Lowell Thank you Question? Piti_Piyachon@student.uml.edu Yan_Luo@uml.edu

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