1. Internet Worms Paxson, Asanovic, Dharmapurikar, Lockwood, Pang, Sommer, Weaver Rethinking Hardware Support for Network Analysis and Intrusion Prevention Vern Paxson (ICSI) Krste Asanovic (MIT) Sarang Dharmapurikar (Nuova Systems) John Lockwood (WUSTL) Ruoming Pang (Princeton) Robin Sommer (ICSI) Nicholas Weaver (ICSI) USENIX Hot Security July 31, 2006

2. Internet Worms Paxson, Asanovic, Dharmapurikar, Lockwood, Pang, Sommer, Weaver Network Analysis Performance Pressures Growing in Multiple Dimensions Increasingly, simple & efficient signature matching proves inadequate False positives Polymorphism Zero-day attacks  We need semantic application-aware analysis But: that costs CPU (parsing) and memory (state)

3. Internet Worms Paxson, Asanovic, Dharmapurikar, Lockwood, Pang, Sommer, Weaver Network Analysis Performance Pressures Growing in Multiple Dimensions, con’t Attacks inexorably grow in sophistication Arms race (particularly w/ attackers motivated by $$$) Analysis also increasingly requires context (= state) Problem of evasion leads to need to alter traffic via normalization … … so we need to operate in-line Plus we want to prevent attacks, not just detect them … … so we need to operate in-line We need to do a lot more processing ….

4. Internet Worms Paxson, Asanovic, Dharmapurikar, Lockwood, Pang, Sommer, Weaver Some Sobering Growth Trends Network traffic rates inexorably grow Network traffic volumes inexorably grow We need to do more analysis on larger amounts of data at higher speeds … But CPU performance is NOT inexorably growing any more.

5. From Hennessy and Patterson, Computer Architecture: A Quantitative Approach, 4th edition, 2006 3X gap from historical growth Uniprocessor Performance (SPECint)  All major manufacturers moving to multicore architectures  General-purpose uniprocessors have stopped historic performance scaling (no longer able to leverage Moore’s Law) –Power consumption –Wire delays –DRAM access latency –Diminishing returns of more instruction-level parallelism

6. Internet Worms Paxson, Asanovic, Dharmapurikar, Lockwood, Pang, Sommer, Weaver Where Will We Find The Performance?? FPGAs! ASICs! Multi-core! Parallelism is here and is growing. Yes, that’s what we will use … … but how? … and at what labor cost?

7. Internet Worms Paxson, Asanovic, Dharmapurikar, Lockwood, Pang, Sommer, Weaver Rethinking Hardware Support … Current efforts in the literature [SP01,FCH02, MLLP03,LMK + 03,CS04,SP04,CMS05,LNZ + 03, DKSL04,DL05,TSCV04,TS05,SL03,SML04,AL05] focus heavily on supporting signature-matching TCAMs, FPGA features, Bloom Filters for string lookups NFAs, DFAs, Aho-Corasick for reg-exp matching Nearly stateless Essentially “Snort in hardware” Rudimentary stateful analysis - TCP stream reassembly w/ adversaries - unexamined in literature until USENIX Security 2005 Commercial designs may be ahead; diff. to know

8. Internet Worms Paxson, Asanovic, Dharmapurikar, Lockwood, Pang, Sommer, Weaver How Do We Get: Stateful analysis State management in presence of adversaries Semantic rather than syntactic analysis Including at semantic layers spanning multiple connections, hosts, applications In-line processing for normalization, intrusion prevention … expressed so it can leverage tomorrow’s massively parallel processors? And without having to code for hardware specifics?

9. Internet Worms Paxson, Asanovic, Dharmapurikar, Lockwood, Pang, Sommer, Weaver Task-Level Parallelism in Network Analysis Note: Parallelism means individual forwarding latency needn’t be  sec’s. Cycle budget can be ≈ msec.

10. Internet Worms Paxson, Asanovic, Dharmapurikar, Lockwood, Pang, Sommer, Weaver Architectural Vision Express high-level (semantic, app-aware, global context) analysis using a high-level language E.g., Bro intrusion detection system Compile these expressions to an abstraction of parallelism E.g., Transactors Retarget these abstractions to different, specific hardware instances (FPGAs, multi-core) to leverage their capabilities and resources

11. Internet Worms Paxson, Asanovic, Dharmapurikar, Lockwood, Pang, Sommer, Weaver The Transactor Abstraction for Parallelism [AAC + 05, GSA06] Network of computational elements Loosely coupled via FIFOs No timing guarantees between elements Transactor unit includes Local architectural state (persists across transactions) Buffered input/output channels Set of transactions (code) that executes atomically Scheduler that mediates execution & messaging Computation always has a serializable equivalent Properties strive for efficient execution and verifiable specifications

12. Internet Worms Paxson, Asanovic, Dharmapurikar, Lockwood, Pang, Sommer, Weaver The Transactor Abstraction for Parallelism, con’t

13. Internet Worms Paxson, Asanovic, Dharmapurikar, Lockwood, Pang, Sommer, Weaver Expressing High-Level Network Analysis At lowest level, handcode analysis primitives for Transactor parallelism abstraction Connection state management, checksum validation, stream reassembly, network/transport normalization At mid-level, construct application protocol analyzers in a custom language (e.g., BinPAC, to appear IMC ‘06) Takes specification of Binary & ASCII protocols, compiles to C++ Retarget to compile to Transactor abstraction At high-level, express analysis in custom language (e.g., Bro) and likewise retarget

14. Internet Worms Paxson, Asanovic, Dharmapurikar, Lockwood, Pang, Sommer, Weaver Challenges Development of high-quality optimizing compilers For high-level analysis & protocol parsers  Abstraction For Abstraction  hardware instances Management of state and timers Private vs. shared memory

15. Internet Worms Paxson, Asanovic, Dharmapurikar, Lockwood, Pang, Sommer, Weaver Possibilities A lot of work. But if achieved, can open up network security analysis to much richer and resilient set of capabilities. Furthermore, consider that just about all of the components are not specific to network security analysis but just network analysis in general HW supporting such analysis in-line can change the paradigm of what network forwarding means No longer: send along packets w/ minimal cycles Rather: enable rich, in-depth transformation as the norm

16. Internet Worms Paxson, Asanovic, Dharmapurikar, Lockwood, Pang, Sommer, Weaver Discussion Goodbye to end-to-end semantics? Opinion: yep :-( Will parallel hardware progress sufficiently? Just one weak link and Amdahl’s Law bites you I.e., can we really keep the processing pipeline full & flowing? Maybe the right answer is a completely different (and inherently parallelizable) model of detection? Opinion: deep knowledge of app semantics is fundamental, remainder follows from that More fundamental parallelism: push work out to edges But how the heck to trust them?