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Cryptanalysis on FPGA Based Hardware

Cryptanalysis on FPGA Based Hardware Malcolm Alda Sumantri Bachelors of Engineering (Software) & Bachelors of Commerce (Finance) Supervisors: Matt Barrie Craig Jin The University of Sydney Introduction Welcome to the Digital Age where everything can be replicated! Cryptography is used…

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Cryptanalysis on FPGA Based Hardware

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  1. Cryptanalysis on FPGA Based Hardware Malcolm Alda SumantriBachelors of Engineering (Software) & Bachelors of Commerce (Finance) Supervisors:Matt BarrieCraig Jin The University of Sydney

  2. Introduction • Welcome to the Digital Age where everything can be replicated! • Cryptography is used… • To protect our privacy • For example: our real identity, our e-mails to family and friends, our digital photos, our work. • To protect corporate secrets • For example: future corporate strategies, intellectual property, pricing information, human resources information. • Bygovernments • For example: sending messages to spies, task forces, between agencies to protect civilians and against terrorism. • How secure are our currently deployed cryptosystems?

  3. Motivation • Information security is a resource game. • More funds means more access to information. • The US National Security Agency’s annual budget is classified but is said to be over US $13 billion. • Assessing the strength of our cryptosystems therefore involves determining the cost to break them. • Rapid development in Field Programmable Gate Array Technology (FPGA) technology that makes it cheaper to develop high-performance custom hardware systems. FPGA technology has proven to be effective for cryptographic use. • A recent optimization in cryptanalysis. • Rainbow Tables

  4. Background • Symmetric Cipher • Cryptanalysis: Code breaking, reveal the plaintext without the key. • Exhaustive Key Search: Try every key possible, requires large computational power. • Table Lookup: Store keys and ciphertexts in a massive tables to perform a lookup when trying to attack, requires a large amount of memory (infeasible). • Time-memory trade-off: Give up memory to achieve a faster attack time. • FPGAs • Reconfigurable logic (upload the bitstream to the hardware). • Cheaper than Application Specific Integrated Circuits (ASICs) for small volumes.

  5. Time-Memory Trade-Off:Rainbow Tables • How does it work? • Assume a chosen-plaintext attack scenario. • The attacker can choose which plaintext to access. • This attacker will use this to attack the cryptosystem. • This is practical in the real-world (UNIX password hashing, “#include <stdio.h>”, “\n”) • Two Phases • Precomputation Phase • Online Attack Phase (Cryptanalytic Attack) • Precomputation Phase: Generate a rainbow table. • A rainbow table is a two-column table (start-point, end-point) • These points are possible keys. • This table is generated by a specific algorithm. • Online Attack Phase: Use the rainbow table. • We are given a ciphertext to break. • Now we perform a search on the rainbow table by using another algorithm • This method is probabilistic, but faster than exhaustive key search. • Unlike exhaustive key search that only requires computational resources (processor). This method uses memory as well as computational resources. • As a result, the attack time is faster but we have given up memory. This is the trade-off.

  6. Methodology • Design and implement an FPGA based cryptanalytic system that uses the rainbow tables method of cryptanalysis. • Use the Data Encryption Standard (DES) as the test symmetric cipher. • DES uses a 56-bit key. • DES is the most widely studied cipher. • DES is still used today (UNIX password hashing). • Determine the cost to break DES. • Extrapolate the cost to break other ciphers.

  7. Design I – Data Encryption Standard • In designing a cryptanalytic system, the performance of the cipher module will determine the performance. • Security of DES derives from 16 rounds of permutations, substitutions and xoring. • Each round is implemented as a 3-stage pipeline. A total of 48-stages for the 16 rounds of DES. • Pipelining improves performance: • Attain higher clock frequencies. • Achieve parallelization: 48 encryptions per clock cycle.

  8. Design II – The Rainbow Table Precomputation System 1. High Level System Design 2. Hardware Design 3. Hardware output behavior (Timing Diagram)

  9. Design III – The Rainbow Table Online Attack System 1. High Level System Design 2. Hardware Design 3. Mechanism

  10. Experiment and Results • Experiment: • Cryptanalytic attack on 40-bit DES since the resources to break DES is out-of-reach for the budget in this thesis. • Use Sensory NetworksTM NodalCoreTM C-1000 PCI Card. • Xilinx® Virtex-II Pro VP-40 FPGA • Flexible chipset architecture to embed our hardware engines. • PCI interface allows for high-speed communications. • Results • 40-bit DES Rainbow Table can be generated in less than 4 hours. Table parameters allows for 85% cryptanalytic success probability. • Fastest known implementation in the literature based on results. • Online attack of 40-bit DES in 30.8 seconds.

  11. Data Analysis • Performance-Cost Analysis • Determine the FPGA chip that provides the highest performance for the lowest cost. • Synthesized the hardware designs for various Xilinx FPGAs. • Spartan 3 S-1500 provides the highest performance-cost relative to other Xilinx® FPGA chips. • Extrapolate the design of a machine to break DES (56-bit key length) • Result: DES can be broken with 85% success probability in 72 minutes for an approximate cost of US $1,210. Performance-Cost of Precomputation Hardware System

  12. Conclusion • FPGAs provides a low cost and effective solution to cryptanalysis. • Rainbow table attacks provide a faster attack time compared to brute-force, but brute-force uses less resources, that is, memory resources. • For large key sizes, the rainbow table attack becomes infeasible as memory costs is prohibitive.

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