Memory-hard function: Difference between revisions

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{{short description|Type of cryptographic algorithm}}In [[cryptography]], a '''memory-hard function''' ('''MHF''') is a function that costs a significant amount of [[random-access memory|memory]] to efficiently evaluate.<ref name=":0">{{Cite thesis |title=Memory-Hard Functions: When Theory Meets Practice |url=https://escholarship.org/uc/item/7x4630qv |publisher=UC Santa Barbara |date=2019 |language=en |first=Binyi |last=Chen}}</ref> It differs from a [[memory-bound function]], which incurs cost by slowing down computation through memory latency.<ref>{{Cite book |last1=Dwork |first1=Cynthia |last2=Goldberg |first2=Andrew |last3=Naor |first3=Moni |date=2003 |editor-last=Boneh |editor-first=Dan |chapter=On Memory-Bound Functions for Fighting Spam |title=Advances in Cryptology - CRYPTO 2003 |series=Lecture Notes in Computer Science |language=en |___location=Berlin, Heidelberg |publisher=Springer |pages=426–444 |doi=10.1007/978-3-540-45146-4_25 |isbn=978-3-540-45146-4|doi-access=free }}</ref> MHFs have found use in [[key stretching]] and [[proof of work]] as their increased memory requirements significantly reduce the computational efficiency advantage of custom hardware over general-purpose hardware compared to non-MHFs.<ref name=":1">{{Cite web |last=LIU |first=ALEC |date=2013-11-29 |title=Beyond Bitcoin: A Guide to the Most Promising Cryptocurrencies |url=https://www.vice.com/en/article/beyond-bitcoin-a-guide-to-the-most-promising-cryptocurrencies/ |access-date=2023-09-30 |website=Vice |language=en}}</ref><ref name=":0" />

In [[cryptography]], a '''memory hard function''' (MHF) is a function that costs a significant amount of memory to evaluate. It is different from [[memory bound function]]s, the latter incurs cost by slowing down computation through memory latency. MHFs find their use as a form of [[Proof of work|proof-of-work]].

== Memory hard measureIntroduction ==

MHFs are designed to consume large amounts of memory on a computer in order to reduce the effectiveness of [[parallel computing]]. In order to evaluate the function using less memory, a significant time penalty is incurred. As each MHF computation requires a large amount of memory, the number of function computations that can occur simultaneously is limited by the amount of available memory. This reduces the efficiency of specialised hardware, such as [[application-specific integrated circuit]]s and [[Graphics processing unit|graphics processing units]], which utilise parallelisation, in computing a MHF for a large number of inputs, such as when [[Brute-force attack|brute-forcing]] password hashes or [[Cryptocurrency|mining cryptocurrency]].<ref name=":0" /><ref name=":2">{{Cite book |last1=Biryukov |first1=Alex |last2=Khovratovich |first2=Dmitry |date=2015 |editor-last=Iwata |editor-first=Tetsu |editor2-last=Cheon |editor2-first=Jung Hee |chapter=Tradeoff Cryptanalysis of Memory-Hard Functions |title=Advances in Cryptology – ASIACRYPT 2015 |series=Lecture Notes in Computer Science |language=en |___location=Berlin, Heidelberg |publisher=Springer |pages=633–657 |doi=10.1007/978-3-662-48800-3_26 |isbn=978-3-662-48800-3|doi-access=free }}</ref>

There are different ways to measure the memory hardness of a function. A commonly seen measure is Cumulative Memory Complexity (CMC). In a parallel model, CMC measures memory hardness by summing up all the inputs on each step. <ref>(AS15) Alwen, Serbineko, [https://eprint.iacr.org/2014/238.pdf ''High Parallel Complexity Graphs and Memory-Hard Functions''], 2015</ref>

== Motivation and examples ==

Another viable measure is integrating memory against physical time.<ref>(MO16) Moran, Orlov, [https://eprint.iacr.org/2016/035.pdf ''Simple Proofs of Space-Time and Rational Proofs of Storage''], 2016</ref>

[[Bitcoin]]'s proof-of-work uses repeated evaluation of the [[SHA-2|SHA-256]] function, but modern general-purpose processors, such as off-the-shelf [[central processing unit|CPUs]], are inefficient when computing a fixed function many times over. Specialized hardware, such as application-specific integrated circuits (ASICs) designed for Bitcoin mining, can use 30,000 times less energy per hash than [[x86]] CPUs whilst having much greater hash rates.<ref name=":2" /> This led to concerns about the centralization of mining for Bitcoin and other cryptocurrencies.<ref name=":2" /> Because of this inequality between miners using ASICs and miners using CPUs or off-the shelf hardware, designers of later proof-of-work systems utilised hash functions for which it was difficult to construct ASICs that could evaluate the hash function significantly faster than a CPU.<ref name=":1" />

As memory cost is platform-independent,<ref name=":0" /> MHFs have found use in cryptocurrency mining, such as for [[Litecoin]], which uses [[scrypt]] as its hash function.<ref name=":1" /> They are also useful in password hashing because they significantly increase the cost of trying many possible passwords against a leaked database of hashed passwords without significantly increasing the computation time for legitimate users.<ref name=":0" />

Yet another measure is the memory bandwidth consumption on a memory bus.<ref>(BR18) Blocki, Ren, [https://eprint.iacr.org/2018/221.pdf ''Bandwidth-Hard Functions: Reductions and Lower Bounds''], 2018</ref> This category of functions are also dubbed "Bandwidth-hard functions".

== Measuring memory hardness ==

== Motivation ==

There are differentvarious ways to measure the memory hardness of a function. AOne commonly seen measure is Cumulativecumulative Memorymemory Complexitycomplexity (CMC). In a parallel model, CMC measuresis memorythe hardnesssum byof summingthe upmemory allrequired theto inputscompute ona eachfunction over every time step. of the computation.<ref>(AS15) Alwen, Serbineko, [https://eprint.iacr.org/2014/238.pdf ''High Parallel Complexity Graphs and Memory-Hard Functions''], 2015</ref><ref>{{cite arXiv |eprint=1705.05313 |class=cs.CR |first1=Joel |last1=Alwen |first2=Jeremiah |last2=Blocki |title=Sustained Space Complexity |date=2017-07-07 |last3=Pietrzak |first3=Krzysztof}}</ref>

There is a reason why MHFs cost a lot of memory instead of, say, CPU cycles.

Other viable measures include integrating memory usage against time and measuring memory [[bandwidth (computing)|bandwidth]] consumption on a memory bus. Functions requiring high memory bandwidth are sometimes referred to as "bandwidth-hard functions".<ref>{{Cite web |last1=Blocki |first1=Jeremiah |last2=Liu |first2=Peiyuan |last3=Ren |first3=Ling |last4=Zhou |first4=Samson |date=2022 |title=Bandwidth-Hard Functions: Reductions and Lower Bounds |url=https://eprint.iacr.org/2018/221.pdf |url-status=live |archive-url=https://web.archive.org/web/20230112040047/https://eprint.iacr.org/2018/221.pdf |archive-date=2023-01-12 |access-date=2023-01-11 |website=[[Cryptology ePrint Archive]]}}</ref>

== Variants ==

MHFs can be categorized into two different groups based on their evaluation patterns: data-dependent memory-hard functions (dMHF) and data-independent memory-hard functions (iMHF). As opposed to iMHFs, the memory access pattern of a dMHF depends on the function input, such as the password provided to a key derivation function.<ref>{{Cite book |last1=Blocki |first1=Jeremiah |last2=Harsha |first2=Ben |last3=Kang |first3=Siteng |last4=Lee |first4=Seunghoon |last5=Xing |first5=Lu |last6=Zhou |first6=Samson |date=2019 |editor-last=Boldyreva |editor-first=Alexandra |editor2-last=Micciancio |editor2-first=Daniele |chapter=Data-Independent Memory Hard Functions: New Attacks and Stronger Constructions |chapter-url=https://link.springer.com/chapter/10.1007/978-3-030-26951-7_20 |title=Advances in Cryptology – CRYPTO 2019 |series=Lecture Notes in Computer Science |language=en |___location=Cham |publisher=Springer International Publishing |pages=573–607 |doi=10.1007/978-3-030-26951-7_20 |isbn=978-3-030-26951-7}}</ref> Examples of dMHFs are [[scrypt]] and [[Argon2]]d, while examples of iMHFs are [[Argon2]]i and [[catena (cryptography)|catena]]. Many of these MHFs have been designed to be used as [[key derivation function|password hashing function]]s because of their memory hardness.

Based on their evaluation patterns, MHFs can be put into two camps: data-dependent MHFs (dMHF) and data-independent MHFs (iMHF). Examples of dMHFs are [[scrypt]], [[argon2]]d. Examples of iMHFs are [[argon2]]i, [[catena]]. Many of these MHFs are developed to be used as [[key derivation function]]s exactly because of their memory hardness.

A notable problem with dMHFs is that they are prone to [[side-channel attack]]s such as cache timing. This has resulted in a preference for using iMHFs when hashing passwords. However, iMHFs have been mathematically proven to have weaker memory hardness properties than dMHFs.<ref>Alwen, J., Blocki, J. (2016). [https://doi.org/10.1007/978-3-662-53008-5_9''Efficiently Computing Data-Independent Memory-Hard Functions.'']</ref>

== References ==

{{Reflist}}

[[Category:Cryptography]]

== References ==