Internet Draft Hilarie Orman draft-orman-public-key-lengths-02.txt Novell, Inc. March 19, 2001 Paul Hoffman Expires in six months IMC & VPNC Determining Strengths For Public Keys Used For Exchanging Symmetric Keys Status of this memo This document is an Internet-Draft and is in full conformance with all provisions of Section 10 of RFC2026. Internet-Drafts are working documents of the Internet Engineering Task Force (IETF), its areas, and its working groups. Note that other groups may also distribute working documents as Internet-Drafts. Internet-Drafts are draft documents valid for a maximum of six months and may be updated, replaced, or obsoleted by other documents at any time. It is inappropriate to use Internet-Drafts as reference material or to cite them other than as "work in progress." The list of current Internet-Drafts can be accessed at http://www.ietf.org/ietf/1id-abstracts.txt The list of Internet-Draft Shadow Directories can be accessed at http://www.ietf.org/shadow.html. Abstract Implementors of systems that use public key cryptography to exchange symmetric keys need to make the public keys resistant to some predetermined level of attack. That level of attack resistance is the strength of the system, and the symmetric keys that are exchanged must be at least as strong as the system strength requirements. The three quantities, system strength, symmetric key strength, and public key strength, must be consistently matched for any network protocol usage. While it is fairly easy to express the system strength requirements in terms of a symmetric key length and to choose a cipher that has a key length equal to or exceeding that requirement, it is harder to choose a public key that has a cryptographic strength meeting a symmetric key strength requirement. This document explains how to determine the length of an asymmetric key as a function of the length of a symmetric key. Some rules of thumb for estimating equivalent resistance to large-scale attacks on various algorithms are given. The document also addresses how changing the sizes of the underlying large integers (moduli, group sizes, exponents, and so on) changes the time to use the algorithms for key exchange. 1. Model of Protecting Symmetric Keys with Public Keys Many books on cryptography and security explain the need to exchange symmetric keys in public as well as the many algorithms that are used for this purpose. However, few of these discussions explain how the strengths of the public keys and the symmetric keys are related. To understand this, picture a house with a strong lock on the front door. Next to the front door is a small lockbox that contains the key to the front door. A would-be burglar who wants to break into the house through the front door has two options: attack the lock on the front door, or attack the lock on the lockbox in order to retrieve the key. Clearly, the burglar is better off attacking the weaker of the two locks. The homeowner in this situation must make sure that adding the second entry option (the lockbox containing the front door key) is at least as strong as the lock on the front door in order not to make the burglar's job easier. An implementor designing a system for exchanging symmetric keys using public key cryptography must make a similar decision. Assume that an attacker wants to learn the contents of a message that is encrypted with a symmetric key, and that the symmetric key was exchanged between the sender and recipient using public key cryptography. The attacker has two options to recover the message: a brute-force attempt to determine the symmetric key by repeated guessing, or mathematical determination of the private key used as the key exchange key. A smart attacker will work on the easier of these two problems. A simple-minded answer to the implementor's problem is to be sure that the key exchange system is always significantly stronger than the symmetric key; this can be done by choosing a very long public key. Such a design is usually not a good idea because the key exchanges become much more expensive in terms of processing time as the length of the public keys go up. Thus, the implementor is faced with the task of trying to match the difficulty of an attack on the symmetric key with the difficulty of an attack on the public key encryption. This analysis is not unnecessary if the key exchange can be performed with extreme security for almost no cost in terms of elapsed time or CPU effort; unfortunately, this is no the case for public key methods today. A third consideration is the minimum security requirement of the user. Assume the user is encrypting with CAST-128 and requires a symmetric key with a resistance time against brute-force attack of 20 years. He might start off by choosing a key with 86 random bits, and then use a one-way function such as SHA-1 to "boost" that to a block of 160 bits, and then take 128 of those bits as the key for CAST-128. In such a case, the key exchange algorithm need only match the difficulty of 86 bits, not 128 bits. The selection rule is: 1. Determine the number of symmetric key bits matching the security requirement of the application (n). 2. Choose a symmetric cipher that has a key with at least n bits, and a cryptanalytic strength of at least that much. 3. Choose a key exchange algorithm with a resistance to attack of at least n bits. A fourth consideration might be the public key authentication method used to establish the identity of a user. This might be an RSA digital signature or a DSA digital signature. If the modulus for the authentication method isn't large enough, then the entire basis for trusting the communication might fall apart. The following step is thus added: 4. Choose an authentication algorithm with a resistance to attack of at least n bits. 1.2 The key exchange algorithms The Diffie-Hellman method uses a group, a generator, and exponents. In today's Internet standards, the group operation is based on modular multiplication. Here, the group is defined by the multiplicative group of an integer, typically a prime p = 2q + 1, where q is a prime, and the arithmetic is done modulo p; the generator (which is often simply 2) is denoted by g. In Diffie-Hellman, Alice and Bob first agree (in public or in private) on the values for g and p. Alice chooses a secret large random integer (a), and Bob chooses a secret random large integer (b). Alice sends Bob A, which is g^a mod p; Bob sends Alice B, which is g^b mod p. Next, Alice computes B^a mod p, and Bob computes A^b mod p. These two numbers are equal, and the participants use a simple function of this number as the symmetric key k. Note that Diffie-Hellman key exchange can be done over different kinds of group representations. For instance, elliptic curves defined over finite fields are a particularly efficient way to compute the key exchange [SCH95]. For RSA key exchange, assume that Bob has a public key (m) which is equal to p*q, where p and q are two secret prime numbers, and an encryption exponent e, and a decryption exponent d. For the key exchange, Alice sends Bob E = k^e mod m, where k is the secret symmetric key being exchanged. Bob recovers k by computing E^d mod m, and the two parties use k as their symmetric key. While Bob's encryption exponent e can be quite small (e.g., 17 bits), his decryption exponent d will have as many bits in it as m does. 2. Determining the Effort to Factor The RSA public key encryption method is immune to brute force guessing attacks because the modulus will have at least 512 bits. The Diffie- Hellman exchange is also secure against guessing because the exponents will have at least twice as many bits as the symmetric keys that will be derived from them. However, both methods are susceptible to mathematical attacks that determine the structure of the public keys. Factoring an RSA modulus will result in complete compromise of the security of the private key. Solving the discrete logarithm problem for a Diffie-Hellman modular exponentiation system will similarly destroy the security of all key exchanges using the particular modulus. This document assumes that the difficulty of solving the discrete logarithm problem is equivalent to the difficulty of factoring numbers that are the same size as the modulus. In fact, it is slightly harder because it requires more memory; based on empirical evidence so far, the ratio of difficulty is at least 20, possibly as high as 64. Solving either problem requires a great deal of memory for the last stage of the algorithm, the matrix reduction step. Whether or not this memory requirement will be the limiting factor in solving larger integer problems remains to be seen. At the current time it is not, and advances in parallel matrix algorithms are expected to mitigate the memory requirements in the near future. Nearly all cryptographers consider the number field sieve (NFS) [GOR93] [LEN93] the best method today for solving the discrete logarithm problem. The formula for estimating the number of simple arithmetic operations needed to factor an integer, n, using the NFS method is: L(n) = k * e^((1.92 + o(1)) * cubrt(ln(n) * (ln(ln(n)))^2)) Many people prefer to discuss the number of MIPS years (MYs) that are needed for large operations such as the number field sieve. For such an estimation, an operation in the L(n) formula is one computer instruction. Empirical evidence indicates that 4 or 5 instructions might be a closer match, but this is a minor factor and this document sticks with one operation/one instruction for this discussion. 2.1 Choosing parameters for the equation The expression above has two parameters that must be estimated by empirical means: k and o(1). Different authors take different approaches to choosing the parameters: - Some authors assume that k is 1 and o(1) is 0. This is reasonably valid if the expression is only used for estimating relative effort (instead of actual effort) and one assumes that the o(1) term is very small over the range of the numbers that are to be factored. - Other authors implicitly assume that o(1) is small and roughly constant and thus its value can be folded into k; they then estimate k from reported amounts of effort spent factoring large integers in tests. This document uses the second approach. Sample values from recent work with the number field sieve, collected by RSA Labs, include: Test name Number of Number of MYs of effort decimal bits digits RSA130 130 430 500 RSA140 140 460 2000 RSA155 155 512 8000 There are no precise measurements of the amount of time used for these factorizations. In most factorization tests, hundreds or thousands of computers are used over a period of several months, but the number of their cycles were used for the factoring project, the precise distribution of processor types, speeds, and so on are not usually reported. However, in all cases, the amount of effort used was far less than the L(n) formula would predict if k was 1 and o(1) was 0. 2.2 Choosing k from empirical reports By solving for k from the empirical reports, it appears that k is approximately 0.02. This means that the "effective key strength" of the RSA algorithm is about 5.5 bits less than is implied by the naive application of equation L(n) (that is, setting k to 1 and o(1) to 0). These estimates of k are fairly stable over the numbers reported in the table. The estimate is limited to a single significant digit of k because it expresses real uncertainties; however, the effect of additional digits would have make only tiny changes to the recommended key sizes. The factorers of RSA130 used about 1700 MYs, but they felt that this was unrealistically high for prediction purposes; by using more memory on their machines, they could have easily reduced the time to 500 MYs. Thus, the value used in preparing the table above was 500. This story does, however, underscore the difficulty in getting an accurate measure of effort. This document takes the reported effort for factoring RSA155 as being the most accurate measure. As a result of examining the empirical data, it appears that the L(n) formula can be used with the o(1) term set to 0 and with k set to 0.02 when talking about factoring numbers in the range of 100 to 200 decimal digits. The equation becomes: L(n) = 0.02 * e^(1.92 * cubrt(ln(n) * (ln(ln(n)))^2)) To convert L(n) from simple math instructions to MYs, divide by 3*10^13. The equation for the number of MYs needed to factor an integer n then reduces to: MYs = 6 * 10^(-16) * e^(1.92 * cubrt(ln(n) * (ln(ln(n)))^2)) With what confidence can this formula be used for predicting the difficulty of factoring slightly larger numbers? The answer is that it should be a close upper bound, but each factorization effort is usually marked by some improvement in the algorithms or their implementations that makes the running time somewhat shorter than the formula would indicate. 2.3 Pollard's rho method In Diffie-Hellman exchanges, there is a second attack, Pollard's rho method [POL78]. The algorithm relies on finding collisions between values computed in a large number space; its success rate is proportional to the square root of the size of the space. Because of Pollard's rho method, the search space in a DH key exchange for the key (the exponent in a g^a term), must be twice as large as the symmetric key. Therefore, to securely derive a key of K bits, an implementation must use an exponent with at least 2*K bits. When the Diffie-Hellman key exchange is done using an elliptic curve method, the NFS methods are of no avail. However, the collision method is still effective, and the need for an exponent (called a multiplier in EC's) with 2*K bits remains. However, the modulus used for the computation can also be 2*K bits, and this will be substantially smaller than the modulus needed for modular exponentiation methods as the desired security level increases past 64 bits of brute-force attack resistance. 2.4 Limits of large memory and many machines Robert Silverman has examined the question of when it will be practical to factor RSA moduli larger than 512 bits. His is based not just on the theoretical number of operations that underlies this document, but it includes expectations about the availability of actual machines for performing the work. He examine the question of whether or not we can expect there be enough machines, memory, and communication to factor a very large number. The best factoring methods need a lot of random access memory for collecting data relations (sieving) and a critical final step that does a row reduction on a large matrix. The memory requirements are related to the size of the number being factored (or subjected to discrete logarithm solution). Silverman [Silv2000] has argued that there is a practical limit to the number of machines and the amount of RAM that be brought to bear on a single problem in the foreseeable future. He sees two problems in attacking a 1024-bit RSA modulus: the machines doing the sieving will need 64-bit address spaces and the matrix row reduction machine will need 6 terabytes of memory. Silverman notes that very few 64-bit machines have been sold, and none of those machines have the 170 gigabytes of memory needed for sieving. Nearly a billion such machines are necessary for the sieving in a reasonable amount of time (a year or two). Silverman's conclusion is that 1024-bit RSA moduli will not be factored until about 2037. This implies a much longer lifetime to RSA keys than the theoretical analysis indicates. He argues that predictions about how many machines and memory modules will be available can be with great confidence, based on Moore's Law extrapolations and the recent history of factoring efforts. One should give the practical considerations a great deal of weight, but in a risk analysis, perhaps the physical world is less predicatable than trend graphs would indicate. In considering how much trust to put into the inability of the computer industry to satisfy the voracious needs of factorers, one must have some insight into economic considerations that are more complicated than the mathematics of factoring. The demand for computer memory is hard to predict because it is based on applications - a "killer app" might come along any day and send the memory industry into a frenzy of sales. The number of processors available on desktops may be limited by the number of desks, but very capable embedded systems account for more processor sales than desktops. As embedded systems absorb networking functions, it is not unimaginable that millions of 64-bit processors with gigabytes of memory will pervade our environment. The bottom line on this is that the key length recommendations predicted by theory may be overly conservative. This question is one that should be reconsidered in light of current technology on a regular basis. 2.5 Strong Enough Key, Not Enough Bits If the key exchange or data protection method has a strength matched to the strength of the needed symmetric key, there remains one possible additional step, and that is to securely derive the actual symmetric key. The usual recommendation is to use a good one-way hash function applied to he base material (the result of the key exchange) and to use a subset of the hash function output for the key. However, if the desired key length is greater than the output of the hash function, one might wonder how to reconcile the two. The step of deriving extra key bits must satisfy these requirements: - The bits must not reveal any information about the key exchange secret - The bits must not be correlated with each other - The bits must depend on all the bits of the key exchange secret Any good cryptographic hash function satisfies these three requirements. Note that the number of bits of output of the hash function is not specified. That is because even a hash function with a very short output can be iterated to produce more uncorrelated bits with just a little bit of care. Appendix B of [RFC2409] describes how to derive long keys from short hash functions. Note that this does not increase the key strength at all; it just produces a good, safe, set of bits for a long key. The trick is to make sure the hash function is applied repeatedly to all the bits of the key exchange and one or more additional varying (but not secret) bits. At each stage, the output bits of the hash function can be collected into the output key bits. The RFC 2409 method gets the additional bits from the output of the previous stage: K1 = hash(keyexchangesecret | 0 ) K2 = hash(keyexchangesecret | K1) . . . KN = hash(keyexchangesecret | KN-1) This concatenation of K1 through KN constitutes a good set of key bits. 3. Time to Use the Algorithms This section describes how long it takes to use the algorithms to perform key exchanges. Again, it is important to consider the increased time it takes to exchange symmetric keys when increasing the length of public keys in order to not choose unfeasibly long public keys. 3.1 Diffie-Hellman Key Exchange A Diffie-Hellman key exchange is done with a group G with a generator g and an exponent x. As noted in the Pollard's rho method section, the exponent has twice as many bits as are needed for the final key. Let the size of the group G be p, let the number of bits in the base 2 representation of p be j, and let the number of bits in the exponent be K. In doing the operations that result in a shared key, a generator is raised to a power. The most efficient way to do this involves squaring a number K times and multiplying it several times along the way. Each of the numbers has j/w computer words in it, where w is the number of bits in a computer word (today that will be 32 or 64 bits). A naive assumption is that you will need to do j squarings and j/2 multiplies; fortunately, an efficient implementation will need fewer. For the remainder of this section, n represents j/w. A squaring operation does not need to use quite as many operations as a multiplication; a reasonable estimate is that squaring takes .6 the number of machine instructions of a multiply. If one prepares a table ahead of time with several values of small integer powers of the generator g, then only about one fifth as many multiplies are needed as the naive formula suggests. Therefore, one needs to do the work of approximately .8*K multiplies of n-by-n word numbers. Further, each multiply and squaring must be followed by a modular reduction, and a good assumption is that it is as hard to do a modular reduction as it is to do an n-by-n word multiply. Thus, it takes K reductions for the squarings and .2*K reductions for the multiplies. Summing this, the total effort for a Diffie-Hellman key exchange with K bit exponents and a modulus of n words is approximately 2*K n-by-n-word multiplies. For 32-bit processors, integers that use less than about 30 computer words in their representation require at least n^2 instructions for an n-by-n-word multiply. Larger numbers will use less time, using Karatsuba multiplications, and they will scale as about n^(1.58) for larger n, but that is ignored for the current discussion. Note that 64- bit processors push the "Karatsuba cross-over" number out to even more bits. The basic result is: if you double the size of the Diffie-Hellman modular exponentiation group, you quadruple the number of operations needed for the computation. 3.1.1 Diffie-Hellman with elliptic curve groups Note that the ratios for computation effort as a function of modulus size hold even if you are using an elliptic curve (EC) group for Diffie-Hellman. However, for equivalent security, one can use smaller numbers in the case of elliptic curves. Assume that someone has chosen an modular exponentiation group with an 2048 bit modulus as being an appropriate security measure for a Diffie-Hellman application and wants to determine what advantage there would be to using an EC group instead. The calculation is relatively straightforward, if you assume that on the average, it is about 20 times more effort to do a squaring or multiplication in an EC group than in a modular exponentiation group. A rough estimate is that an EC group with equivalent security has about 200 bits in its representation. Then, assuming that the time is dominated by n-by-n- word operations, the relative time is computed as: ((2048/200)^2)/20 ~= 5 showing that an elliptic curve implementation should be five times as fast as a modular exponentiation implementation. 3.2 RSA encryption and decryption Assume that an RSA public key uses a modulus with j bits; its factors are two numbers of about j/2 bits each. The expected computation time for encryption and decryption are different. Denote the number of words in the machine representation of the modulus by the symbol n. Most implementations of RSA use a small exponent for encryption. An encryption may involve as few as 16 squarings and one multiplication, using n-by-n-word operations. Each operation must be followed by a modular reduction, and therefore the time complexity is about 16*(.6 + 1) + 1 + 1 ~= 28 n-by-n-word multiplies. RSA decryption must use an exponent that has as many bits as the modulus, j. However, the Chinese Remainder Theorem applies, and all the computations can be done with a modulus of only n/2 words and an exponent of only j/2 bits. The computation must be done twice, once for each factor. The effort is equivalent to 2*(j/2) (n/2 by n/2)-word multiplies. Because multiplying numbers with n/2 words is only 1/4 as difficult as multiplying numbers with n words, the equivalent effort for RSA decryption is j/4 n-by-n-word multiplies. If you double the size of the modulus for RSA, the n-by-n multiplies will take four times as long. Further, the decryption time doubles because the exponent is larger. The overall scaling cost is a factor of 4 for encryption, a factor of 8 for decryption. 3.3 Real-world examples To make these numbers more real, here are a few examples of software implementations run on current hardware. The examples are included to show rough estimates of reasonable implementations; they are not benchmarks. As with all software, the performance will depend on the exact details of specialization of the code to the problem and the specific hardware. The best time informally reported for a 1024-bit modular exponentiation (the decryption side of 2048-bit RSA), is 0.9 ms (about 450,000 CPU cycles) on a 500 MHz Itanium processor. This shows that newer processors are not losing ground on big number operations; the number of instructions is less than a 32-bit processor uses for a 256-bit modular exponentiation. For less advanced processors timing, the following two tables (computed by Tero Monenen at SSH Communications) for modular exponentiation, such as would be done in a Diffie-Hellman key exchange. Celeron 400 MHz; compiled with GNU C compiler, optimized, some platform specific coding optimizations: group modulus exponent time type size size mod 768 ~150 18 msec mod 1024 ~160 32 msec mod 1536 ~180 82 msec ecn 155 ~150 35 msec ecn 185 ~200 56 msec The group type is from RFC2409 and is either modular exponentiation ("mod") or elliptic curve ("ecn"). All sizes here and in subsequent tables are in bits. Alpha 500 MHz compiled with Digital's C compiler, optimized, no platform specific code: group modulus exponent time type size size mod 768 ~150 12 msec mod 1024 ~160 24 msec mod 1536 ~180 59 msec ecn 155 ~150 20 msec ecn 185 ~200 27 msec The following two tables (computed by Eric Young) were originally for RSA signing operations, using the Chinese Remainder representation. For ease of understanding, the parameters are presented here to show the interior calculations, i.e., the size of the modulus and exponent used by the software. Dual Pentium II-350: equiv equiv equiv modulus exponent time size size 256 256 1.5 ms 512 512 8.6 ms 1024 1024 55.4 ms 2048 2048 387 ms Alpha 264 600mhz: equiv equiv equiv modulus exponent time size size 512 512 1.4 ms Current chips that accelerate exponentiation can perform 1024-bit exponentiations (1024 bit modulus, 1024 bit exponent) in about 3 milliseconds. 4. Equivalences of Key Sizes In order to determine how strong a public key is needed to protect a particular symmetric key, you first need to determine how much effort is needed to break the symmetric key. Most Internet security protocols require the use of TripleDES for strong symmetric encryption, and it is expected that the Advanced Encryption Standard (AES) will be adopted on the Internet in the coming years. Therefore, these two algorithms are discussed here. If one could simply determine the number of MYs it takes to break TripleDES, the task of computing the public key size of equivalent strength would be easy. Unfortunately, that isn't the case here because there are many examples of DES-specific hardware that encrypt faster than DES in software on a standard CPU. Instead, one must determine the equivalent cost for a system to break TripleDES and a system to break the public key protecting a TripleDES key. In 1998, the Electronic Frontier Foundation (EFF) built a DES-cracking machine [GIL98] for US$130,000 that could test about 1e11 DES keys per second (additional money was spent on the machine's design). The machine's builders fully admit that the machine is not well optimized, and it is estimated that ten times the amount of money could probably create a machine about 50 times as fast. Assuming more optimization by guessing that a system to test TripleDES keys runs about as fast as a system to test DES keys, so approximately US$1 million might test 5e12 TripleDES keys per second. In case your adversaries are much richer than EFF, you may want to assume that they have US$1 trillion, enough to test 5e18 keys per second. An exhaustive search of the TripleDES space of 2^112 keys with this quite expensive system would take about 1e15 seconds or about 33 million years. (Note that such a system would also need 2^60 bytes of RAM [MH81], which is considered free in this calculation). This seems a needlessly conservative value. However, if computer logic speeds continue to increase in accordance with Moore's Law (doubling in speed every 1.5 years), then one might expect that in about 50 years, the computation could be completed in only one year. For the purposes of illustration, this 50 year resistance against a trillionaire is assumed to be the minimum security requirement for a set of applications. If 112 bits of attack resistance is the system security requirement, then the key exchange system for TripleDES should have equivalent difficulty; that is to say, if the attacker has US$1 trillion, you want him to spend all his money to buy hardware today and to know that he will "crack" the key exchange in not less than 33 million years. (Obviously, a rational attacker would wait for about 45 years before actually spending the money, because he could then get much better hardware, but all attackers benefit from this sort of wait equally.) It is estimated that a typical PC CPU today can generate about 500 MIPs and can be purchased for about US$100 in quantity; thus you get about 5 MIPs/US$. For one trillion US dollars, an attacker can get 5e12 MIP years of computer instructions. This figure is used in the following estimates of equivalent costs for breaking key exchange systems. 4.1 Key equivalence against special purpose brute force hardware If the trillionaire attacker is to use conventional CPU's to "crack" a key exchange for a 112 bit key in the same time that the special purpose machine is spending on brute force search for the symmetric key, the key exchange system must use an appropriately large modulus. Assume that the trillionaire performs 5e12 MIPs of instructions per year. Use the following equation to estimate the modulus size to use with RSA encryption or DH key exchange: 5*10^33 = (6*10^-16)*e^(1.92*cubrt(ln(n)*(ln(ln(n)))^2)) Solving this approximately for n yields: n = 10^(625) = 2^(2077) Thus, assuming similar logic speeds and the current efficiency of the number field sieve, moduli with about 2100 bits will have about the same resistance against attack as an 112-bit TripleDES key. This indicates that RSA public key encryption should use a modulus with around 2100 bits; for a Diffie-Hellman key exchange, one could use a slightly smaller modulus, but it not a significant difference. 4.2 Key equivalence against conventional CPU brute force attack An alternative way of estimating this assumes that the attacker has a less challenging requirement: he must only "crack" the key exchange in less time than a brute force key search against the symmetric key would take with general purpose computers. This is an "apples-to-apples" comparison, because it assumes that the attacker needs only to have computation donated to his effort, not built from a personal or national fortune. The public key modulus will be larger than the one in 4.1, because the symmetric key is going to be viable for a longer period of time. Assume that the number of congenial CPU instructions to encrypt a block of material using TripleDES is 300. The estimated number of computer instructions to break 112 bit TripleDES key: 300 * 2^112 = 1.6 * 10^(36) = .02*e^(1.92*cubrt(ln(n)*(ln(ln(n)))^2)) Solving this approximately for n yields: n = 10^(734) = 2^(2439) Thus, for general purpose CPU attacks, you can assume that moduli with about 2400 bits will have about the same strength against attack as an 112-bit TripleDES key. This indicates that RSA public key encryption should use a modulus with around 2400 bits; for a Diffie-Hellman key exchange, one could use a slightly smaller modulus, but it not a significant difference. Note that some authors assume that the algorithms underlying the number field sieve will continue to get better over time. These authors recommend an even larger modulus, over 4000 bits, for protecting a 112- bit symmetric key for 50 years. This points out the difficulty of long-term cryptographic security: it is all but impossible to predict progress in mathematics and physics over such a long period of time. 4.3 A One Year Attack Assuming a trillionaire spends his money today to buy hardware, what size key exchange numbers could he "crack" in one year? He can perform 5*e12 MYs of instructions, or 3*10^13 * 5*10^12 = .02*e^(1.92*cubrt(ln(n)*(ln(ln(n)))^2)) Solving for an approximation of n yields n = 10^(360) = 2^(1195) This is about as many operations as it would take to crack an 80-bit symmetric key by brute force. Thus, for protecting data that has a secrecy requirement of one year against an incredibly rich attacker, a key exchange modulus with about 1200 bits protecting an 80-bit symmetric key is safe even against a nation's resources. 4.4 Key equivalence for other ciphers Extending this logic to the AES is straightforward. For purposes of estimation for key searching, one can think of the 128-bit AES as being at least 16 bits stronger than TripleDES but about 5 times as fast. The time and cost for a brute force attack is approximately 2^(14) more than for TripleDES, and thus the recommended key exchange modulus sizes are more than 600 bits longer (based on the difficulty of breaking a discrete log). If it is possible to design hardware for AES cracking that is considerably more efficient than hardware for DES cracking, then the moduli for protecting the key exchange can be made smaller. However, the existence of such designs is only a matter of speculation at this early moment in the AES lifetime. The AES ciphers have key sizes of 128 bits up to 256 bits. Should a prudent minimum security requirement, and thus the key exchange moduli, have similar strengths? The answer to this depends on whether or not one expect Moore's Law to continue unabated. If it continues, one would expect 128 bit keys to be safe for about 60 years, and 256 bit keys would be safe for another 400 years beyond that, far beyond any imaginable security requirement. But such progress is difficult to predict, as it exceeds the physical capabilities of today's devices and would imply the existence of logic technologies that are unknown or infeasible today. Quantum computing is a candidate, but too little is known today to make confident predictions about its applicability to cryptography (which itself might change over the next 100 years!). If Moore's Law does not continue to hold, if no new computational paradigms emerge, then keys of over 100 bits in length might well be safe "forever". Note, however that others have come up with estimates based on assumptions of new computational paradigms emerging. For example, Lenstra and Verheul's web-based paper "Selecting Cryptographic Key Sizes" chooses a more conservative analysis than the one in this document. 4.5 Table of effort comparisons In this table it is assumed that attackers use general purpose computers, that the hardware is purchased in the year 2000, and that mathematical knowledge relevant to the problem remains the same as today. This is an pure "apples-to-apples" comparison demonstrating how the time for a key exchange scales with respect to the strength requirement. The subgroup size for DSA is included, if that is being used for supporting authentication as part of the protocol; the DSA modulus must be as long as the DH modulus, but the size of the "q" subgroup is also relevant. Symm. key RSA or DH DSA subgroup size modulus size size (bits) (bits) (bits) 70 947 128 80 1228 145 90 1553 153 100 1926 184 150 4575 279 200 8719 373 250 14596 475 5. Security Considerations The equations and values given in this document are meant to be as accurate as possible, based on the state of the art in general purpose computers at the time that this document is being written. No predictions can be completely accurate, and the formulas given here are not meant to be definitive statements of fact about cryptographic strengths. For example, some of the empirical results used in calibrating the formulas in this document are probably not completely accurate, and this inaccuracy affects the estimates. It is the authors' hope that the numbers presented here vary from real world experience as little as possible. 6. References [DL] B. Dodson, A.K. Lenstra, NFS with four large primes: an explosive experiment, Proceedings Crypto 95, Lecture Notes in Comput. Sci. 963, (1995) 372-385. [GIL98] Cracking DES: Secrets of Encryption Research, Wiretap Politics & Chip Design , Electronic Frontier Foundation, John Gilmore (Ed.), 272 pages, May 1998, O'Reilly & Associates; ISBN: 1565925203 [GOR93] D. Gordon, "Discrete logarithms in GF(p) using the number field sieve", SIAM Journal on Discrete Mathematics, 6 (1993), 124-138. [LEN93] A. K. Lenstra, H. W. Lenstra, Jr. (eds), The development of the number field sieve, Lecture Notes in Math, 1554, Springer Verlag, Berlin, 1993. [MH81] Merkle, R.C., and Hellman, M., "On the Security of Multiple Encryption", Communications of the ACM, v. 24 n. 7, 1981, pp. 465-467. [ODL95] RSA Labs Cryptobytes, Volume 1, No. 2 - Summer 1995; The Future of Integer Factorization, A. M. Odlyzko [ODL99] A. M. Odlyzko, Discrete logarithms: The past and the future, Designs, Codes, and Cryptography (1999). To appear. [POL78] J. Pollard, "Monte Carlo methods for index computation mod p", Mathematics of Computation, 32 (1978), 918-924. [RFC2409] D. Harkens and D. Carrel, "Internet Key Exchange (IKE)", RFC 2409. [SCH95] R. Schroeppel, et al., Fast Key Exchange With Elliptic Curve Systems, In Don Coppersmith, editor, Advances in Cryptology -- CRYPTO '95, volume 963 of Lecture Notes in Computer Science, pages 43-56, 27- 31 August 1995. Springer-Verlag [SIL99] R. D. Silverman, RSA Laboratories Bulletin, Number 12 - May 3, 1999; An Analysis of Shamir's Factoring Device [SIL00] R. D. Silverman, RSA Laboratories Bulletin, Number 13 - April 2000, A Cost-Based Security Analysis of Symmetric and Asymmetric Key Lengths A. Authors' Addresses Hilarie Orman Novell, Inc. 1800 South Novell Place Provo, UT 84606 horman@novell.com Paul Hoffman Internet Mail Consortium and VPN Consortium 127 Segre Place Santa Cruz, CA 95060 USA paul.hoffman@imc.org and paul.hoffman@vpnc.org