Format preserving encryption: www.voltage.com.ABSTRACT Encrypting Personally Identifiable Information In information security and privacy, personally identifiable information or personally identifying information (PII) is any piece of information which can potentially be used to uniquely identify, contact, or locate a single person. (PII See Pentium II. ) in large databases has historically been difficult, because encrypting information typically implies expanding data and changing its format. Previous attempts to encrypt See encryption. PII data like credit cardnumbers and Social Security Numbers without changing their format have used questionable cryptographic constructions. We examine the security model for this problem, extend a construction by Black and Rogaway, and propose practical constructions for encrypting credit card numbers and Social Security Numbers. Categories and Subject Descriptors General Terms Algorithms, Management, Security, Legal Aspects. Keywords 1. INTRODUCTION Increased regulation, such as California SB1386 and the PCI (1) (Payment Card Industry) See PCI DSS. (2) (Peripheral Component Interconnect) The most widely used I/O bus (peripheral bus). Data Security Standard [9], and consumer awareness of privacy issues have motivated many businesses to investigate methods to encrypt Personally Identifiable Information (PII) and minimize the repercussions repercussions npl → répercussions fpl repercussions npl → Auswirkungen pl of losing data. One of the barriers to the adoption of effective encryption The reversible transformation of data from the original (the plaintext) to a difficulttointerpret format (the ciphertext) as a mechanism for protecting its confidentiality, integrity and sometimes its authenticity. Encryption uses an encryption algorithm and one or more encryption keys. methods is the cost of modifying databases and applications to accommodate encrypted en·crypt tr.v. en·crypt·ed, en·crypt·ing, en·crypts 1. To put into code or cipher. 2. Computer Science information. These costs are associated with two changes needed to accommodate classically encrypted data First, privacycritical information like credit card numbers or Social Security Numbers are often used as keys or indices in databases, so randomization randomization (ranˈ·d·m of these fields by encrypting data may require significant schema changes. Second, applications may be written expecting data in a specific format; encryption will typically expand data and require a format change. In addition to encryption of production databases, it may be desirable to produce test databases that resemble production databases. Often, the development and deployment process for large business applications involves testing an application against a production Environment now needs to be moved out into a probably less protected test environment. Encrypting the data would protect the data, but destroy the ability to test against that data, since the format would be changed, and, if the encryption was randomized ran·dom·ize tr.v. ran·dom·ized, ran·dom·iz·ing, ran·dom·iz·es To make random in arrangement, especially in order to control the variables in an experiment. , destroy referential integrity A database management safeguard that ensures every foreign key matches a primary key. For example, customer numbers in a customer file are the primary keys, and customer numbers in the order file are the foreign keys. in the database. It would be desirable to have an acceptably secure encryption process that would render a database of identifying information useless to an attacker without a key, but that would produce ciphertext Data that has been encrypted for security purposes. See plaintext. (cryptography) ciphertext  Text which has been encrypted by some encryption system. Opposite: plaintext. in the same formatas the plaintext. Certain compromises from the traditional semantic security Semantic security is a widelyused definition for security in an asymmetric key encryption algorithm. For a cryptosystem to be semantically secure, it must be infeasible for a computationallybounded adversary to derive significant information about a message (plaintext) when given model for ciphers must be taken, because of the desired size of the ciphertext, and the fact that we might want to encrypt deterministically to preserve referential integrity in a database. However, we still want formal statements of the security of these methods. We term algorithms with this property Format Preserving Encryption (FPE FPE Final Prediction Error FPE Floating Point Exception (a computer math error) FPE FokkerPlanck Equation FPE Fire Protection Engineering FPE Free Primary Education (Africa) ) algorithms. Historically, the best test for a cryptographic algorithm is the test of time. For this reason, we would like to have an FPE algorithm that is not new, or at least can be reduced (within some bound) to some existing, known cipher cipher: see cryptography. (1) The core algorithm used to encrypt data. A cipher transforms regular data (plaintext) into a coded set of data (ciphertext) that is not reversible without a key. . The algorithms proposed in this paper have security proofs in the cryptographic literature, and are based on constructions that go back at least to 1986. This paper discusses the history of the FPE problem, various solutions that have been proposed, the security model for FPE in general, and describes three methods that cover various FPE subcases. We expand the range of encryptable plaintexts from the BlackRogaway paper, examine the limits of these ciphers in the light of contributions from Patarin, and present practical constructions for encryption of two important data types, Social Security Numbers and credit card numbers. We also present performance figures for implementations of these ciphers. 2. HISTORY The FPE problem goes back at least to 1997, when Smith and Brightwell [5] argued that an FPE algorithm would help secure databases and data warehouses: Ciphertext (data in encrypted form) bears roughly the same resemblance to plaintext (data in its original form) as a hamburger does to a Tbone steak. A social security number, encrypted using the DES encryptional gorithm, not only does not resemble a social security number but will likely not contain any numbers at all. A database field which was defined to hold a ninecharacter social security number (eleven, if you want to include the hyphens) would not be able to store the DESencrypted version of the data. A Visual Basic program would not read it. A graphical interface See GUI. would not display it. There would be nothing that you could do with the encrypted social security number unless you had made extensive provisions for changes in data format throughout your application and physical database design. They defined the problem and proposed an encryption method based on an existing block cipher An encryption method that processes the input stream as groups of bytes that are fixed in size, typically 64, 128 or 256 bits long. The state of a block cipher is reset before processing each block. The DES and AES algorithms are examples of block ciphers (see DES and AES). (DES) in CipherFeedbackMode (CFB CFB Canadian Forces Base ), which a series of data and key dependent offsets that can be used to encrypt each character of a formatted string by adding the offset. This method has the weakness that, using the same key, initial characters in the string will be encrypted identically, so, for example, credit card numbers that share a bank id can be identified. The authors propose a "rippling" scheme to induce dependencies among the characters in the string, but no argument for the security of this scheme is given. The first strong cryptographic attempt to solve a related problem was Black and Rogaway in 2002 [1]. In this paper, they attempt to find solutions to a closely related problem: how to find ciphers that will encrypt elements of a set of some size in into a set of the same size. Since all formatted strings fit into a finite set In mathematics, a set is called finite if there is a bijection between the set and some set of the form where n is a natural number. (The value n = 0 is allowed; that is, the empty set is finite.) An infinite set is a set which is not finite. of some size, solutions to this problem can be used as the core of FPE algorithms. They propose three methods, which we examine below. Two of the methods, the Prefix The beginning or to add to the beginning. To prefix a header onto a packet means to place the header characters in front of the packet. "To prefix" at the beginning is the opposite of "to append" characters at the end. See prepend. 1. method (which works for small sets) and the CycleWalking Cipher (which works for sets just smaller than the size of the block cipher) have strong security bounds. The third method encrypts a much wider variety of data, using the Feistel construction first formally examined by Luby and Rackoff. [6]. The Feistel construction has the desirable property that ciphers built from it can be proven to reduce to some other cipher used as a round function, as long as the attacker only has access to some limited number of ciphertext/plaintext pairs. At the time of the BlackRogaway paper, there was no proof of bounds strong enough to allow this construction to be used to encrypt data in the range of credit card numbers, which left an important use case unsolved. Because the LubyRackoff construction is so important to the development of cryptographic algorithms, there has been a large body of work following that of Luby and Rackoff which attempts to give tighter security bounds. The basic LubyRackoff security problem is typically formulated as an attacker attempting to distinguish an instance of a LubyRackoff cipher from a random permutation A random permutation is a random ordering of a set of objects, that is, a permutationvalued random variable. The use of random permutations is often fundamental to fields that use randomized algorithms. Such fields include coding theory, cryptography, and simulation. , given the assumption that the LubyRackoff cipher is built from a psuedorandom function. This is important, as it is the weakest attack that can be mounted against a cipher. Any other attack would distinguish the cipher from a random permutation, so the strength of the cipher against this attack gives a lower bound on the security of the algorithm. In the LubyRackoff model, security is measured by the number of ciphertext/plaintext pairs needed by an attacker of unbounded computational power to have a reasonable chance of distinguishing between the cipher and a random permutation. The bounds shown in these proofs establish a formula for the number of pairs based on the size of the plaintext and the number ofrounds used. At the time of the original LubyRackoff paper, bounds were only known for three and four rounds, and the number of pairs was essentially the square root of half the size of the plaintext space. While this bound was an important theoretical result, it would give a security hound hound, classification used by breeders and kennel clubs to designate dogs bred to hunt animals. Most of the dogs in this group hunt by scent, their quarry ranging from such large game as bear or elk to small game and vermin; ground scenters trail slowly with the head of 16 bits for tripleDES (since it was unknown if extra rounds would improve bounds.) Clearly there were better bounds to be found. In the credit card case, this result would give a bound of 10,000 ciphertext/plaintext pairs needed, which is clearly too small for comfort. This bound was especially worrisome for the Black and Rogaway construction because running at three rounds, 10,000 ciphertext/plaintext pairs would give an attack that would leak information about other ciphertexts. In the paper, the authors speculate that more rounds would give more security, but left the problem to future work. In 2004, Patarin [7] showed that if the LubyRackoff construction is run with a sufficient number of rounds (6, 7, or 8, depending on the security model), the number of ciphertext/plaintext rounds needed by an attacker with unbounded computational resources In computational complexity theory, a computational resource is a resource used by some computational models in the solution of computational problems. The simplest computational resources are computation time, the number of steps necessary to solve a problem, and to establish a difference between a LubyRackoff cipher and a random permutation approaches the theoretical maximum, which is the square root of the size of the entire plaintext. In the credit card number case, the bound would now be 16 million ciphertext/plaintext pairs, for a theoretical attack by a computationally unbounded opponent (i.e., an attacker with infinite computing resources). Patarin also gives the best known realistic attack, which is still somewhat theoretic in that it requires more ciphertext/plaintext pairs than can be produced by a single key, and also at least 2 (64) computational steps. In the light of the Patarin results, it seems worthwhile to reexamine re·ex·am·ine also reex·am·ine tr.v. re·ex·am·ined, re·ex·am·in·ing, re·ex·am·ines 1. To examine again or anew; review. 2. Law To question (a witness) again after crossexamination. the LubyRackoff construction for the FPE problem, as it gives an efficient, AESbased encryption algorithm A formula used to turn ordinary data, or "plaintext," into a secret code known as "ciphertext." Each algorithm uses a string of bits known as a "key" to perform the calculations. The larger the key (the more bits), the greater the number of potential patterns can be created, thus making with a strong proof of security within acceptable bounds. 3. The FPE Model The archetypical ar·che·type n. 1. An original model or type after which other similar things are patterned; a prototype: "'Frankenstein' . . . 'Dracula' . . . 'Dr. Jekyll and Mr. Hyde' . . . FPE use case is the encryption of an internal database so that a limited number of applications and users (perhaps none) can recover the original values from the FPE encrypted values. In this setting, any security mechanism (FPE, traditional encryption, or other access: control mechanism) needs to be strong with the following limitations: Constraint 1: The attacker knows the format and type of data in the database. We should assume that an attacker knows that they are looking for Looking for In the context of general equities, this describing a buy interest in which a dealer is asked to offer stock, often involving a capital commitment. Antithesis of in touch with. credit card numbers or social security numbers. Constraint 2: The plaintext size will be relatively small, compared to typical cryptographic set sizes. A block cipher like AES operates on 128 bit blocks. Social security numbers are approximately 28 bits, and credit card numbers are approximately 58 bits long. This means that any mechanism (FPE or other) must protect against attacker access to the encrypt/decrypt function; otherwise, an attacker can simply start asking for decryptions of arbitrary data and potentially get a dangerous amount of PII data. In the case of FPE, two other important limitations are put on the algorithm: Constraint 3: Data cannot be expanded. When an FPE algorithm encrypts an Ndigit number, it must output an Ndigit number. Constraint 4: Data must be encrypted deterministically. Data is typically being encrypted in a database, and it is highly desirable to preserve the ability to use a column as a key or index, which requires that multiple instances of a given data item encrypt to an identical data item (when using the same key). Note that Constraint4 also can be seen as a consequence of Constraint 3. Since no additional data can be stored in the data field (otherwise expansion would result), there is no space forrandomness needed for initialization vectors A continuously changing number used in combination with a secret key to encrypt data. Initialization vectors (IVs) are used to prevent a sequence of text that is identical to a previous sequence from producing the same exact ciphertext when encrypted. or other randomizers. Location within the database, or other fields could be used asrandomness, but then the ability to decrypt To convert secretly coded data (encrypted data) back into its original form. Contrast with encrypt. See plaintext and cryptography. is conditioned on the availability of that data. If data is decrypted within an application external to the database, this data may not be available. Within these constraints, we need an algorithm that will encrypt data by permuting strings in a given format to different strings in the same format, will not leak information to an attacker that has access to a large number of ciphertexts, and will survive the exposure of a reasonable number of plaintext/ciphertext pairs. The algorithms that meet this standard are built to survive only in the FPE setting, and are not generally recommended for building into communication applications, or other settings where the attacker can be assumed to have access to the encrypt/ decrypt function or access to unlimited ciphertext/plaintext pairs. The compensating factor that makes it possible to construct a secure cipher within these constraints is that, while the attacker knows that they are looking for a specific kind of data (a Social Security Number, for instance), they must find one particular number that matches the other personal data in the database. This means that we can essentially permute per·mute tr.v. per·mut·ed, per·mut·ing, per·mutes 1. To change the order of. 2. Mathematics To subject to permutation. the set of numbers, and measure the success of the attacker by how successful they can be at guessing a specific number given a permuted number and some other defined data. The practical security goal here is to turn a currently passiveattack (stealing database data through an application, log file, or backup tape See tape backup. ) into one that requires active subversion sub·ver·sion n. 1. a. The act or an instance of subverting. b. The condition of being subverted. 2. Obsolete A cause of overthrow or ruin. of a trusted encryption/decryption function, and that will keep data safe even if a substantial number of encryptions and decryptions escape. In section 4, we examine each FPE method and detail the security bounds that are shown for each method. 3.1 Test Data Model The model of encrypting data for testing in a lab or for development access is slightly different than the full FPE model. In this case, the encryption process may not need to be arbitrarily reversible reversible, adj capable of going through a series of changes in either direction, forward or backward (e.g., reversible chemical reaction). reversible hydrocolloid, n See hydrocolloid, reversible. , but instead is used to permute the data, then the key is thrown away. In this case, any possible encryption/decryption oracle is destroyed, and the best that an attacker can do, short of finding a way to recorrelate the data with plaintext by breaking into internal databases, is to examine the ciphertext. The FPE methods below are very strong in this model. Currently, many applications use hash functions This is a list of hash functions, including cyclic redundancy checks, checksum functions, and cryptographic hash functions. Cyclic redundancy checks
Name Length Type Adler32 32 bits sum truncated truncated adjective Shortened to output formatted data. This preserves the referential integrity requirement, but creates the possibility of internal collisions (where two data items encrypt to the same value), possibly leading to difficult to detect bugs. Since all the FPE algorithms are permutations, they guarantee that data items will not collide col·lide intr.v. col·lid·ed, col·lid·ing, col·lides 1. To come together with violent, direct impact. 2. when encrypted. This is an especially desirable feature for small data items like Social Security Numbers where the probability of a collision is nonnegligible. 4. FPE Methods This section details three practical FPE methods, all derived from the three methods in the Black and Rogaway paper [1]. We give performance measurements for these methods, and offer a modification and security bound improvement for the Feistel construction based on Patarin's results. The next section details the practical FPE schemes for the specific credit card number and Social Security Number cases. Each of the three methods handles a different input set size, either for security or performance reasons. The following table summarizes the practical and secure bounds for each of he methods, in terms of overall set size and also in terms of the number of decimal digits Noun 1. decimal digit  a digit from 0 to 9 in decimal notation digit, figure  one of the elements that collectively form a system of numeration; "0 and 1 are digits" of a formatted string. Set sizes and formats that are not covered not covered Health care adjective Referring to a procedure, test or other health service to which a policy holder or insurance beneficiary is not entitled under the terms of the policy or payment system–eg, Medicare. Cf Covered. by this table may be covered by application of a compound method specified in section 5. The values in the table areapproximate, and actual bounds are dependent on the security level required by the specific application. The table attempts to be conservative in terms of security model. The description of the individual algorithms specifies how set size interacts with security and performance. Method Set Sizes (bits) Decimal Digits Prefix 120 16 Cyclewalking 5063 1619 FeistelCycle 40240 1280 4.1 The Prefix method The Prefix method is very simple, but only works on small datasets. The method works by essentially "writing down" a random permutation in memory, and using that permutation One possible combination of items out of a larger set of items. For example, with the set of numbers 1, 2 and 3, there are six possible permutations: 12, 21, 13, 31, 23 and 32. (mathematics) permutation  1. toencrypt data. 4.1.1 Prefix Method Description: To encrypt data with the Prefix method, we first construct a table which stores a permutation over the full plaintext set, then simply look up the ciphertext value using the plaintext. This means that encryptions and decryptions are very fast. Table set up is more expensive, but acceptable for small set sizes. To set up the table, we pick an underlying cipher, typically AES or 3DES. We then encrypt the values 0 ... Nl, where N is the size of the input set. We record the input number and the encrypted value, then sort by the encrypted value For example, say that we want to encrypt data in the set of a single digit (09). We encrypt ten values with AES, then sort, creating a table that looks like the following: Digit AES encryption of digit, sorted 7 12d76795b5e818b38be9813260ab0c5f 3 203c3c515ae6101c4858fe07ecb78ec0 1 25dabcc8862842c228a2d7ac5058b780 2 416f3563827406dab2ef1246393fed32 6 45bd0fb7d45bd276d499ad4b8cd52e55 9 4c9c6ecbdf1ab60ef0b31d753fa594c6 4 4e20e4d8c4195df66a3cc9fe60f5b98f 0 5c3f46a3cf7a8da378eb95f546a20ab2 8 98bc8588c55900703ef11fa80447e32c 5 d99851ff58a9bf03d717ff6601639795 We can then throw away the encrypted values, leaving a permutation over the set size. In this example, the encryption of 2 would be 1. Decryption (cryptography) decryption  Any procedure used in cryptography to convert ciphertext (encrypted data) into plaintext. can be performed by simply finding the index of the encrypted value. For example, a ciphertext of 7 would correspond to the plaintext of 0. We can build these tables for any size set up to just under the size of the underlying block cipher. (If the input set was the same size as the block cipher, we could just directly use the block cipher.) 4.1.2 Prefix Cipher Tweaking tweaking Vox populi Finetuning to produce optimal results Because rekeying In cryptography, rekeying refers to the process of changing the encryption key of an ongoing communication in order to limit the amount of data encrypted with the same key. the Prefix Cipher requires rebuilding the table, it may be desirable in certain circumstances to be able to apply a "tweak To make minor adjustments in an electronic system or in a software program in order to improve performance. See calibrate. 1. tweak  To change slightly, usually in reference to a value. Also used synonymously with twiddle. " to the cipher, which will alter the encryption function without requiring a rekey Rekeying is the process of changing a lock's tumblers to work on a different key than the current one. Though often referred to as 'changing a lock', rekeying does not require replacement of the lock itself, but resetting the tumbler combination to fit a different key. . The security requirements for tweaks, and some methods for building tweaked See tweak. ciphers, are given in [8]. The basic method for applying a tweak T to a cipher E (of size N) that is shown secure in [8] is to perform the following operation, which encrypts a plaintext P using a key K. C = E((E(P, K) + T) mod N, K) Normally, this construction is seen to be inefficient, because it requires two invocations of the underlying cipher. In the case of the Prefix Cipher, the cost of encryption is only a lookup A data search performed within a predefined table of values (array, matrix, etc.) or within a data file. , so the construction is very fast, requiring only two memory lookups and an addition operation. We will use this tweaking construction to construct a Social Security Number encryption operation later. 4.1.3 Prefix Method Security Black and Rogaway [1] give a straightforward proof that breaking this construction reduces to breaking the underlying cipher. They conclude that finding a difference between this kind of Prefix permutation and a random permutation would require finding a difference between the underlying cipher and a random permutation. 4.1.4 Prefix Method Performance The Prefix method can be thought of as having a very slow key setup time (building the permutation in memory) and a very fast encrypt and decrypt time (doing the single lookup in the table.) The performance question comes down to the time required to build the table, and the memory required to hold the table. One useful optimization is to initially encrypt the set elements, but only record the initial 32 bits in the table. The table sort can then be done on these 32 bit elements, and if two elements are equivalent, reencrypt and compare the entire encrypted value. This optimization makes the intermediate table smaller, and lowers the amount of copying required during the sort. The following table shows the performance of the prefix cipher, using AES256 as the base cipher, at various set sizes on a 2.34 Ghz Pentium IV See Pentium 4. with 1 GB memory running Microsoft Windows See Windows. (operating system) Microsoft Windows  Microsoft's proprietary window system and user interface software released in 1985 to run on top of MSDOS. Widely criticised for being too slow (hence "Windoze", "Microsloth Windows") on the machines available then. XP Professional. Since encryption and decryption is trivial (requires a single memory lookup), we only show the time required to build the key table. The table shows the size of the plaintext in bits, the number of decimal digits that can be encoded by the cipher, and the time to build the table in milliseconds. Bits Decimal Digits Table Build Time 10 3 0.476 14 4 5.5 17 5 62 20 6 760 4.2 Cyclewalking Method The Cyclewalking construction, like the Prefix method, is quite simple, but works on a limited class of sets. The Cyclewalking construction works by encrypting the plaintext with an existing block cipher (AES or 3DES) repeatedly until the cipher output falls in the acceptable output range. To encrypt a ciphertext C in the range 0..N, using some base cipher E, we perform the following operation: T = E (C) while(T > N) T = E(T) The larger the difference is between the size of the output of the base cipher and the size of the desired output set, the longer this operation will take to terminate. For this construction to be practical, N needs to be some small number of bits shorter than the output of the cipher. 4.2.1 Cyclewalking Method Security [1] contains the proof that the Cyclewalking cipher does notdegrade the security of the underlying cipher. 4.2.2 Cyclewalking Method Performance The following table shows CycleWalking performance using 3DES for a variety of set sizes close to 64 bits. The timings were taken on a 2.34 Ghz Pentium IV with 1GB memory running Windows XP The previous client version of Windows. XP was a major upgrade to the client version of Windows 2000 with numerous changes to the user interface. XP improved support for gaming, digital photography, instant messaging, wireless networking and sharing connections to the Internet. Professional. The table shows the bit size of the input, the number of encoded decimal digits, and the number of encyption operations per second. The timings were taken by generating a random decimal Meaning 10. The numbering system used by humans, which is based on 10 digits. In contrast, computers use binary numbers because it is easier to design electronic systems that can maintain two states rather than 10. value in the range shown, packing it into binary form Binary form is a way of structuring a piece of music into two related sections, both of which are usually repeated. Note that Binary is also a structure used to choreograph dance. , and encrypting using 3DES in the Cyclewalking mode. Bits Digits Enc/Second 54 16 500 57 17 5000 60 18 43000 64 19 15000 As can be seen from the table, the Cyclewalking method yields a usable cipher for values in the size range of standard credit card numbers, which range from 1619 digits long. 4.3 Feistel + Cycle Method: This method is more complex than the Prefix or Cyclewalking constructions, but allows for encryption over a wide variety of set sizes with good performance. We adapt the BlackRogaway construction to use a standard "textbook" Feistel network, which lets us get close to desired set size, and use the Cyclewalking technique to get the output into the output set. Black and Rogaway use a more modified Feistel at three rounds. We use the unmodified Adj. 1. unmodified  not changed in form or character unqualified  not limited or restricted; "an unqualified denial" modified  changed in form or character; "their modified stand made the issue more acceptable"; "the performance of the modified aircraft LubyRackoff Feistel construction with two different round function constructions with a minimum of eight rounds. 4.3.1 Feistel + Cycle Description: The Feistel + Cycle construction has two main parts. First, the Feistel network that is closest to the size of the plaintext is constructed. This is then used to encrypt the data. The cyclewalking technique is then used to insure that the ciphertext is in the appropriate range. The Feistel construction for a given bit length n consists of multiple rounds of the following construction using some PsuedoRandom Function (PRF PRF abbr. prolactinreleasing factor ) f, which takes n/2 bits and outputs 0./2 bits. It operates on the plaintext, which is divided into a left and right half, called L and R. The round function produces a new L and R, which is either output or fed back into the next round. The round function performs the following operation to calculate the new L and R values: R'= L XOR (eXclusive OR) A Boolean logic operation that is widely used in cryptography as well as in generating parity bits for error checking and fault tolerance. XOR compares two input bits and generates one output bit. The logic is simple. If the bits are the same, the result is 0. f(R) L'=R To construct a FeistelCycle cipher [FC.sub.N, F, x] to encrypt a value P from 0 ... N, using a base psuedorandom function F and x rounds, we do the following: Define the Feistel network: 1. Find the smallest W s.t. [2.sup.2w] > log2(N). This is the width of the Feistel network we will use. 2. Define F'(x) = tnmc(F(x), w) 3. Round(R, L) = L XOR F'(R) 4. [Feistel.sub.N, F. x](P) is then computed by: 1. Find R, L s.t. P = R* [2.sup.W] + L 2. Repeat x times: {T = Round(R, L), L = R, R = T} 3. Output R * [2.sup.W] + L [FC.sub.N, F, x](P) is then computed as: 1. C = [Feistel.sub.N, F,x](P) 2. while(C > N) {C = [Feistel.sub.N, F, x](C)} To fully specify a FeistelCycle cipher for a specific instance, we now need to just decide two things. First, how many rounds to run. The security bounds that we need are comfortably achieved with 8 rounds for most datasets. Second, what do we use for F? The security bounds reduce the problem of distinguishing the whole cipher from a random permutation to distinguishing F from a random function. Hence, we need a strong random function of n/2 bits for a wide variety of n. The problem of building PRFs has been widely studied, and there are two methods that give acceptable PRFs for use here. We can't simply use AES, since it is a pseudorandom permutation In cryptography, a pseudorandom permutation, abbreviated PRP, is an idealized block cipher. It means the cipher that cannot be distinguished from a random permutation (that is, a permutation selected at random with uniform probability, from the family of all permutations on (PRP PrP A prion protein. See Prion. ), not a PRF, and it is too wide. We need a random function that is exactly the same width as the left element so that L can be XOR' ed with the output. If n is small enough, simply taking the first n/2 bits of AES actually gives a strong PRF. If n is larger, we can take the output of two instances of AES XORed together. [2] details the proof that these constructions yield strong PRFs. There is a long tradition of using truncated PRPs as strong PRFs. For example, the IETF See Internet Engineering Task Force. IETF  Internet Engineering Task Force RFC (Request For Comments) A document that describes the specifications for a recommended technology. Although the word "request" is in the title, if the specification is ratified, it becomes a standards document. on a PRF for Kerberos [10] uses this construction. 4.3.2 Feistel + Cycle Security We can measure security of this cipher in three different ways. First is the resistance to attack by the best possible computationally unbounded attacker. Second is the resistance to attack by brute force (programming) brute force  A primitive programming style in which the programmer relies on the computer's processing power instead of using his own intelligence to simplify the problem, often ignoring problems of scale and applying naive methods suited to small problems directly . Third is the best known attack that distinguishes Feistel networks from random permutations. Attacker 1: The Optimal Unbounded Attacker For any Feistel network, we can measure the amount of entropy entropy (ĕn`trəpē), quantity specifying the amount of disorder or randomness in a system bearing energy or information. Originally defined in thermodynamics in terms of heat and temperature, entropy indicates the degree to which a given in the function, estimate how much entropy a plaintext/ciphertext pair gives away, and then derive how many plaintext/ciphertextpairs are required for any possible attacker. This is the strongest possible security model. The result of this analysis [5] is that the best possible unbounded attacker will require sqrt(2n) ciphertext/plaintext pairs, and Patarin [7] shows that 6 rounds of a Feistel network is sufficient to get to this upper bound. This means that any theoretic adversary adversary traditional appellation of Satan [O.T.: Job 1:6; N.T.: I Peter 5:8] See : Devil attacking a 6 or more round Feistel network operating on 56 bits, which is the set required for credit card numbers, will require a minimum of 16 million plaintext/ciphertext pairs. The same cipher operating over the Social Security Number space, which is about 28 bits, will require a minimum of 16,384 pairs. Since this number is small, we consider hybrid techniques in the next section to handle this case. Note that for Feistel networks of over 6 rounds, these bounds are for a hypothesized optimal attacker, and no practical attack comes close to these bounds. The unbounded attack model is most interesting in that it provides a strong lower bound. We know, through the proof, that no attack can be constructed that is more efficient. The currently known attacks against Feistel networks are far worse than these bounds. Attacker 2: The Brute Force Attacker The closest match to the unbounded attacker is an attacker that attempts to enumerate To count or list one by one. For example, an enumerated data type defines a list of all possible values for a variable, and no other value can then be placed into it. See device enumeration and ENUM. all possible round functions that are consistent with the plaintext/ciphertext pairs it has seen. This attacker would require [2.sup.log2(r)+sqrt(n)] pairs, and would need to perform a very large number of computations. We can see the difficulty of the attack by examining the computations required to attack a small six bit wide Feistel network using eight rounds. A six bit wide Feistel network will use three bit PRFs. There are [8.sup.8] or [2.sup.24] possible functions of this type. With eight rounds, the brute force attacker will need to keep track of [2.sup.192] possible Feistel networks, and eliminate them as they become inconsistent with the ciphertext/plaintext pairs. It is possible that there is some optimization that would make this attack practical, but it appears that even a trivially small Feistel requires an currently impractical amount of computational power. Attacker 3: The Best Known Attacker Patarin showed the best known realizable attack against Feistel networks [7]. These attacks are realizable in principle, but require more ciphertext/plaintext pairs than can be produced by a single key, and require significant computational resources. The Patarin attacks are also pure distinguishing attacks The introduction to this article provides insufficient context for those unfamiliar with the subject matter. Please help [ improve the introduction] to meet Wikipedia's layout standards. You can discuss the issue on the talk page. that produce a single bit, which is the guess as to if the plaintext/ciphertext pairs are produced by a random permutation or by a Feistel network. To distinguish an 2n bit wide Feistel network of 8 or more rounds from a random permutation, the Patarin attacks require [2.sup.(r6)n] plaintext/ciphertext pairs, and [2.sup.(r4)n] computations. So, for thecredit card case with 8 rounds, it would require [2.sup.56] plaintext/ciphertext pairs, and [2.sup.112] computational steps. This means the attacker would need every single possible plaintext/ciphertext pair, and would need to perform more computations than would be needed to break an 80 bit key. Increasing the round cotmt beyond 8 makes these attacks even more difficult. 4.3.3 Feistel + Cycle Performance The Feistel + Cycle construction's performance is dependent upon the number of rounds used and the specific PRF that is used in the round function. For any plaintext that is smaller than the block size of the PRF, the performance is essentially [i.sup.*][r.sup.*]cost(PRF), where r is the round count and i is the average number of times the cipher cycles to get an acceptable output. For the truncated AES PRF, performance is very close to [i.sup.*][r.sup.*] cost(AES) + cost(AES key setup). For the summing AESPRF, performance is close to [2.sup.*][i.sup.*][r.sup.*]cost(AES) + [2.sup.*]cost(AES key setup). Measurement of the Feistel+Cycle method was done on a 2.34Ghz Pentium IV with 1GB of memory running Windows XP Professional, using AES as the base for the internal PRF. The cipher was measured for a range of round counts ranging from 8 to 128, using both the truncation and additive additive In foods, any of various chemical substances added to produce desirable effects. Additives include such substances as artificial or natural colourings and flavourings; stabilizers, emulsifiers, and thickeners; preservatives and humectants (moistureretainers); and PRF constructions. Rounds PRF Enc/Second 128 Trunc 7000 32 Trunc 10500 8 Trunc 18000 8 Add 8100 The range of rounds was measured to examine the viability of running large numbers of rounds to defeat any possibility of the worstcase brute force attack The systematic, exhaustive testing of all possible methods that can be used to break a security system. For example, in cryptanalysis, trying all possible keys in the keyspace to decrypt a ciphertext. See dictionary attack. See also brute force programming. working for small inputs. 5. Specific and Compound Methods It is possible to use these methods in combination to yield FPE techniques that will allow for granting access to only selected digits of a number (for example, limiting a customer service application to the last four digits of a Social Security Number, while granting another application full access.) These methods can be used to fill the gap between where the Prefix method is not practical and where the Feistel + Cycle construction may not be considered fully secure. 5.1 Compound for Social Security Numbers The Social Security Number case is interesting because this is a common type of PII, and it is small enough that it does not fall into the obvious bounds for the known three provable FPE methods. This case is valuable enough that we supply a method that gives reasonable security bounds for the entire number, and also gives the valuable property of being able to either decrypt the entire number or just the last four digits, which are often used in customer service applications for confirmation purposes. The construction works in the following way. We use as the basis for the construction two ciphers: Pre5 (P, T, K): A Prefix cipher encrypting all five digit decimal values using key K, and an arbitrary tweak value T FC 9 (P, K): A Feistelcycle cipher encrypting all nine digit decimal values using key K. H (P): A hash function An algorithm that turns a variablesized amount of text into a fixedsized output (hash value). Hash functions are used in creating digital signatures, hash tables and short condensations of text for analysis purposes (see hash buster). from four digit decimal values to an arbitrary bit string. Construct two keys, K1 and K2. Divide the Social Security Number into the initial five digits L and the last four digits R. The encrypted number is then computed by: E = FC9(Pre5(L, H(R), K1), K2) Now an entity can be given access to just the last four digits by giving them just K2. They can use K2 to undo the Feistel encryption only. An entity with access to K1 and K2 can decrypt the entire number by first undoing the Feistel encryption with K2, then undoing the Prefix encryption with K1 and the decrypted last four digits. The initial encryption with the Prefix Cipher insures that a theoretical attacker that uses the smaller bounds of the Feistel cipher run on a small plaintext space will only recover (in the worst case) the last four digits of the number and encrypted versions of the first five digits. 5.2 Methods for Credit Card Numbers Credit card numbers are an interesting case for FPE, as they carry a check digit A numeric digit used to ensure that account numbers are entered accurately into the computer. Using a formula, a digit is calculated from each new account number, which is then made part of that number, either at the end, the beginning or somewhere in the middle of the number. at the end of the number that is calculated with the Luhn algorithm The Luhn algorithm or Luhn formula, also known as the "modulus 10" or "mod 10" algorithm, is a simple checksum formula used to validate a variety of identification numbers, such as credit card numbers and Canadian Social Insurance Numbers. , which is a modified sum of the digits. This digit does not need to be encrypted, since it can simply be recalculated when the remaining digits are decrypted. There are three methods to encrypt with this checksum A value used to ensure data are stored or transmitted without error. It is created by calculating the binary values in a block of data using some algorithm and storing the results with the data. : Checksum 1Encrypt the number but exclude the final digit, and replace the checksum digit with a valid checksum of the encrypted digits. This has the advantage that, to any application that tests the checksum, encrypted CCNs look identical to valid CCNs. Checksum 2Encrypt the number but exclude the final digit, and replace the checksum digit with the checksum value plus 1. This insures that the checksum digit is invalid, and gives a reliable method to distinguish an encrypted CCN CCN Cloud Condensation Nuclei CCN Church Communication Network CCN Conseil Canadien des Normes (Standards Council of Canada) CCN Critical Care Nurse CCN Certified Clinical Nutritionist CCN Community Care Network CCN Cyclin from a plaintext CCN. Checksum 3Generate nine keys, encrypt all the digits (but the final) with one of these keys, and replace the checksum digits with the checksum plus a key identifying value from 1 to 9. This ensures that the checksum is invalid, and gives a method to change keys and record what key is used to encrypt a specific value without adding any data to the database. 6. ACKNOWLEDGEMENTS 7. REFERENCES [1] J. Black and P. Rogaway. Ciphers with Arbitrary Finite Domains. RSA (1) (Rural Service Area) See MSA. (2) (RivestShamirAdleman) A highly secure cryptography method by RSA Security, Inc., Bedford, MA (www.rsa.com), a division of EMC Corporation since 2006. It uses a twopart key. Data Security Conference, Cryptographer's Track (RSA CT '02), Lecture Notes in Computer Science Lecture Notes in Computer Science (LNCS) is a computer science series published by Springer Science+Business Media. , vol. 2271, pp. 114130, Springer springer a North American term commonly used to describe heifers close to term with their first calf. , 2002. [2] M. Bellare and R. Impagliazzo. A tool for obtaining tighter security analyses of pseudorandom pseu·do·ran·dom adj. Of, relating to, or being random numbers generated by a definite, nonrandom computational process. function based constructions, with applications to PRP / PRF conversion. Manuscript, 1999. [3] S. Lucks. The Sum of PRPs Is a Secure PRF. Lecture Notes in Computer Science", volume 1807, 2000 [4] H.E. Smith and M. Brightwell. Using DatatypePreserving Encryption to Enhance Data Warehouse Security. NIST (National Institute of Standards & Technology, Washington, DC, www.nist.gov) The standardsdefining agency of the U.S. government, formerly the National Bureau of Standards. It is one of three agencies that fall under the Technology Administration (www.technology. 20th National Information Systems Security Conference, pp. 141, 1997. [5] 5. M. Naor and O. Reingold, On the construction of pseudorandom permutations: LubyRackoff revisited, J. of Cryptology The science of developing secret codes and/or the use of those codes in encryption systems. See cryptography. cryptology  The study of cryptography and cryptanalysis. , vol 12, 1999, pp. 2966. Extended abstract in: Proc. 29th Ann. ACM (Association for Computing Machinery, New York, www.acm.org) A membership organization founded in 1947 dedicated to advancing the arts and sciences of information processing. In addition to awards and publications, ACM also maintains special interest groups (SIGs) in the computer field. Symp. on Theory of Computing, 1997, pp. 189199 [6] M. Luby and C. Rackoff. How to construct pseudorandom permutations and pseudorandom functions. SIAM J. Computing, 17(2):373386, April 1988. [7] J. Patarin. Security of Random Feistel Schemes With 5 or More Rounds. In proceedings of Crypto 2004, The 24th Annual International Cryptology Conference, Santa Barbara, California Santa Barbara is a city in California, United States. It is the county seat of Santa Barbara County, California. As of the 2000 census, the city had a total population of 92,325. , USA, August 1519, 2004. [8] M. Liskov, R. Rivest, D. Wagner. Tweakable Block Ciphers. Proceedings of Crypto 2002, The 22nd Annual International Cryptology Conference, Santa Barbara Santa Barbara (săn'tə bär`brə, –bərə), city (1990 pop. 85,571), seat of Santa Barbara co., S Calif., on the Pacific Ocean; inc. 1850. , CA, Aug 1519, 2002. [9] PCI Security Standards Council, Payment Card Industry (PCI) Data Security Standard, https://www.pcisecuritystandards.org/tech/index.htm September 2006 [10] N. Williams, Internet Engineering Task Force (c/o Corporation for National Research Initiatives (CNRI), Reston, VA, www.ietf.org) Founded in 1986, the IETF is a nonmembership, open, voluntary standards organization dedicated to identifying problems and opportunities in IP data networks and proposing technical solutions to the RFC 4402 (http://www.rfc archive.org/getrfc.php?rfc=4402 

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