An Alternative to Public Key Encryption
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A [49 16 6 ]-Linear Code As Product of the [7 4 2 ] Code Due to Aunu and the Hamming [7 4 3 ] Code
General Letters in Mathematics, Vol. 4, No.3 , June 2018, pp.114 -119 Available online at http:// www.refaad.com https://doi.org/10.31559/glm2018.4.3.4 A [49 16 6 ]-Linear Code as Product Of The [7 4 2 ] Code Due to Aunu and the Hamming [7 4 3 ] Code CHUN, Pamson Bentse1, IBRAHIM Alhaji Aminu2, and MAGAMI, Mohe'd Sani3 1 Department Of Mathematics, Plateau State University Bokkos, Jos Nigeria [email protected] 2 Department Of Mathematics, Usmanu Danfodiyo University Sokoto, Sokoto Nigeria [email protected] 3 Department Of Mathematics, Usmanu Danfodiyo University Sokoto, Sokoto Nigeria [email protected] Abstract: The enumeration of the construction due to "Audu and Aminu"(AUNU) Permutation patterns, of a [ 7 4 2 ]- linear code which is an extended code of the [ 6 4 1 ] code and is in one-one correspondence with the known [ 7 4 3 ] - Hamming code has been reported by the Authors. The [ 7 4 2 ] linear code, so constructed was combined with the known Hamming [ 7 4 3 ] code using the ( u|u+v)-construction method to obtain a new hybrid and more practical single [14 8 3 ] error- correcting code. In this paper, we provide an improvement by obtaining a much more practical and applicable double error correcting code whose extended version is a triple error correcting code, by combining the same codes as in [1]. Our goal is achieved through using the product code construction approach with the aid of some proven theorems. Keywords: Cayley tables, AUNU Scheme, Hamming codes, Generator matrix,Tensor product 2010 MSC No: 97H60, 94A05 and 94B05 1. -
Coding Theory: Linear Error-Correcting Codes Coding Theory Basic Definitions Error Detection and Correction Finite Fields Anna Dovzhik
Coding Theory: Linear Error- Correcting Codes Anna Dovzhik Outline Coding Theory: Linear Error-Correcting Codes Coding Theory Basic Definitions Error Detection and Correction Finite Fields Anna Dovzhik Linear Codes Hamming Codes Finite Fields Revisited BCH Codes April 23, 2014 Reed-Solomon Codes Conclusion Coding Theory: Linear Error- Correcting 1 Coding Theory Codes Basic Definitions Anna Dovzhik Error Detection and Correction Outline Coding Theory 2 Finite Fields Basic Definitions Error Detection and Correction 3 Finite Fields Linear Codes Linear Codes Hamming Codes Hamming Codes Finite Fields Finite Fields Revisited Revisited BCH Codes BCH Codes Reed-Solomon Codes Reed-Solomon Codes Conclusion 4 Conclusion Definition A q-ary word w = w1w2w3 ::: wn is a vector where wi 2 A. Definition A q-ary block code is a set C over an alphabet A, where each element, or codeword, is a q-ary word of length n. Basic Definitions Coding Theory: Linear Error- Correcting Codes Anna Dovzhik Definition If A = a ; a ;:::; a , then A is a code alphabet of size q. Outline 1 2 q Coding Theory Basic Definitions Error Detection and Correction Finite Fields Linear Codes Hamming Codes Finite Fields Revisited BCH Codes Reed-Solomon Codes Conclusion Definition A q-ary block code is a set C over an alphabet A, where each element, or codeword, is a q-ary word of length n. Basic Definitions Coding Theory: Linear Error- Correcting Codes Anna Dovzhik Definition If A = a ; a ;:::; a , then A is a code alphabet of size q. Outline 1 2 q Coding Theory Basic Definitions Error Detection Definition and Correction Finite Fields A q-ary word w = w1w2w3 ::: wn is a vector where wi 2 A. -
Mceliece Cryptosystem Based on Extended Golay Code
McEliece Cryptosystem Based On Extended Golay Code Amandeep Singh Bhatia∗ and Ajay Kumar Department of Computer Science, Thapar university, India E-mail: ∗[email protected] (Dated: November 16, 2018) With increasing advancements in technology, it is expected that the emergence of a quantum computer will potentially break many of the public-key cryptosystems currently in use. It will negotiate the confidentiality and integrity of communications. In this regard, we have privacy protectors (i.e. Post-Quantum Cryptography), which resists attacks by quantum computers, deals with cryptosystems that run on conventional computers and are secure against attacks by quantum computers. The practice of code-based cryptography is a trade-off between security and efficiency. In this chapter, we have explored The most successful McEliece cryptosystem, based on extended Golay code [24, 12, 8]. We have examined the implications of using an extended Golay code in place of usual Goppa code in McEliece cryptosystem. Further, we have implemented a McEliece cryptosystem based on extended Golay code using MATLAB. The extended Golay code has lots of practical applications. The main advantage of using extended Golay code is that it has codeword of length 24, a minimum Hamming distance of 8 allows us to detect 7-bit errors while correcting for 3 or fewer errors simultaneously and can be transmitted at high data rate. I. INTRODUCTION Over the last three decades, public key cryptosystems (Diffie-Hellman key exchange, the RSA cryptosystem, digital signature algorithm (DSA), and Elliptic curve cryptosystems) has become a crucial component of cyber security. In this regard, security depends on the difficulty of a definite number of theoretic problems (integer factorization or the discrete log problem). -
On Notions of Security for Deterministic Encryption, and Efficient Constructions Without Random Oracles
A preliminary version of this paper appears in Advances in Cryptology - CRYPTO 2008, 28th Annual International Cryptology Conference, D. Wagner ed., LNCS, Springer, 2008. This is the full version. On Notions of Security for Deterministic Encryption, and Efficient Constructions without Random Oracles Alexandra Boldyreva∗ Serge Fehr† Adam O’Neill∗ Abstract The study of deterministic public-key encryption was initiated by Bellare et al. (CRYPTO ’07), who provided the “strongest possible” notion of security for this primitive (called PRIV) and con- structions in the random oracle (RO) model. We focus on constructing efficient deterministic encryption schemes without random oracles. To do so, we propose a slightly weaker notion of security, saying that no partial information about encrypted messages should be leaked as long as each message is a-priori hard-to-guess given the others (while PRIV did not have the latter restriction). Nevertheless, we argue that this version seems adequate for certain practical applica- tions. We show equivalence of this definition to single-message and indistinguishability-based ones, which are easier to work with. Then we give general constructions of both chosen-plaintext (CPA) and chosen-ciphertext-attack (CCA) secure deterministic encryption schemes, as well as efficient instantiations of them under standard number-theoretic assumptions. Our constructions build on the recently-introduced framework of Peikert and Waters (STOC ’08) for constructing CCA-secure probabilistic encryption schemes, extending it to the deterministic-encryption setting and yielding some improvements to their original results as well. Keywords: Public-key encryption, deterministic encryption, lossy trapdoor functions, leftover hash lemma, standard model. ∗ College of Computing, Georgia Institute of Technology, 266 Ferst Drive, Atlanta, GA 30332, USA. -
Coded Computing Via Binary Linear Codes: Designs and Performance Limits Mahdi Soleymani∗, Mohammad Vahid Jamali∗, and Hessam Mahdavifar, Member, IEEE
1 Coded Computing via Binary Linear Codes: Designs and Performance Limits Mahdi Soleymani∗, Mohammad Vahid Jamali∗, and Hessam Mahdavifar, Member, IEEE Abstract—We consider the problem of coded distributed processing capabilities. A coded computing scheme aims to computing where a large linear computational job, such as a divide the job to k < n tasks and then to introduce n − k matrix multiplication, is divided into k smaller tasks, encoded redundant tasks using an (n; k) code, in order to alleviate the using an (n; k) linear code, and performed over n distributed nodes. The goal is to reduce the average execution time of effect of slower nodes, also referred to as stragglers. In such a the computational job. We provide a connection between the setup, it is often assumed that each node is assigned one task problem of characterizing the average execution time of a coded and hence, the total number of encoded tasks is n equal to the distributed computing system and the problem of analyzing the number of nodes. error probability of codes of length n used over erasure channels. Recently, there has been extensive research activities to Accordingly, we present closed-form expressions for the execution time using binary random linear codes and the best execution leverage coding schemes in order to boost the performance time any linear-coded distributed computing system can achieve. of distributed computing systems [6]–[18]. However, most It is also shown that there exist good binary linear codes that not of the work in the literature focus on the application of only attain (asymptotically) the best performance that any linear maximum distance separable (MDS) codes. -
ERROR CORRECTING CODES Definition (Alphabet)
ERROR CORRECTING CODES Definition (Alphabet) An alphabet is a finite set of symbols. Example: A simple example of an alphabet is the set A := fB; #; 17; P; $; 0; ug. Definition (Codeword) A codeword is a string of symbols in an alphabet. Example: In the alphabet A := fB; #; 17; P; $; 0; ug, some examples of codewords of length 4 are: P 17#u; 0B$#; uBuB; 0000: Definition (Code) A code is a set of codewords in an alphabet. Example: In the alphabet A := fB; #; 17; P; $; 0; ug, an example of a code is the set of 5 words: fP 17#u; 0B$#; uBuB; 0000;PP #$g: If all the codewords are known and recorded in some dictionary then it is possible to transmit messages (strings of codewords) to another entity over a noisy channel and detect and possibly correct errors. For example in the code C := fP 17#u; 0B$#; uBuB; 0000;PP #$g if the word 0B$# is sent and received as PB$#, then if we knew that only one error was made it can be determined that the letter P was an error which can be corrected by changing P to 0. Definition (Linear Code) A linear code is a code where the codewords form a finite abelian group under addition. Main Problem of Coding Theory: To construct an alphabet and a code in that alphabet so it is as easy as possible to detect and correct errors in transmissions of codewords. A key idea for solving this problem is the notion of Hamming distance. Definition (Hamming distance dH ) Let C be a code and let 0 0 0 0 w = w1w2 : : : wn; w = w1w2 : : : wn; 0 0 be two codewords in C where wi; wj are elements of the alphabet of C. -
Probabilistic Public-Key Encryption
PROBABILISTIC PUBLIC-KEY ENCRYPTION By Azymbek Beibyt Fundamentals Semantic Security A public-key cryptosystem is semantically secure if it’s computationally infeasible for opponent to derive any information about plaintext given only ciphertext and public key. Semantic Security = Cryptosystem Indistinguishability Fundamentals Semantic Security (Cont.) Semantic security are obtained using trapdoor (one- way) functions: - prime factorization in RSA - discrete logarithm problem in ElGamal Fundamentals Semantic Security (Cont.) Why not use trapdoor functions as before? ¨ The fact that f is a trapdoor function does not rule out the possibility of computing x from f (x) when x is of a special form. ¨ The fact that f is a trapdoor function does not rule out the possibility of easily computing some partial information about x (even every other bit of x) from f(x). Probabilistic Encryption New approach introduced by Shafi Goldwasser and Silvio Micali in 1983. ¨ Replace deterministic block encryption by probabilistic encryption of single bits. ¨ Proved to be hard to extract any information about plaintext under polynomially bounded computational resources, because is based on intractability of deciding Quadratic Residuosity modulo composite numbers whose factorization is unknown. Probabilistic Public -Key Cryptosystem General Idea (P, C, K, E, D, R), where R is a set of randomizers, encryption is public and decryption is secret and following properties should be satisfied: 1. , where b Є P, r Є R and if Probabilistic Public -Key Cryptosystem General Idea (Cont.) 2. Let ϵ be specified security parameter. Define probability distribution on C, which denotes the probability that y is the ciphertext given that K is the key and x is the plaintext . -
Improved List-Decodability of Random Linear Binary Codes
Improved list-decodability of random linear binary codes∗ Ray Li† and Mary Wootters‡ November 26, 2020 Abstract There has been a great deal of work establishing that random linear codes are as list- decodable as uniformly random codes, in the sense that a random linear binary code of rate 1 H(p) ǫ is (p, O(1/ǫ))-list-decodable with high probability. In this work, we show that such codes− are− (p,H(p)/ǫ + 2)-list-decodable with high probability, for any p (0, 1/2) and ǫ > 0. In addition to improving the constant in known list-size bounds, our argument—which∈ is quite simple—works simultaneously for all values of p, while previous works obtaining L = O(1/ǫ) patched together different arguments to cover different parameter regimes. Our approach is to strengthen an existential argument of (Guruswami, H˚astad, Sudan and Zuckerman, IEEE Trans. IT, 2002) to hold with high probability. To complement our up- per bound for random linear codes, we also improve an argument of (Guruswami, Narayanan, IEEE Trans. IT, 2014) to obtain an essentially tight lower bound of 1/ǫ on the list size of uniformly random codes; this implies that random linear codes are in fact more list-decodable than uniformly random codes, in the sense that the list sizes are strictly smaller. To demonstrate the applicability of these techniques, we use them to (a) obtain more in- formation about the distribution of list sizes of random linear codes and (b) to prove a similar result for random linear rank-metric codes. -
Coding Theory and Applications Solved Exercises and Problems Of
Coding Theory and Applications Solved Exercises and Problems of Linear Codes Enes Pasalic University of Primorska Koper, 2013 Contents 1 Preface 3 2 Problems 4 2 1 Preface This is a collection of solved exercises and problems of linear codes for students who have a working knowledge of coding theory. Its aim is to achieve a balance among the computational skills, theory, and applications of cyclic codes, while keeping the level suitable for beginning students. The contents are arranged to permit enough flexibility to allow the presentation of a traditional introduction to the subject, or to allow a more applied course. Enes Pasalic [email protected] 3 2 Problems In these exercises we consider some basic concepts of coding theory, that is we introduce the redundancy in the information bits and consider the possible improvements in terms of improved error probability of correct decoding. 1. (Error probability): Consider a code of length six n = 6 defined as, (a1; a2; a3; a2 + a3; a1 + a3; a1 + a2) where ai 2 f0; 1g. Here a1; a2; a3 are information bits and the remaining bits are redundancy (parity) bits. Compute the probability that the decoder makes an incorrect decision if the bit error probability is p = 0:001. The decoder computes the following entities b1 + b3 + b4 = s1 b1 + b3 + b5 == s2 b1 + b2 + b6 = s3 where b = (b1; b2; : : : ; b6) is a received vector. We represent the error vector as e = (e1; e2; : : : ; e6) and clearly if a vector (a1; a2; a3; a2+ a3; a1 + a3; a1 + a2) was transmitted then b = a + e, where '+' denotes bitwise mod 2 addition. -
A CCA2 Secure Public Key Encryption Scheme Based on the Mceliece Assumptions in the Standard Model
A CCA2 Secure Public Key Encryption Scheme Based on the McEliece Assumptions in the Standard Model Rafael Dowsley1, J¨ornM¨uller-Quade2, Anderson C. A. Nascimento1 1 Department of Electrical Engineering, University of Brasilia. Campus Universit´arioDarcy Ribeiro,Brasilia, CEP: 70910-900, Brazil, Email:[email protected], [email protected] 2 Universit¨atKarlsruhe, Institut f¨urAlgorithmen und Kognitive Systeme. Am Fasanengarten 5, 76128 Karlsruhe, Germany. E-mail: [email protected] We show that a recently proposed construction by Rosen and Segev can be used for obtaining the first public key encryption scheme based on the McEliece assumptions which is secure against adaptive chosen ciphertext attacks in the standard model. 1 Introduction Indistinguishability of messages under adaptive chosen ciphertext attacks is the strongest known notion of security for public key encryption schemes (PKE). Many computational assumptions have been used in the literature for obtain- ing cryptosystems meeting such a strong security requirements. Given one-way trapdoor permutations, we know how to obtain CCA2 security from any seman- tically secure public key cryptosystem [14, 20, 12]. Efficient constructions are also known based on number-theoretic assumptions [6] or on identity based encryp- tion schemes [3]. Obtaining a CCA2 secure cryptosystem (even an inefficient one) based on the McEliece assumptions in the standard model has been an open problem in this area for quite a while. Recently, Rosen and Segev proposed an elegant and simple new computa- tional assumption for obtaining CCA2 secure PKEs: correlated products [19]. They provided constructions of correlated products based on the existence of certain lossy trapdoor functions [16] which in turn can be based on the deci- sional Diffie-Hellman problem and on Paillier's decisional residuosity problem [16]. -
Reed-Solomon Encoding and Decoding
Bachelor's Thesis Degree Programme in Information Technology 2011 León van de Pavert REED-SOLOMON ENCODING AND DECODING A Visual Representation i Bachelor's Thesis | Abstract Turku University of Applied Sciences Degree Programme in Information Technology Spring 2011 | 37 pages Instructor: Hazem Al-Bermanei León van de Pavert REED-SOLOMON ENCODING AND DECODING The capacity of a binary channel is increased by adding extra bits to this data. This improves the quality of digital data. The process of adding redundant bits is known as channel encod- ing. In many situations, errors are not distributed at random but occur in bursts. For example, scratches, dust or fingerprints on a compact disc (CD) introduce errors on neighbouring data bits. Cross-interleaved Reed-Solomon codes (CIRC) are particularly well-suited for detection and correction of burst errors and erasures. Interleaving redistributes the data over many blocks of code. The double encoding has the first code declaring erasures. The second code corrects them. The purpose of this thesis is to present Reed-Solomon error correction codes in relation to burst errors. In particular, this thesis visualises the mechanism of cross-interleaving and its ability to allow for detection and correction of burst errors. KEYWORDS: Coding theory, Reed-Solomon code, burst errors, cross-interleaving, compact disc ii ACKNOWLEDGEMENTS It is a pleasure to thank those who supported me making this thesis possible. I am thankful to my supervisor, Hazem Al-Bermanei, whose intricate know- ledge of coding theory inspired me, and whose lectures, encouragement, and support enabled me to develop an understanding of this subject. -
Decoding Algorithms of Reed-Solomon Code
Master’s Thesis Computer Science Thesis no: MCS-2011-26 October 2011 Decoding algorithms of Reed-Solomon code Szymon Czynszak School of Computing Blekinge Institute of Technology SE – 371 79 Karlskrona Sweden This thesis is submitted to the School of Computing at Blekinge Institute o f Technology in partial fulfillment of the requirements for the degree of Master of Science in Computer Science. The thesis is equivalent to 20 weeks of full time studies. Contact Information: Author(s): Szymon Czynszak E-mail: [email protected] University advisor(s): Mr Janusz Biernat, prof. PWR, dr hab. in ż. Politechnika Wrocławska E-mail: [email protected] Mr Martin Boldt, dr Blekinge Institute of Technology E-mail: [email protected] Internet : www.bth.se/com School of Computing Phone : +46 455 38 50 00 Blekinge Institute of Technology Fax : +46 455 38 50 57 SE – 371 79 Karlskrona Sweden ii Abstract Reed-Solomon code is nowadays broadly used in many fields of data trans- mission. Using of error correction codes is divided into two main operations: information coding before sending information into communication channel and decoding received information at the other side. There are vast of decod- ing algorithms of Reed-Solomon codes, which have specific features. There is needed knowledge of features of algorithms to choose correct algorithm which satisfies requirements of system. There are evaluated cyclic decoding algo- rithm, Peterson-Gorenstein-Zierler algorithm, Berlekamp-Massey algorithm, Sugiyama algorithm with erasures and without erasures and Guruswami- Sudan algorithm. There was done implementation of algorithms in software and in hardware.