May 02, 2018 Microsoft researchers leveraged resource estimation techniques to analyze the cost of mounting quantum attacks on real-world public-key cryptographic schemes. Case in point are RSA encryption, where the underlying hard problem is that of factoring large integers and elliptic curve cryptography (ECC), where the underlying problem is that of computing discrete logarithms.

Lattice-based cryptography is the generic term for constructions of cryptographic primitives that involve lattices, either in the construction itself or in the security proof. Lattice-based constructions are currently important candidates for post-quantum cryptography. Unlike more widely used and known public-key schemes such as the RSA, Diffie-Hellman or elliptic-curve cryptosystems, which are easily attacked by a quantum computer, some lattice-based constructions appear to be resistant to attack by both classical and quantum computers. Furthermore, many lattice-based constructions are considered to be secure under the assumption that certain well-studied computational lattice problems cannot be solved efficiently.


In 1996, Miklós Ajtai introduced the first lattice-based cryptographic construction whose security could be based on the hardness of well-studied lattice problems,[1] and Cynthia Dwork showed that a certain average-case lattice problem, known as Short Integer Solutions (SIS), is at least as hard to solve as a worst-case lattice problem.[2] He then showed a cryptographic hash function whose security is equivalent to the computational hardness of SIS

In 1998, Jeffrey Hoffstein, Jill Pipher, and Joseph H. Silverman introduced a lattice-based public-key encryption scheme, known as NTRU.[3] However, their scheme is not known to be at least as hard as solving a worst-case lattice problem.

The first lattice-based public-key encryption scheme whose security was proven under worst-case hardness assumptions was introduced by Oded Regev in 2005,[4] together with the Learning with Errors problem (LWE). Since then, much follow-up work has focused on improving Regev's security proof[5][6] and improving the efficiency of the original scheme.[7][8][9][10] Much more work has been devoted to constructing additional cryptographic primitives based on LWE and related problems. For example, in 2009, Craig Gentry introduced the first fully homomorphic encryption scheme, which was based on a lattice problem.[11]

Key Generation In Quantum Encryption Schemes Pdf

Mathematical background[edit]

A latticeLRn{displaystyle Lsubset mathbb {R} ^{n}} is the set of all integer linear combinations of basis vectors b1,,bnRn{displaystyle mathbf {b} _{1},ldots ,mathbf {b} _{n}in mathbb {R} ^{n}}. I.e., L={aibi:aiZ}.{displaystyle L={Big {}sum a_{i}mathbf {b} _{i} : a_{i}in mathbb {Z} {Big }};.}For example, Zn{displaystyle mathbb {Z} ^{n}} is a lattice, generated by the standard orthonormal basis for Rn{displaystyle mathbb {R} ^{n}}. Crucially, the basis for a lattice is not unique. For example, the vectors (3,1,4){displaystyle (3,1,4)}, (1,5,9){displaystyle (1,5,9)}, and (2,1,0){displaystyle (2,-1,0)} form an alternative basis for Z3{displaystyle mathbb {Z} ^{3}}.

The most important lattice-based computational problem is the Shortest Vector Problem (SVP or sometimes GapSVP), which asks us to approximate the minimal Euclidean length of a non-zero lattice vector. This problem is thought to be hard to solve efficiently, even with approximation factors that are polynomial in n{displaystyle n}, and even with a quantum computer. Many (though not all) lattice-based cryptographic constructions are known to be secure if SVP is in fact hard in this regime.

Selected lattice-based cryptosystems[edit]

Encryption schemes[edit]

  • Peikert's Ring - Learning With Errors (Ring-LWE) Key Exchange[8]


  • Güneysu, Lyubashevsky, and Poppleman's Ring - Learning with Errors (Ring-LWE) Signature[12]

Hash functions[edit]

  • LASH (Lattice Based Hash Function)[13][14]

Fully homomorphic encryption[edit]

  • Gentry's original scheme.[11]
  • Brakerski and Vaikuntanathan.[15][16]


Lattice-based cryptographic constructions are the leading candidates for public-keypost-quantum cryptography.[17] Indeed, the main alternative forms of public-key cryptography are schemes based on the hardness of factoring and related problems and schemes based on the hardness of the discrete logarithm and related problems. However, both factoring and the discrete logarithm are known to be solvable in polynomial time on a quantum computer.[18] Furthermore, algorithms for factorization tend to yield algorithms for discrete logarithm, and vice versa. This further motivates the study of constructions based on alternative assumptions, such as the hardness of lattice problems.

Many lattice-based cryptographic schemes are known to be secure assuming the worst-case hardness of certain lattice problems.[1][4][5] I.e., if there exists an algorithm that can efficiently break the cryptographic scheme with non-negligible probability, then there exists an efficient algorithm that solves a certain lattice problem on any input. In contrast, cryptographic schemes based on, e.g., factoring would be broken if factoring was easy 'on an average input,' even if factoring was in fact hard in the worst case. However, for the more efficient and practical lattice-based constructions (such as schemes based on NTRU and even schemes based on LWE with more aggressive parameters), such worst-case hardness results are not known. For some schemes, worst-case hardness results are known only for certain structured lattices[7] or not at all.


For many cryptographic primitives, the only known constructions are based on lattices or closely related objects. These primitives include fully homomorphic encryption,[11]indistinguishability obfuscation,[19]cryptographic multilinear maps, and functional encryption.[19]

See also[edit]


Key Generation In Quantum Encryption Schemes 2017

  1. ^ abAjtai, Miklós (1996). 'Generating Hard Instances of Lattice Problems'. Proceedings of the Twenty-Eighth Annual ACM Symposium on Theory of Computing. pp. 99–108. CiteSeerX10. doi:10.1145/237814.237838. ISBN978-0-89791-785-8.
  2. ^Public-Key Cryptosystem with Worst-Case/Average-Case Equivalence
  3. ^Hoffstein, Jeffrey; Pipher, Jill; Silverman, Joseph H. (1998). 'NTRU: A ring-based public key cryptosystem'. Algorithmic Number Theory. Lecture Notes in Computer Science. 1423. pp. 267–288. CiteSeerX10. doi:10.1007/bfb0054868. ISBN978-3-540-64657-0.
  4. ^ abRegev, Oded (2005-01-01). 'On lattices, learning with errors, random linear codes, and cryptography'. Proceedings of the thirty-seventh annual ACM symposium on Theory of computing - STOC '05. ACM. pp. 84–93. CiteSeerX10. doi:10.1145/1060590.1060603. ISBN978-1581139600.
  5. ^ abPeikert, Chris (2009-01-01). 'Public-key cryptosystems from the worst-case shortest vector problem'. Proceedings of the 41st annual ACM symposium on Symposium on theory of computing - STOC '09. ACM. pp. 333–342. CiteSeerX10. doi:10.1145/1536414.1536461. ISBN9781605585062.
  6. ^Brakerski, Zvika; Langlois, Adeline; Peikert, Chris; Regev, Oded; Stehlé, Damien (2013-01-01). 'Classical hardness of learning with errors'. Proceedings of the 45th annual ACM symposium on Symposium on theory of computing - STOC '13. ACM. pp. 575–584. arXiv:1306.0281. doi:10.1145/2488608.2488680. ISBN9781450320290.
  7. ^ abLyubashevsky, Vadim; Peikert, Chris; Regev, Oded (2010-05-30). On Ideal Lattices and Learning with Errors over Rings. Advances in Cryptology – EUROCRYPT 2010. Lecture Notes in Computer Science. 6110. pp. 1–23. CiteSeerX10.1.1.352.8218. doi:10.1007/978-3-642-13190-5_1. ISBN978-3-642-13189-9.
  8. ^ abPeikert, Chris (2014-07-16). 'Lattice Cryptography for the Internet'(PDF). IACR. Retrieved 2017-01-11.
  9. ^Alkim, Erdem; Ducas, Léo; Pöppelmann, Thomas; Schwabe, Peter (2015-01-01). 'Post-quantum key exchange - a new hope'.Cite journal requires journal= (help)
  10. ^Bos, Joppe; Costello, Craig; Ducas, Léo; Mironov, Ilya; Naehrig, Michael; Nikolaenko, Valeria; Raghunathan, Ananth; Stebila, Douglas (2016-01-01). 'Frodo: Take off the ring! Practical, Quantum-Secure Key Exchange from LWE'.Cite journal requires journal= (help)
  11. ^ abcGentry, Craig (2009-01-01). A Fully Homomorphic Encryption Scheme (Thesis). Stanford, CA, USA: Stanford University.
  12. ^Güneysu, Tim; Lyubashevsky, Vadim; Pöppelmann, Thomas (2012). 'Practical Lattice-Based Cryptography: A Signature Scheme for Embedded Systems'(PDF). Cryptographic Hardware and Embedded Systems – CHES 2012. Lecture Notes in Computer Science. 7428. IACR. pp. 530–547. doi:10.1007/978-3-642-33027-8_31. ISBN978-3-642-33026-1. Retrieved 2017-01-11.
  13. ^'LASH: A Lattice Based Hash Function'. Archived from the original on October 16, 2008. Retrieved 2008-07-31.CS1 maint: BOT: original-url status unknown (link) (broken)
  14. ^Scott Contini, Krystian Matusiewicz, Josef Pieprzyk, Ron Steinfeld, Jian Guo, San Ling and Huaxiong Wang (2008). 'Cryptanalysis of LASH'(PDF). Fast Software Encryption. Lecture Notes in Computer Science. 5086. pp. 207–223. doi:10.1007/978-3-540-71039-4_13. ISBN978-3-540-71038-7.CS1 maint: uses authors parameter (link)
  15. ^Brakerski, Zvika; Vaikuntanathan, Vinod (2011). 'Efficient Fully Homomorphic Encryption from (Standard) LWE'.Cite journal requires journal= (help)
  16. ^Brakerski, Zvika; Vaikuntanathan, Vinod (2013). 'Lattice-Based FHE as Secure as PKE'.Cite journal requires journal= (help)
  17. ^Micciancio, Daniele; Regev, Oded (2008-07-22). 'Lattice-based cryptography'(PDF). Retrieved 2017-01-11.Cite journal requires journal= (help)
  18. ^Shor, Peter W. (1997-10-01). 'Polynomial-Time Algorithms for Prime Factorization and Discrete Logarithms on a Quantum Computer'. SIAM Journal on Computing. 26 (5): 1484–1509. arXiv:quant-ph/9508027. doi:10.1137/S0097539795293172. ISSN0097-5397.
  19. ^ abGarg, Sanjam; Gentry, Craig; Halevi, Shai; Raykova, Mariana; Sahai, Amit; Waters, Brent (2013-01-01). 'Candidate Indistinguishability Obfuscation and Functional Encryption for all circuits'. CiteSeerX10.1.1.400.6501.Cite journal requires journal= (help)


  • Oded Goldreich, Shafi Goldwasser, and Shai Halevi. 'Public-key cryptosystems from lattice reduction problems'. In CRYPTO ’97: Proceedings of the 17th Annual International Cryptology Conference on Advances in Cryptology, pages 112–131, London, UK, 1997. Springer-Verlag.
  • Phong Q. Nguyen. 'Cryptanalysis of the Goldreich–Goldwasser–Halevi cryptosystem from crypto ’97'. In CRYPTO ’99: Proceedings of the 19th Annual International Cryptology Conference on Advances in Cryptology, pages 288–304, London, UK, 1999. Springer-Verlag.
  • Oded Regev. Lattice-based cryptography. In Advances in cryptology (CRYPTO), pages 131–141, 2006.
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