Lattice-based cryptography

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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 could, theoretically, be defeated using Shor's algorithm on 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] She 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]

Mathematical background[edit]

In linear algebra, a lattice is the set of all integer linear combinations of vectors from a basis of . In other words, For example, is a lattice, generated by the standard basis for . Crucially, the basis for a lattice is not unique. For example, the vectors , , and form an alternative basis for .

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 , 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]


Hash functions[edit]

Fully homomorphic encryption[edit]

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


Lattice-based cryptographic constructions are the leading candidates for public-key post-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]


  1. ^ a b Ajtai, Miklós (1996). "Generating Hard Instances of Lattice Problems". Proceedings of the Twenty-Eighth Annual ACM Symposium on Theory of Computing. pp. 99–108. CiteSeerX doi:10.1145/237814.237838. ISBN 978-0-89791-785-8. S2CID 6864824.
  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. Vol. 1423. pp. 267–288. CiteSeerX doi:10.1007/bfb0054868. ISBN 978-3-540-64657-0.
  4. ^ a b Regev, 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. CiteSeerX doi:10.1145/1060590.1060603. ISBN 978-1581139600. S2CID 53223958.
  5. ^ a b Peikert, 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. CiteSeerX doi:10.1145/1536414.1536461. ISBN 9781605585062. S2CID 1864880.
  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. ISBN 9781450320290. S2CID 6005009.
  7. ^ a b Lyubashevsky, 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. Vol. 6110. pp. 1–23. CiteSeerX doi:10.1007/978-3-642-13190-5_1. ISBN 978-3-642-13189-9.
  8. ^ a b Peikert, 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}}: 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}}: Cite journal requires |journal= (help)
  11. ^ a b c Gentry, 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. Vol. 7428. IACR. pp. 530–547. doi:10.1007/978-3-642-33027-8_31. ISBN 978-3-642-33026-1. Retrieved 2017-01-11.
  13. ^ "LASH: A Lattice Based Hash Function". Archived from the original on October 16, 2008. Retrieved 2008-07-31.{{cite web}}: 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. Vol. 5086. pp. 207–223. doi:10.1007/978-3-540-71039-4_13. ISBN 978-3-540-71038-7.{{cite book}}: CS1 maint: uses authors parameter (link)
  15. ^ Brakerski, Zvika; Vaikuntanathan, Vinod (2011). "Efficient Fully Homomorphic Encryption from (Standard) LWE". {{cite journal}}: Cite journal requires |journal= (help)
  16. ^ Brakerski, Zvika; Vaikuntanathan, Vinod (2013). "Lattice-Based FHE as Secure as PKE". {{cite journal}}: Cite journal requires |journal= (help)
  17. ^ Micciancio, Daniele; Regev, Oded (2008-07-22). "Lattice-based cryptography" (PDF). Retrieved 2017-01-11. {{cite journal}}: 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. ISSN 0097-5397. S2CID 2337707.
  19. ^ a b Garg, Sanjam; Gentry, Craig; Halevi, Shai; Raykova, Mariana; Sahai, Amit; Waters, Brent (2013-01-01). "Candidate Indistinguishability Obfuscation and Functional Encryption for all circuits". CiteSeerX {{cite journal}}: 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.