Choosing Ntruencrypt Parameters in Light of Combined Lattice Reduction and MITM Approaches
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Etsi Gr Qsc 001 V1.1.1 (2016-07)
ETSI GR QSC 001 V1.1.1 (2016-07) GROUP REPORT Quantum-Safe Cryptography (QSC); Quantum-safe algorithmic framework 2 ETSI GR QSC 001 V1.1.1 (2016-07) Reference DGR/QSC-001 Keywords algorithm, authentication, confidentiality, security ETSI 650 Route des Lucioles F-06921 Sophia Antipolis Cedex - FRANCE Tel.: +33 4 92 94 42 00 Fax: +33 4 93 65 47 16 Siret N° 348 623 562 00017 - NAF 742 C Association à but non lucratif enregistrée à la Sous-Préfecture de Grasse (06) N° 7803/88 Important notice The present document can be downloaded from: http://www.etsi.org/standards-search The present document may be made available in electronic versions and/or in print. The content of any electronic and/or print versions of the present document shall not be modified without the prior written authorization of ETSI. In case of any existing or perceived difference in contents between such versions and/or in print, the only prevailing document is the print of the Portable Document Format (PDF) version kept on a specific network drive within ETSI Secretariat. Users of the present document should be aware that the document may be subject to revision or change of status. Information on the current status of this and other ETSI documents is available at https://portal.etsi.org/TB/ETSIDeliverableStatus.aspx If you find errors in the present document, please send your comment to one of the following services: https://portal.etsi.org/People/CommiteeSupportStaff.aspx Copyright Notification No part may be reproduced or utilized in any form or by any means, electronic or mechanical, including photocopying and microfilm except as authorized by written permission of ETSI. -
Circuit-Extension Handshakes for Tor Achieving Forward Secrecy in a Quantum World
Proceedings on Privacy Enhancing Technologies ; 2016 (4):219–236 John M. Schanck*, William Whyte, and Zhenfei Zhang Circuit-extension handshakes for Tor achieving forward secrecy in a quantum world Abstract: We propose a circuit extension handshake for 2. Anonymity: Some one-way authenticated key ex- Tor that is forward secure against adversaries who gain change protocols, such as ntor [13], guarantee that quantum computing capabilities after session negotia- the unauthenticated peer does not reveal their iden- tion. In doing so, we refine the notion of an authen- tity just by participating in the protocol. Such pro- ticated and confidential channel establishment (ACCE) tocols are deemed one-way anonymous. protocol and define pre-quantum, transitional, and post- 3. Forward Secrecy: A protocol provides forward quantum ACCE security. These new definitions reflect secrecy if the compromise of a party’s long-term the types of adversaries that a protocol might be de- key material does not affect the secrecy of session signed to resist. We prove that, with some small mod- keys negotiated prior to the compromise. Forward ifications, the currently deployed Tor circuit extension secrecy is typically achieved by mixing long-term handshake, ntor, provides pre-quantum ACCE security. key material with ephemeral keys that are discarded We then prove that our new protocol, when instantiated as soon as the session has been established. with a post-quantum key encapsulation mechanism, Forward secret protocols are a particularly effective tool achieves the stronger notion of transitional ACCE se- for resisting mass surveillance as they resist a broad curity. Finally, we instantiate our protocol with NTRU- class of harvest-then-decrypt attacks. -
Arxiv:Cs/0601091V2
Communication Over MIMO Broadcast Channels Using Lattice-Basis Reduction1 Mahmoud Taherzadeh, Amin Mobasher, and Amir K. Khandani Coding & Signal Transmission Laboratory Department of Electrical & Computer Engineering University of Waterloo Waterloo, Ontario, Canada, N2L 3G1 Abstract A simple scheme for communication over MIMO broadcast channels is introduced which adopts the lattice reduction technique to improve the naive channel inversion method. Lattice basis reduction helps us to reduce the average transmitted energy by modifying the region which includes the constellation points. Simulation results show that the proposed scheme performs well, and as compared to the more complex methods (such as the perturbation method [1]) has a negligible loss. Moreover, the proposed method is extended to the case of different rates for different users. The asymptotic behavior (SNR ) of the symbol error rate of the proposed method and the −→ ∞ perturbation technique, and also the outage probability for the case of fixed-rate users is analyzed. It is shown that the proposed method, based on LLL lattice reduction, achieves the optimum asymptotic slope of symbol-error-rate (called the precoding diversity). Also, the outage probability for the case of fixed sum-rate is analyzed. I. INTRODUCTION In the recent years, communications over multiple-antenna fading channels has attracted the attention of many researchers. Initially, the main interest has been on the point-to-point Multiple-Input Multiple-Output (MIMO) communications [2]–[6]. In [2] and [3], the authors have shown that the capacity of a MIMO point-to-point channel increases linearly with the arXiv:cs/0601091v2 [cs.IT] 18 Jun 2007 minimum number of the transmit and the receive antennas. -
Public Key Cryptography And
PublicPublic KeyKey CryptographyCryptography andand RSARSA Raj Jain Washington University in Saint Louis Saint Louis, MO 63130 [email protected] Audio/Video recordings of this lecture are available at: http://www.cse.wustl.edu/~jain/cse571-11/ Washington University in St. Louis CSE571S ©2011 Raj Jain 9-1 OverviewOverview 1. Public Key Encryption 2. Symmetric vs. Public-Key 3. RSA Public Key Encryption 4. RSA Key Construction 5. Optimizing Private Key Operations 6. RSA Security These slides are based partly on Lawrie Brown’s slides supplied with William Stallings’s book “Cryptography and Network Security: Principles and Practice,” 5th Ed, 2011. Washington University in St. Louis CSE571S ©2011 Raj Jain 9-2 PublicPublic KeyKey EncryptionEncryption Invented in 1975 by Diffie and Hellman at Stanford Encrypted_Message = Encrypt(Key1, Message) Message = Decrypt(Key2, Encrypted_Message) Key1 Key2 Text Ciphertext Text Keys are interchangeable: Key2 Key1 Text Ciphertext Text One key is made public while the other is kept private Sender knows only public key of the receiver Asymmetric Washington University in St. Louis CSE571S ©2011 Raj Jain 9-3 PublicPublic KeyKey EncryptionEncryption ExampleExample Rivest, Shamir, and Adleman at MIT RSA: Encrypted_Message = m3 mod 187 Message = Encrypted_Message107 mod 187 Key1 = <3,187>, Key2 = <107,187> Message = 5 Encrypted Message = 53 = 125 Message = 125107 mod 187 = 5 = 125(64+32+8+2+1) mod 187 = {(12564 mod 187)(12532 mod 187)... (1252 mod 187)(125 mod 187)} mod 187 Washington University in -
Lectures on the NTRU Encryption Algorithm and Digital Signature Scheme: Grenoble, June 2002
Lectures on the NTRU encryption algorithm and digital signature scheme: Grenoble, June 2002 J. Pipher Brown University, Providence RI 02912 1 Lecture 1 1.1 Integer lattices Lattices have been studied by cryptographers for quite some time, in both the field of cryptanalysis (see for example [16{18]) and as a source of hard problems on which to build encryption schemes (see [1, 8, 9]). In this lecture, we describe the NTRU encryption algorithm, and the lattice problems on which this is based. We begin with some definitions and a brief overview of lattices. If a ; a ; :::; a are n independent vectors in Rm, n m, then the 1 2 n ≤ integer lattice with these vectors as basis is the set = n x a : x L f 1 i i i 2 Z . A lattice is often represented as matrix A whose rows are the basis g P vectors a1; :::; an. The elements of the lattice are simply the vectors of the form vT A, which denotes the usual matrix multiplication. We will specialize for now to the situation when the rank of the lattice and the dimension are the same (n = m). The determinant of a lattice det( ) is the volume of the fundamen- L tal parallelepiped spanned by the basis vectors. By the Gram-Schmidt process, one can obtain a basis for the vector space generated by , and L the det( ) will just be the product of these orthogonal vectors. Note that L these vectors are not a basis for as a lattice, since will not usually L L possess an orthogonal basis. -
Solving Hard Lattice Problems and the Security of Lattice-Based Cryptosystems
Solving Hard Lattice Problems and the Security of Lattice-Based Cryptosystems † Thijs Laarhoven∗ Joop van de Pol Benne de Weger∗ September 10, 2012 Abstract This paper is a tutorial introduction to the present state-of-the-art in the field of security of lattice- based cryptosystems. After a short introduction to lattices, we describe the main hard problems in lattice theory that cryptosystems base their security on, and we present the main methods of attacking these hard problems, based on lattice basis reduction. We show how to find shortest vectors in lattices, which can be used to improve basis reduction algorithms. Finally we give a framework for assessing the security of cryptosystems based on these hard problems. 1 Introduction Lattice-based cryptography is a quickly expanding field. The last two decades have seen exciting devel- opments, both in using lattices in cryptanalysis and in building public key cryptosystems on hard lattice problems. In the latter category we could mention the systems of Ajtai and Dwork [AD], Goldreich, Goldwasser and Halevi [GGH2], the NTRU cryptosystem [HPS], and systems built on Small Integer Solu- tions [MR1] problems and Learning With Errors [R1] problems. In the last few years these developments culminated in the advent of the first fully homomorphic encryption scheme by Gentry [Ge]. A major issue in this field is to base key length recommendations on a firm understanding of the hardness of the underlying lattice problems. The general feeling among the experts is that the present understanding is not yet on the same level as the understanding of, e.g., factoring or discrete logarithms. -
Ch 13 Digital Signature
1 CH 13 DIGITAL SIGNATURE Cryptography and Network Security HanJung Mason Yun 2 Index 13.1 Digital Signatures 13.2 Elgamal Digital Signature Scheme 13.3 Schnorr Digital Signature Scheme 13.4 NIST Digital Signature Algorithm 13.6 RSA-PSS Digital Signature Algorithm 3 13.1 Digital Signature - Properties • It must verify the author and the date and time of the signature. • It must authenticate the contents at the time of the signature. • It must be verifiable by third parties, to resolve disputes. • The digital signature function includes authentication. 4 5 6 Attacks and Forgeries • Key-Only attack • Known message attack • Generic chosen message attack • Directed chosen message attack • Adaptive chosen message attack 7 Attacks and Forgeries • Total break • Universal forgery • Selective forgery • Existential forgery 8 Digital Signature Requirements • It must be a bit pattern that depends on the message. • It must use some information unique to the sender to prevent both forgery and denial. • It must be relatively easy to produce the digital signature. • It must be relatively easy to recognize and verify the digital signature. • It must be computationally infeasible to forge a digital signature, either by constructing a new message for an existing digital signature or by constructing a fraudulent digital signature for a given message. • It must be practical to retain a copy of the digital signature in storage. 9 Direct Digital Signature • Digital signature scheme that involves only the communication parties. • It must authenticate the contents at the time of the signature. • It must be verifiable by third parties, to resolve disputes. • Thus, the digital signature function includes the authentication function. -
On Ideal Lattices and Learning with Errors Over Rings∗
On Ideal Lattices and Learning with Errors Over Rings∗ Vadim Lyubashevskyy Chris Peikertz Oded Regevx June 25, 2013 Abstract The “learning with errors” (LWE) problem is to distinguish random linear equations, which have been perturbed by a small amount of noise, from truly uniform ones. The problem has been shown to be as hard as worst-case lattice problems, and in recent years it has served as the foundation for a plethora of cryptographic applications. Unfortunately, these applications are rather inefficient due to an inherent quadratic overhead in the use of LWE. A main open question was whether LWE and its applications could be made truly efficient by exploiting extra algebraic structure, as was done for lattice-based hash functions (and related primitives). We resolve this question in the affirmative by introducing an algebraic variant of LWE called ring- LWE, and proving that it too enjoys very strong hardness guarantees. Specifically, we show that the ring-LWE distribution is pseudorandom, assuming that worst-case problems on ideal lattices are hard for polynomial-time quantum algorithms. Applications include the first truly practical lattice-based public-key cryptosystem with an efficient security reduction; moreover, many of the other applications of LWE can be made much more efficient through the use of ring-LWE. 1 Introduction Over the last decade, lattices have emerged as a very attractive foundation for cryptography. The appeal of lattice-based primitives stems from the fact that their security can often be based on worst-case hardness assumptions, and that they appear to remain secure even against quantum computers. -
Implementation and Performance Evaluation of XTR Over Wireless Network
Implementation and Performance Evaluation of XTR over Wireless Network By Basem Shihada [email protected] Dept. of Computer Science 200 University Avenue West Waterloo, Ontario, Canada (519) 888-4567 ext. 6238 CS 887 Final Project 19th of April 2002 Implementation and Performance Evaluation of XTR over Wireless Network 1. Abstract Wireless systems require reliable data transmission, large bandwidth and maximum data security. Most current implementations of wireless security algorithms perform lots of operations on the wireless device. This result in a large number of computation overhead, thus reducing the device performance. Furthermore, many current implementations do not provide a fast level of security measures such as client authentication, authorization, data validation and data encryption. XTR is an abbreviation of Efficient and Compact Subgroup Trace Representation (ECSTR). Developed by Arjen Lenstra & Eric Verheul and considered a new public key cryptographic security system that merges high level of security GF(p6) with less number of computation GF(p2). The claim here is that XTR has less communication requirements, and significant computation advantages, which indicate that XTR is suitable for the small computing devices such as, wireless devices, wireless internet, and general wireless applications. The hoping result is a more flexible and powerful secure wireless network that can be easily used for application deployment. This project presents an implementation and performance evaluation to XTR public key cryptographic system over wireless network. The goal of this project is to develop an efficient and portable secure wireless network, which perform a variety of wireless applications in a secure manner. The project literately surveys XTR mathematical and theoretical background as well as system implementation and deployment over wireless network. -
Key Improvements to XTR
To appear in Advances in Cryptology|Asiacrypt 2000, Lecture Notes in Computer Science 1976, Springer-Verlag 2000, 220-223. Key improvements to XTR Arjen K. Lenstra1, Eric R. Verheul2 1 Citibank, N.A., Technical University Eindhoven, 1 North Gate Road, Mendham, NJ 07945-3104, U.S.A., [email protected] 2 PricewaterhouseCoopers, GRMS Crypto Group, Goudsbloemstraat 14, 5644 KE Eindhoven, The Netherlands, Eric.Verheul@[nl.pwcglobal.com, pobox.com] Abstract. This paper describes improved methods for XTR key rep- resentation and parameter generation (cf. [4]). If the ¯eld characteristic is properly chosen, the size of the XTR public key for signature appli- cations can be reduced by a factor of three at the cost of a small one time computation for the recipient of the key. Furthermore, the para- meter set-up for an XTR system can be simpli¯ed because the trace of a proper subgroup generator can, with very high probability, be com- puted directly, thus avoiding the probabilistic approach from [4]. These non-trivial extensions further enhance the practical potential of XTR. 1 Introduction In [1] it was shown that conjugates of elements of a subgroup of GF(p6)¤ of order 2 dividing Á6(p) = p ¡ p + 1 can be represented using 2 log2(p) bits, as opposed to the 6 log2(p) bits that would be required for their traditional representation. In [4] an improved version of the method from [1] was introduced that achieves the same communication advantage at a much lower computational cost. The resulting representation method is referred to as XTR, which stands for E±cient and Compact Subgroup Trace Representation. -
On Lattices, Learning with Errors, Random Linear Codes, and Cryptography
On Lattices, Learning with Errors, Random Linear Codes, and Cryptography Oded Regev ¤ May 2, 2009 Abstract Our main result is a reduction from worst-case lattice problems such as GAPSVP and SIVP to a certain learning problem. This learning problem is a natural extension of the ‘learning from parity with error’ problem to higher moduli. It can also be viewed as the problem of decoding from a random linear code. This, we believe, gives a strong indication that these problems are hard. Our reduction, however, is quantum. Hence, an efficient solution to the learning problem implies a quantum algorithm for GAPSVP and SIVP. A main open question is whether this reduction can be made classical (i.e., non-quantum). We also present a (classical) public-key cryptosystem whose security is based on the hardness of the learning problem. By the main result, its security is also based on the worst-case quantum hardness of GAPSVP and SIVP. The new cryptosystem is much more efficient than previous lattice-based cryp- tosystems: the public key is of size O~(n2) and encrypting a message increases its size by a factor of O~(n) (in previous cryptosystems these values are O~(n4) and O~(n2), respectively). In fact, under the assumption that all parties share a random bit string of length O~(n2), the size of the public key can be reduced to O~(n). 1 Introduction Main theorem. For an integer n ¸ 1 and a real number " ¸ 0, consider the ‘learning from parity with n error’ problem, defined as follows: the goal is to find an unknown s 2 Z2 given a list of ‘equations with errors’ hs; a1i ¼" b1 (mod 2) hs; a2i ¼" b2 (mod 2) . -
Efficient Encryption on Limited Devices
Rochester Institute of Technology RIT Scholar Works Theses 2006 Efficient encryption on limited devices Roderic Campbell Follow this and additional works at: https://scholarworks.rit.edu/theses Recommended Citation Campbell, Roderic, "Efficient encryption on limited devices" (2006). Thesis. Rochester Institute of Technology. Accessed from This Master's Project is brought to you for free and open access by RIT Scholar Works. It has been accepted for inclusion in Theses by an authorized administrator of RIT Scholar Works. For more information, please contact [email protected]. Masters Project Proposal: Efficient Encryption on Limited Devices Roderic Campbell Department of Computer Science Rochester Institute of Technology Rochester, NY, USA [email protected] June 24, 2004 ________________________________________ Chair: Prof. Alan Kaminsky Date ________________________________________ Reader: Prof. Hans-Peter Bischof Date ________________________________________ Observer: Prof. Leonid Reznik Date 1 1 Summary As the capstone of my Master’s education, I intend to perform a comparison of Elliptic Curve Cryptography(ECC) and The XTR Public Key System to the well known RSA encryption algorithm. The purpose of such a project is to provide a further understanding of such types of encryption, as well as present an analysis and recommendation for the appropriate technique for given circumstances. This comparison will be done by developing a series of tests on which to run identical tasks using each of the previously mentioned algorithms. Metrics such as running time, maximum and average memory usage will be measured as applicable. There are four main goals of Crypto-systems: Confidentiality, Data Integrity, Authentication and Non-repudiation[5]. This implementation deals only with confidentiality of symmetric key exchange.