Crypto 101 Lvh
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An Enhanced Advanced Encryption Standard Algorithm
ISSN 2278 – 3091 International Journal of Advanced Trends in Computer Science and Engineering (IJATCSE), Vol. 4 , No.4 Pages : 28 - 33 (2015) Special Issue of ICEEC 2015 - Held on August 24, 2015 in The Dunes, Cochin, India http://warse.org/IJATCSE/static/pdf/Issue/iceec2015sp06.pdf An Enhanced Advanced Encryption Standard Algorithm Kshyamasagar Mahanta1, Hima Bindu Maringanti2 1Department of Computer Science & Engineering, North Orissa University, India, [email protected] 2Department of Computer Science & Engineering, North Orissa University, India, [email protected] modifying the shift row phase involved . Similarly, in 2010, Abstract: In today’s world most of the communication is El-Sayed Abdoul-Moaty ElBadawy et. al. and in 2011, done using electronic media. Data Security plays a vital role Zhang Zhao et. al. have modified the standard AES in such communication. Hence, there is a need to protect data algorithm by modifying the S-box generation using 1-D from malicious attacks. Cryptography is the study of logistic chaos equation . In 2011, Alireza Jolfaei et. al. have mathematical techniques related to aspects of information identified such issues and modified the standard algorithm by security such as confidentiality, data integrity, entity modifying the S-box using the chaotic baker’s map equations authentication and data origin authentication. In data and . telecommunications, cryptography is necessary when Here, we have followed a different approach by encrypting communicating over any unreliable medium, which includes the key used in the AES algorithm. For the key encryption, any network particularly the internet. we have used the RNG algorithm, which gives a unique Advanced Encryption Standard (AES), also known as random key for each time of encryption. -
A Practical Implementation of a One-Time Pad Cryptosystem
Jeff Connelly CPE 456 June 11, 2008 A Practical Implementation of a One-time Pad Cryptosystem 0.1 Abstract How to securely transmit messages between two people has been a problem for centuries. The first ciphers of antiquity used laughably short keys and insecure algorithms easily broken with today’s computational power. This pattern has repeated throughout history, until the invention of the one-time pad in 1917, the world’s first provably unbreakable cryptosystem. However, the public generally does not use the one-time pad for encrypting their communication, despite the assurance of confidentiality, because of practical reasons. This paper presents an implementation of a practical one-time pad cryptosystem for use between two trusted individuals, that have met previously but wish to securely communicate over email after their departure. The system includes the generation of a one-time pad using a custom-built hardware TRNG as well as software to easily send and receive encrypted messages over email. This implementation combines guaranteed confidentiality with practicality. All of the work discussed here is available at http://imotp.sourceforge.net/. 1 Contents 0.1 Abstract.......................................... 1 1 Introduction 3 2 Implementation 3 2.1 RelatedWork....................................... 3 2.2 Description ........................................ 3 3 Generating Randomness 4 3.1 Inadequacy of Pseudo-random Number Generation . 4 3.2 TrulyRandomData .................................... 5 4 Software 6 4.1 Acquiring Audio . 6 4.1.1 Interference..................................... 6 4.2 MeasuringEntropy................................... 6 4.3 EntropyExtraction................................ ..... 7 4.3.1 De-skewing ..................................... 7 4.3.2 Mixing........................................ 7 5 Exchanging Pads 8 5.1 Merkle Channels . 8 5.2 Local Pad Security . -
Key Derivation Functions and Their GPU Implementation
MASARYK UNIVERSITY FACULTY}w¡¢£¤¥¦§¨ OF I !"#$%&'()+,-./012345<yA|NFORMATICS Key derivation functions and their GPU implementation BACHELOR’S THESIS Ondrej Mosnáˇcek Brno, Spring 2015 This work is licensed under a Creative Commons Attribution- NonCommercial-ShareAlike 4.0 International License. https://creativecommons.org/licenses/by-nc-sa/4.0/ cbna ii Declaration Hereby I declare, that this paper is my original authorial work, which I have worked out by my own. All sources, references and literature used or excerpted during elaboration of this work are properly cited and listed in complete reference to the due source. Ondrej Mosnáˇcek Advisor: Ing. Milan Brož iii Acknowledgement I would like to thank my supervisor for his guidance and support, and also for his extensive contributions to the Cryptsetup open- source project. Next, I would like to thank my family for their support and pa- tience and also to my friends who were falling behind schedule just like me and thus helped me not to panic. Last but not least, access to computing and storage facilities owned by parties and projects contributing to the National Grid In- frastructure MetaCentrum, provided under the programme “Projects of Large Infrastructure for Research, Development, and Innovations” (LM2010005), is also greatly appreciated. v Abstract Key derivation functions are a key element of many cryptographic applications. Password-based key derivation functions are designed specifically to derive cryptographic keys from low-entropy sources (such as passwords or passphrases) and to counter brute-force and dictionary attacks. However, the most widely adopted standard for password-based key derivation, PBKDF2, as implemented in most applications, is highly susceptible to attacks using Graphics Process- ing Units (GPUs). -
The Double Ratchet Algorithm
The Double Ratchet Algorithm Trevor Perrin (editor) Moxie Marlinspike Revision 1, 2016-11-20 Contents 1. Introduction 3 2. Overview 3 2.1. KDF chains . 3 2.2. Symmetric-key ratchet . 5 2.3. Diffie-Hellman ratchet . 6 2.4. Double Ratchet . 13 2.6. Out-of-order messages . 17 3. Double Ratchet 18 3.1. External functions . 18 3.2. State variables . 19 3.3. Initialization . 19 3.4. Encrypting messages . 20 3.5. Decrypting messages . 20 4. Double Ratchet with header encryption 22 4.1. Overview . 22 4.2. External functions . 26 4.3. State variables . 26 4.4. Initialization . 26 4.5. Encrypting messages . 27 4.6. Decrypting messages . 28 5. Implementation considerations 29 5.1. Integration with X3DH . 29 5.2. Recommended cryptographic algorithms . 30 6. Security considerations 31 6.1. Secure deletion . 31 6.2. Recovery from compromise . 31 6.3. Cryptanalysis and ratchet public keys . 31 1 6.4. Deletion of skipped message keys . 32 6.5. Deferring new ratchet key generation . 32 6.6. Truncating authentication tags . 32 6.7. Implementation fingerprinting . 32 7. IPR 33 8. Acknowledgements 33 9. References 33 2 1. Introduction The Double Ratchet algorithm is used by two parties to exchange encrypted messages based on a shared secret key. Typically the parties will use some key agreement protocol (such as X3DH [1]) to agree on the shared secret key. Following this, the parties will use the Double Ratchet to send and receive encrypted messages. The parties derive new keys for every Double Ratchet message so that earlier keys cannot be calculated from later ones. -
TMF: Asymmetric Cryptography Security Layer V1.0
GlobalPlatform Device Technology TMF: Asymmetric Cryptography Security Layer Version 1.0 Public Release March 2017 Document Reference: GPD_SPE_122 Copyright 2013-2017 GlobalPlatform, Inc. All Rights Reserved. Recipients of this document are invited to submit, with their comments, notification of any relevant patents or other intellectual property rights (collectively, “IPR”) of which they may be aware which might be necessarily infringed by the implementation of the specification or other work product set forth in this document, and to provide supporting documentation. The technology provided or described herein is subject to updates, revisions, and extensions by GlobalPlatform. Use of this information is governed by the GlobalPlatform license agreement and any use inconsistent with that agreement is strictly prohibited. TMF: Asymmetric Cryptography Security Layer – Public Release v1.0 THIS SPECIFICATION OR OTHER WORK PRODUCT IS BEING OFFERED WITHOUT ANY WARRANTY WHATSOEVER, AND IN PARTICULAR, ANY WARRANTY OF NON-INFRINGEMENT IS EXPRESSLY DISCLAIMED. ANY IMPLEMENTATION OF THIS SPECIFICATION OR OTHER WORK PRODUCT SHALL BE MADE ENTIRELY AT THE IMPLEMENTER’S OWN RISK, AND NEITHER THE COMPANY, NOR ANY OF ITS MEMBERS OR SUBMITTERS, SHALL HAVE ANY LIABILITY WHATSOEVER TO ANY IMPLEMENTER OR THIRD PARTY FOR ANY DAMAGES OF ANY NATURE WHATSOEVER DIRECTLY OR INDIRECTLY ARISING FROM THE IMPLEMENTATION OF THIS SPECIFICATION OR OTHER WORK PRODUCT. Copyright 2013-2017 GlobalPlatform, Inc. All Rights Reserved. The technology provided or described herein is subject to updates, revisions, and extensions by GlobalPlatform. Use of this information is governed by the GlobalPlatform license agreement and any use inconsistent with that agreement is strictly prohibited. TMF: Asymmetric Cryptography Security Layer – Public Release v1.0 3 / 38 Contents 1 Introduction ........................................................................................................................... -
Modes of Operation for Compressed Sensing Based Encryption
Modes of Operation for Compressed Sensing based Encryption DISSERTATION zur Erlangung des Grades eines Doktors der Naturwissenschaften Dr. rer. nat. vorgelegt von Robin Fay, M. Sc. eingereicht bei der Naturwissenschaftlich-Technischen Fakultät der Universität Siegen Siegen 2017 1. Gutachter: Prof. Dr. rer. nat. Christoph Ruland 2. Gutachter: Prof. Dr.-Ing. Robert Fischer Tag der mündlichen Prüfung: 14.06.2017 To Verena ... s7+OZThMeDz6/wjq29ACJxERLMATbFdP2jZ7I6tpyLJDYa/yjCz6OYmBOK548fer 76 zoelzF8dNf /0k8H1KgTuMdPQg4ukQNmadG8vSnHGOVpXNEPWX7sBOTpn3CJzei d3hbFD/cOgYP4N5wFs8auDaUaycgRicPAWGowa18aYbTkbjNfswk4zPvRIF++EGH UbdBMdOWWQp4Gf44ZbMiMTlzzm6xLa5gRQ65eSUgnOoZLyt3qEY+DIZW5+N s B C A j GBttjsJtaS6XheB7mIOphMZUTj5lJM0CDMNVJiL39bq/TQLocvV/4inFUNhfa8ZM 7kazoz5tqjxCZocBi153PSsFae0BksynaA9ZIvPZM9N4++oAkBiFeZxRRdGLUQ6H e5A6HFyxsMELs8WN65SCDpQNd2FwdkzuiTZ4RkDCiJ1Dl9vXICuZVx05StDmYrgx S6mWzcg1aAsEm2k+Skhayux4a+qtl9sDJ5JcDLECo8acz+RL7/ ovnzuExZ3trm+O 6GN9c7mJBgCfEDkeror5Af4VHUtZbD4vALyqWCr42u4yxVjSj5fWIC9k4aJy6XzQ cRKGnsNrV0ZcGokFRO+IAcuWBIp4o3m3Amst8MyayKU+b94VgnrJAo02Fp0873wa hyJlqVF9fYyRX+couaIvi5dW/e15YX/xPd9hdTYd7S5mCmpoLo7cqYHCVuKWyOGw ZLu1ziPXKIYNEegeAP8iyeaJLnPInI1+z4447IsovnbgZxM3ktWO6k07IOH7zTy9 w+0UzbXdD/qdJI1rENyriAO986J4bUib+9sY/2/kLlL7nPy5Kxg3 Et0Fi3I9/+c/ IYOwNYaCotW+hPtHlw46dcDO1Jz0rMQMf1XCdn0kDQ61nHe5MGTz2uNtR3bty+7U CLgNPkv17hFPu/lX3YtlKvw04p6AZJTyktsSPjubqrE9PG00L5np1V3B/x+CCe2p niojR2m01TK17/oT1p0enFvDV8C351BRnjC86Z2OlbadnB9DnQSP3XH4JdQfbtN8 BXhOglfobjt5T9SHVZpBbzhDzeXAF1dmoZQ8JhdZ03EEDHjzYsXD1KUA6Xey03wU uwnrpTPzD99cdQM7vwCBdJnIPYaD2fT9NwAHICXdlp0pVy5NH20biAADH6GQr4Vc -
CSE 291-I: Applied Cryptography
CSE 291-I: Applied Cryptography Nadia Heninger UCSD Fall 2020 Lecture 7 Legal Notice The Zoom session for this class will be recorded and made available asynchronously on Canvas to registered students. Announcements 1. HW 3 is due next Tuesday. 2. HW 4 is online, due before class in 1.5 weeks, November 3. Last time: Hash functions This time: Hash-based MACs, authenticated encryption Constructing a MAC from a hash function Recall: Collision-resistant hash function: Unkeyed function • H : 0, 1 0, 1 n hard to find inputs mapping to same { }⇤ !{ } output. MAC: Keyed function Mac (m)=t,hardforadversaryto • k construct valid (m, t) pair. functor alone not- MAC : anyone can (m Hcm)) Hash forge , No secrets . Insecure. Vulnerable to length extension attacks for Merkle-Damgård functions. Secure for SHA3 sponge. Ok, but vulnerable to offline collision-finding attacks against H. Ok, but nobody uses. Secure, similar to HMAC. Candidate MAC constructions Mac(k, m)=H(k m) • || Mac(k, m)=H(m k) • || Mac(k, m)=H(k m k) • || || Mac(k , k , m)=H(k H(k m)) • 1 2 2|| 1|| Ok, but vulnerable to offline collision-finding attacks against H. Ok, but nobody uses. Secure, similar to HMAC. Candidate MAC constructions Mac(k, m)=H(k m) • || Insecure. Vulnerable to length extension attacks for Merkle-Damgård functions. Secure for SHA3 sponge. Mac(k, m)=H(m k) • || Mac(k, m)=H(k m k) • || || Mac(k , k , m)=H(k H(k m)) • 1 2 2|| 1|| Ok, but nobody uses. Secure, similar to HMAC. -
Analysis of Entropy Usage in Random Number Generators
DEGREE PROJECT IN THE FIELD OF TECHNOLOGY ENGINEERING PHYSICS AND THE MAIN FIELD OF STUDY COMPUTER SCIENCE AND ENGINEERING, SECOND CYCLE, 30 CREDITS STOCKHOLM, SWEDEN 2017 Analysis of Entropy Usage in Random Number Generators KTH ROYAL INSTITUTE OF TECHNOLOGY SCHOOL OF COMPUTER SCIENCE AND COMMUNICATION Analysis of Entropy Usage in Random Number Generators JOEL GÄRTNER Master in Computer Science Date: September 16, 2017 Supervisor: Douglas Wikström Examiner: Johan Håstad Principal: Omegapoint Swedish title: Analys av entropianvändning i slumptalsgeneratorer School of Computer Science and Communication i Abstract Cryptographically secure random number generators usually require an outside seed to be initialized. Other solutions instead use a continuous entropy stream to ensure that the internal state of the generator always remains unpredictable. This thesis analyses four such generators with entropy inputs. Furthermore, different ways to estimate entropy is presented and a new method useful for the generator analy- sis is developed. The developed entropy estimator performs well in tests and is used to analyse en- tropy gathered from the different generators. Furthermore, all the analysed generators exhibit some seemingly unintentional behaviour, but most should still be safe for use. ii Sammanfattning Kryptografiskt säkra slumptalsgeneratorer behöver ofta initialiseras med ett oförutsägbart frö. En annan lösning är att istället konstant ge slumptalsgeneratorer entropi. Detta gör det möjligt att garantera att det interna tillståndet i generatorn hålls oförutsägbart. I den här rapporten analyseras fyra sådana generatorer som matas med entropi. Dess- utom presenteras olika sätt att skatta entropi och en ny skattningsmetod utvecklas för att användas till analysen av generatorerna. Den framtagna metoden för entropiskattning lyckas bra i tester och används för att analysera entropin i de olika generatorerna. -
Cryptgenrandom()
(Pseudo)Random Data PA193 – Secure coding Petr Švenda Zdeněk Říha Faculty of Informatics, Masaryk University, Brno, CZ Need for “random” data • Games • Simulations, … • Crypto – Symmetric keys – Asymmetric keys – Padding/salt – Initialization vectors – Challenges (for challenge – response protocols) – … “Random” data • Sometimes (games, simulations) we only need data with some statistical properties – Evenly distributed numbers (from an interval) – Long and complete cycle • Large number of different values • All values can be generated • In crypto we also need unpredictability – Even if you have seen all the “random” data generated until now you have no idea what will be the random data generated next “Random” data generators • Insecure random number generators – noncryptographic pseudo-random number generators – Often leak information about their internal state with each output • Cryptographic pseudo-random number generators (PRNGs) – Based on seed deterministically generate pseudorandom data • “True” random data generators – Entropy harvesters – gather entropy from other sources and present it directly What (pseudo)random data to use? • Avoid using noncryptographic random number generators • For many purposes the right way is to get the seed from the true random number generator and then use it in the pseudorandom number generator (PRNG) – PRNG are deterministic, with the same seed they produce the same pseudorandom sequence • There are situations, where PRNG are not enough – E.g. one time pad Noncryptographic generators • Standard rand()/srand(), random ()/srandom() functions – libc • “Mersenne Twister” • linear feedback shift registers • Anything else not labeled as cryptographic PRNG… • Not to be used for most purposes…. Noncryptographic generators Source: Writing secure code, 2nd edition Source: http://xkcd.com/ PRNG • Cryptographic pseudo-random number generators are still predictable if you somehow know their internal state. -
Additional Source of Entropy As a Service in the Android User-Space
Faculty of Science Additional source of entropy as a service in the Android user-space Master Thesis B.C.M. (Bas) Visser Supervisors: dr. P. (Peter) Schwabe dr. V. (Veelasha) Moonsamy Nijmegen, July 2015 Abstract Secure encrypted communication on a smartphone or tablet requires a strong random seed as input for the encryption scheme. Android devices are based on the Linux kernel and are therefore provided with the /dev/random and /dev/urandom pseudo-random-number generators. /dev/random generates randomness from environmental sources but a number of papers have shown vulnerabilities in the entropy pool when there is a lack of user input. This thesis will research the possibility to provide additional entropy on the Android platform by extracting entropy from sensor data without the need for user input. The entropy level of this generated data is evaluated and this shows that it is feasible to extract randomness from the sensor data within reasonable time and using limited resources from the Android device. Finally, a prototype Android app is presented which uses generated sensor data as input for a stream cipher to create a pseudo-random-number generator in the Android user-space. This app can then be used as an additional source of randomness to strengthen random seeds for any process in the Android user-space on request. Additional source of entropy as a service in the Android user-space 1 Acknowledgements First I would like to thank my supervisor, Peter Schwabe. I started with a number of research projects that did not align with my interests and expertise. -
Crypto 101 Lvh
Crypto 101 lvh 1 2 Copyright 2013-2016, Laurens Van Houtven This book is made possible by your donations. If you enjoyed it, please consider making a donation, so it can be made even better and reach even more people. This work is available under the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) license. You can find the full text of the license at https://creativecommons.org/licenses/by-nc/4.0/. The following is a human-readable summary of (and not a substitute for) the license. You can: • Share: copy and redistribute the material in any medium or format • Adapt: remix, transform, and build upon the material The licensor cannot revoke these freedoms as long as you follow the license terms: • Attribution: you must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use. • NonCommercial: you may not use the material for commercial purposes. • No additional restrictions: you may not apply legal terms or technological measures that legally restrict others from doing anything the license permits. 3 You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation. No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material. -
Cryptographic Extraction and Key Derivation: the HKDF Scheme
Cryptographic Extraction and Key Derivation: The HKDF Scheme Hugo Krawczyk∗ Abstract In spite of the central role of key derivation functions (KDF) in applied cryptography, there has been little formal work addressing the design and analysis of general multi-purpose KDFs. In practice, most KDFs (including those widely standardized) follow ad-hoc approaches that treat cryptographic hash functions as perfectly random functions. In this paper we close some gaps between theory and practice by contributing to the study and engineering of KDFs in several ways. We provide detailed rationale for the design of KDFs based on the extract-then-expand approach; we present the first general and rigorous definition of KDFs and their security which we base on the notion of computational extractors; we specify a concrete fully practical KDF based on the HMAC construction; and we provide an analysis of this construction based on the extraction and pseudorandom properties of HMAC. The resultant KDF design can support a large variety of KDF applications under suitable assumptions on the underlying hash function; particular attention and effort is devoted to minimizing these assumptions as much as possible for each usage scenario. Beyond the theoretical interest in modeling KDFs, this work is intended to address two important and timely needs of cryptographic applications: (i) providing a single hash-based KDF design that can be standardized for use in multiple and diverse applications, and (ii) providing a conservative, yet efficient, design that exercises much care in the way it utilizes a cryptographic hash function. (The HMAC-based scheme presented here, named HKDF, is being standardized by the IETF.) ∗IBM T.J.