Brief Contents
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Cryptographic Hash Functions and Message Authentication Code
Cryptographic Hash Functions and Message Authentication Code Thierry Sans Cryptographic hashing H m1 m2 x1 m3 x2 H(m) = x is a hash function if • H is one-way function • m is a message of any length • x is a message digest of a fixed length ➡ H is a lossy compression function necessarily there exists x, m1 and m2 | H(m1) = H(m2) = x Computational complexity m H x • Given H and m, computing x is easy (polynomial or linear) • Given H and x, computing m is hard (exponential) ➡ H is not invertible Preimage resistance and collision resistance m H x PR - Preimage Resistance (a.k.a One Way) ➡ given H and x, hard to find m e.g. password storage 2PR - Second Preimage Resistance (a.k.a Weak Collision Resistance) ➡ given H, m and x, hard to find m’ such that H(m) = H(m’) = x e.g. virus identification CR - Collision Resistance (a.k.a Strong Collision Resistance) ➡ given H, hard to find m and m’ such that H(m) = H(m’) = x e.g. digital signatures CR → 2PR and CR → PR Hash functions in practice IV n’ bits n bits n’ bits Common hash functions m H x Name SHA-2 SHA-3 MD5 SHA-1 Variant SHA-224 SHA-256 SHA-384 SHA-512 SHA3-224 SHA3-256 SHA3-384 SHA3-512 Year 1992 1993 2001 2012 Guido Bertoni, Joan Daemen, Michaël Designer Rivest NSA NSA Peeters, and Gilles Van Assche Input 512 512 512 512 1024 1024 1152 1088 832 576 n bits Output 128 160 224 256 384 512 224 256 384 512 n’ bits Speed 6.8 11.4 15.8 17.7 12.5 cycle/byte Considered Broken yes yes no no How to hash long messages ? Merkle–Damgård construction m split m in blocks of n bits and add padding p n bits m1 -
Grostl-Comment-April28.Pdf
Some notes on Grøstl John Kelsey, NIST, April 2009 These are some quick notes on some properties and observations of Grøstl. Nothing in this note threatens the hash function; instead, I'm pointing out some properties that are a bit surprising, and some broad approaches someone might take to get attacks to work. I've discussed these with the Grøstl team, and gotten quite a bit of useful feedback. I'm pretty sure they agree that my observations are correct, but obviously, any errors here are mine alone. 1 Grøstl Compression Function The Grøstl compression function is built from two different fixed permutations, P and Q, on 2n bits, where n is the final hash output size. The design is quite interesting; among other things, this (like LANE and Luffa, among others) takes away the key schedule as a way of affecting things inside P and Q. Here is a picture of the Grøstl compression function: M Q v u w Y + P + Z In this diagram, I've labeled the input hash chaining value Y, the output Z, and the message M. Similarly, I have introduced variables for the internal values inside the compression function--u, v, and w. I'll use this notation a lot in the next few pages to simplify discussion. To write this in terms of equations: u = Y xor M v = Q(M) w = P(u) Z = v xor w xor Y or, in a shorter form: Z = Q(M) xor P(Y xor M) xor Y It's important to remember here that all variables are 2n bits, so for a 256-bit hash, they're 512 bits each. -
Cryptography Whitepaper
Cryptography Whitepaper Threema uses modern cryptography based on open source components that strike an optimal balance between security, performance and message size. In this whitepaper, the algorithms and design decisions behind the cryptography in Threema are explained. VERSION: JUNE 21, 2021 Contents Overview 4 Open Source 5 End-to-End Encryption 5 Key Generation and Registration 5 Key Distribution and Trust 6 Message Encryption 7 Group Messaging 8 Key Backup 8 Client-Server Protocol Description 10 Chat Protocol (Message Transport Layer) 10 Directory Access Protocol 11 Media Access Protocol 11 Cryptography Details 12 Key Lengths 12 Random Number Generation 13 Forward Secrecy 14 Padding 14 Repudiability 15 Replay Prevention 15 Local Data Encryption 15 iOS 15 Android 16 Key Storage 16 iOS 16 Android 16 Push Notifications 17 iOS 17 Android 17 Threema • Cryptography Whitepaper Address Book Synchronization 17 Linking 18 ID Revocation 19 An Example 19 Profile Pictures 19 Web Client 20 Architecture 20 Connection Buildup 21 WebRTC Signaling 22 WebRTC Connection Buildup 22 Trusted Keys / Stored Sessions 23 Push Service 23 Self Hosting 24 Links 24 Threema Calls 24 Signaling 24 Call Encryption 24 Audio Encoding 25 Video Encoding 25 Privacy / IP Exposure 25 Threema Safe 26 Overview 26 Backup Format 27 Encryption 27 Upload/Storage 27 Backup Intervals 28 Restore/Decryption 28 Running a Custom Threema Safe Server 28 Threema • Cryptography Whitepaper Overview Threema uses two different encryption layers to protect messages between the sender and the recipient. • End-to-end encryption layer: this layer is between the sender and the recipient. • Transport layer: each end-to-end encrypted message is encrypted again for transport between the client and the server, in order to protect the header information. -
Methods and Tools for Analysis of Symmetric Cryptographic Primitives
METHODSANDTOOLS FOR ANALYSIS OF SYMMETRICCRYPTOGRAPHIC PRIMITIVES Oleksandr Kazymyrov dissertation for the degree of philosophiae doctor the selmer center department of informatics university of bergen norway DECEMBER 1, 2014 A CKNOWLEDGMENTS It is impossible to thank all those who have, directly or indirectly, helped me with this thesis, giving of their time and experience. I wish to use this opportunity to thank some of them. Foremost, I would like to express my very great appreciation to my main supervisor Tor Helleseth, who has shared his extensive knowledge and expe- rience, and made warm conditions for the comfortable research in one of the rainiest cities in the world. I owe a great deal to Lilya Budaghyan, who was always ready to offer assistance and suggestions during my research. Advice given by Alexander Kholosha has been a great help in the early stages of my work on the thesis. My grateful thanks are also extended to all my friends and colleagues at the Selmer Center for creating such a pleasant environment to work in. I am particularly grateful to Kjell Jørgen Hole, Matthew G. Parker and Håvard Raddum for the shared teaching experience they provided. Moreover, I am very grateful for the comments and propositions given by everyone who proofread my thesis. In addition, I would like to thank the administrative staff at the Department of Informatics for their immediate and exhaustive solutions of practical issues. I wish to acknowledge the staff at the Department of Information Tech- nologies Security, Kharkiv National University of Radioelectronics, Ukraine, especially Roman Oliynykov, Ivan Gorbenko, Viktor Dolgov and Oleksandr Kuznetsov for their patient guidance, enthusiastic encouragement and useful critiques. -
ERHARD-RNG: a Random Number Generator Built from Repurposed Hardware in Embedded Systems
ERHARD-RNG: A Random Number Generator Built from Repurposed Hardware in Embedded Systems Jacob Grycel and Robert J. Walls Department of Computer Science Worcester Polytechnic Institute Worcester, MA Email: jtgrycel, [email protected] Abstract—Quality randomness is fundamental to crypto- only an external 4 MHz crystal oscillator and power supply. graphic operations but on embedded systems good sources are We chose this platform due to its numerous programmable pe- (seemingly) hard to find. Rather than use expensive custom hard- ripherals, its commonality in embedded systems development, ware, our ERHARD-RNG Pseudo-Random Number Generator (PRNG) utilizes entropy sources that are already common in a and its affordability. Many microcontrollers and Systems On a range of low-cost embedded platforms. We empirically evaluate Chip (SoC) include similar hardware that allows our PRNG to the entropy provided by three sources—SRAM startup state, be implemented, including chips from Atmel, Xilinx, Cypress oscillator jitter, and device temperature—and integrate those Semiconductor, and other chips from Texas Instruments. sources into a full Pseudo-Random Number Generator imple- ERHARD-RNG is based on three key insights. First, we mentation based on Fortuna [1]. Our system addresses a number of fundamental challenges affecting random number generation can address the challenge of collecting entropy at runtime by on embedded systems. For instance, we propose SRAM startup sampling the jitter of the low-power/low-precision oscillator. state as a means to efficiently generate the initial seed—even for Coupled with measurements of the internal temperature sensor systems that do not have writeable storage. Further, the system’s we can effectively re-seed our PRNG with minimal overhead. -
How to Eat Your Entropy and Have It Too — Optimal Recovery Strategies for Compromised Rngs
How to Eat Your Entropy and Have it Too — Optimal Recovery Strategies for Compromised RNGs Yevgeniy Dodis1?, Adi Shamir2, Noah Stephens-Davidowitz1, and Daniel Wichs3?? 1 Dept. of Computer Science, New York University. { [email protected], [email protected] } 2 Dept. of Computer Science and Applied Mathematics, Weizmann Institute. [email protected] 3 Dept. of Computer Science, Northeastern University. [email protected] Abstract. We study random number generators (RNGs) with input, RNGs that regularly update their internal state according to some aux- iliary input with additional randomness harvested from the environment. We formalize the problem of designing an efficient recovery mechanism from complete state compromise in the presence of an active attacker. If we knew the timing of the last compromise and the amount of entropy gathered since then, we could stop producing any outputs until the state becomes truly random again. However, our challenge is to recover within a time proportional to this optimal solution even in the hardest (and most realistic) case in which (a) we know nothing about the timing of the last state compromise, and the amount of new entropy injected since then into the state, and (b) any premature production of outputs leads to the total loss of all the added entropy used by the RNG. In other words, the challenge is to develop recovery mechanisms which are guaranteed to save the day as quickly as possible after a compromise we are not even aware of. The dilemma is that any entropy used prematurely will be lost, and any entropy which is kept unused will delay the recovery. -
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 -
Broad View of Cryptographic Hash Functions
IJCSI International Journal of Computer Science Issues, Vol. 10, Issue 4, No 1, July 2013 ISSN (Print): 1694-0814 | ISSN (Online): 1694-0784 www.IJCSI.org 239 Broad View of Cryptographic Hash Functions 1 2 Mohammad A. AlAhmad , Imad Fakhri Alshaikhli 1 Department of Computer Science, International Islamic University of Malaysia, 53100 Jalan Gombak Kuala Lumpur, Malaysia, 2 Department of Computer Science, International Islamic University of Malaysia, 53100 Jalan Gombak Kuala Lumpur, Malaysia Abstract Cryptographic hash function is a function that takes an arbitrary length as an input and produces a fixed size of an output. The viability of using cryptographic hash function is to verify data integrity and sender identity or source of information. This paper provides a detailed overview of cryptographic hash functions. It includes the properties, classification, constructions, attacks, applications and an overview of a selected dedicated cryptographic hash functions. Keywords-cryptographic hash function, construction, attack, classification, SHA-1, SHA-2, SHA-3. Figure 1. Classification of cryptographic hash function 1. INTRODUCTION CRHF usually deals with longer length hash values. An A cryptographic hash function H is an algorithm that takes an unkeyed hash function is a function for a fixed positive integer n * arbitrary length of message as an input {0, 1} and produce a which has, as a minimum, the following two properties: n fixed length of an output called message digest {0, 1} 1) Compression: h maps an input x of arbitrary finite bit (sometimes called an imprint, digital fingerprint, hash code, hash length, to an output h(x) of fixed bit length n. -
HCAHF: a New Family of CA-Based Hash Functions
(IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 10, No. 12, 2019 HCAHF: A New Family of CA-based Hash Functions Anas Sadak1, Fatima Ezzahra Ziani2, Bouchra Echandouri3, Charifa Hanin4, Fouzia Omary5 Faculty of Science, Mohammed V University Rabat, Morocco Abstract—Cryptographic hash functions (CHF) represent a The article is organized as follows: in Section 2, a core cryptographic primitive. They have application in digital background on cellular automata and hash functions is signature and message authentication protocols. Their main included. In Section 3, some related works are presented. building block are Boolean functions. Those functions provide Section 4 details the hashing scheme proposed. In Section 5, pseudo-randomness and sensitivity to the input. They also help the result of the different statistical tests and the cryptographic prevent and lower the risk of attacks targeted at CHF. Cellular properties of cellular automata are provided. Next, in Section 6 automata (CA) are a class of Boolean functions that exhibit good a security analysis is performed. Finally, Section 7 summarizes cryptographic properties and display a chaotic behavior. In this the article. article, a new hash function based on CA is proposed. A description of the algorithm and the security measures to II. BACKGROUND increase the robustness of the construction are presented. A security analysis against generic and dedicated attacks is A. Cryptographic Hash Functions (CHF) included. It shows that the hashing algorithm has good security Cryptographic hash functions with good security properties features and meet the security requirements of a good hashing represent a significant part of cryptography. They are the basis scheme. -
Cryptography for Developers.Pdf
404_CRYPTO_FM.qxd 10/30/06 2:33 PM Page i Visit us at www.syngress.com Syngress is committed to publishing high-quality books for IT Professionals and delivering those books in media and formats that fit the demands of our cus- tomers. We are also committed to extending the utility of the book you purchase via additional materials available from our Web site. SOLUTIONS WEB SITE To register your book, visit www.syngress.com/solutions. Once registered, you can access our [email protected] Web pages. There you may find an assortment of value-added features such as free e-books related to the topic of this book, URLs of related Web site, FAQs from the book, corrections, and any updates from the author(s). ULTIMATE CDs Our Ultimate CD product line offers our readers budget-conscious compilations of some of our best-selling backlist titles in Adobe PDF form. These CDs are the perfect way to extend your reference library on key topics pertaining to your area of exper- tise, including Cisco Engineering, Microsoft Windows System Administration, CyberCrime Investigation, Open Source Security, and Firewall Configuration, to name a few. DOWNLOADABLE E-BOOKS For readers who can’t wait for hard copy, we offer most of our titles in download- able Adobe PDF form. These e-books are often available weeks before hard copies, and are priced affordably. SYNGRESS OUTLET Our outlet store at syngress.com features overstocked, out-of-print, or slightly hurt books at significant savings. SITE LICENSING Syngress has a well-established program for site licensing our e-books onto servers in corporations, educational institutions, and large organizations. -
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. -
ΥΣ13 - Computer Security
ΥΣ13 - Computer Security Hashing Κώστας Χατζηκοκολάκης 1 • Solution : hash function - h(x): f0; 1g∗ ! f0; 1gn - h(x) is the hash/digest of x Context • Goal - Represent large/sensitive message by a smaller one - Numerous applications 2 Context • Goal - Represent large/sensitive message by a smaller one - Numerous applications • Solution : hash function - h(x): f0; 1g∗ ! f0; 1gn - h(x) is the hash/digest of x 2 - h(x) ! x : hard · Even to find a single bit of x ! • No collisions - Do x =6 x0 exist such that h(x) = h(x0)? YES - But the should be hard to find! Properties • One-way - x ! h(x) : easy 3 YES - But the should be hard to find! Properties • One-way - x ! h(x) : easy - h(x) ! x : hard · Even to find a single bit of x ! • No collisions - Do x =6 x0 exist such that h(x) = h(x0)? 3 Properties • One-way - x ! h(x) : easy - h(x) ! x : hard · Even to find a single bit of x ! • No collisions - Do x =6 x0 exist such that h(x) = h(x0)? YES - But the should be hard to find! 3 • Just 23! − • − 364 · 363 · · 365 22 ≈ pb = 1 365 365 ::: 365 0:507 • Approximation - e−x ≈ 1 − x (x ≈ 0) − m2 - pb ≈ 1 − e 2·365 Collision-resistance Birthday paradox • How many people do we need so that any 2 have the same birthday with pb 50%? 4 • Approximation - e−x ≈ 1 − x (x ≈ 0) − m2 - pb ≈ 1 − e 2·365 Collision-resistance Birthday paradox • How many people do we need so that any 2 have the same birthday with pb 50%? • Just 23! − • − 364 · 363 · · 365 22 ≈ pb = 1 365 365 ::: 365 0:507 4 Collision-resistance Birthday paradox • How many people do we need so that