Analysis of Entropy Usage in Random Number Generators
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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. -
Oracle Solaris 11.4 Security Target, V1.3
Oracle Solaris 11.4 Security Target Version 1.3 February 2021 Document prepared by www.lightshipsec.com Oracle Security Target Document History Version Date Author Description 1.0 09 Nov 2020 G Nickel Update TOE version 1.1 19 Nov 2020 G Nickel Update IDR version 1.2 25 Jan 2021 L Turner Update TLS and SSH. 1.3 8 Feb 2021 L Turner Finalize for certification. Page 2 of 40 Oracle Security Target Table of Contents 1 Introduction ........................................................................................................................... 5 1.1 Overview ........................................................................................................................ 5 1.2 Identification ................................................................................................................... 5 1.3 Conformance Claims ...................................................................................................... 5 1.4 Terminology ................................................................................................................... 6 2 TOE Description .................................................................................................................... 9 2.1 Type ............................................................................................................................... 9 2.2 Usage ............................................................................................................................. 9 2.3 Logical Scope ................................................................................................................ -
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 . -
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. -
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. -
Cryptanalysis of the Random Number Generator of the Windows Operating System
Cryptanalysis of the Random Number Generator of the Windows Operating System Leo Dorrendorf School of Engineering and Computer Science The Hebrew University of Jerusalem 91904 Jerusalem, Israel [email protected] Zvi Gutterman Benny Pinkas¤ School of Engineering and Computer Science Department of Computer Science The Hebrew University of Jerusalem University of Haifa 91904 Jerusalem, Israel 31905 Haifa, Israel [email protected] [email protected] November 4, 2007 Abstract The pseudo-random number generator (PRNG) used by the Windows operating system is the most commonly used PRNG. The pseudo-randomness of the output of this generator is crucial for the security of almost any application running in Windows. Nevertheless, its exact algorithm was never published. We examined the binary code of a distribution of Windows 2000, which is still the second most popular operating system after Windows XP. (This investigation was done without any help from Microsoft.) We reconstructed, for the ¯rst time, the algorithm used by the pseudo- random number generator (namely, the function CryptGenRandom). We analyzed the security of the algorithm and found a non-trivial attack: given the internal state of the generator, the previous state can be computed in O(223) work (this is an attack on the forward-security of the generator, an O(1) attack on backward security is trivial). The attack on forward-security demonstrates that the design of the generator is flawed, since it is well known how to prevent such attacks. We also analyzed the way in which the generator is run by the operating system, and found that it ampli¯es the e®ect of the attacks: The generator is run in user mode rather than in kernel mode, and therefore it is easy to access its state even without administrator privileges. -
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. -
Vulnerabilities of the Linux Random Number Generator
Black Hat 2006 Open to Attack Vulnerabilities of the Linux Random Number Generator Zvi Gutterman Chief Technology Officer with Benny Pinkas Tzachy Reinman Zvi Gutterman CTO, Safend Previously a chief architect in the IP infrastructure group for ECTEL (NASDAQ:ECTX) and an officer in the Israeli Defense Forces (IDF) Elite Intelligence unit. Master's and Bachelor's degrees in Computer Science from the Israeli Institute of Technology. Ph.D. candidate at the Hebrew University of Jerusalem, focusing on security, network protocols, and software engineering. - Proprietary & Confidential - Safend Safend is a leading provider of innovative endpoint security solutions that protect against corporate data leakage and penetration via physical and wireless ports. Safend Auditor and Safend Protector deliver complete visibility and granular control over all enterprise endpoints. Safend's robust, ultra- secure solutions are intuitive to manage, almost impossible to circumvent, and guarantee connectivity and productivity, without sacrificing security. For more information, visit www.safend.com. - Proprietary & Confidential - Pseudo-Random-Number-Generator (PRNG) Elementary and critical component in many cryptographic protocols Usually: “… Alice picks key K at random …” In practice looks like random.nextBytes(bytes); session_id = digest.digest(bytes); • Which is equal to session_id = md5(get next 16 random bytes) - Proprietary & Confidential - If the PRNG is predictable the cryptosystem is not secure Demonstrated in - Netscape SSL [GoldbergWagner 96] http://www.cs.berkeley.edu/~daw/papers/ddj-netscape.html Apache session-id’s [GuttermanMalkhi 05] http://www.gutterman.net/publications/2005/02/hold_your_sessions_an_attack_o.html - Proprietary & Confidential - General PRNG Scheme 0 0 01 Stateseed 110 100010 Properties: 1. Pseudo-randomness Output bits are indistinguishable from uniform random stream 2. -
Trusted Platform Module ST33TPHF20SPI FIPS 140-2 Security Policy Level 2
STMICROELECTRONICS Trusted Platform Module ST33TPHF20SPI ST33HTPH2E28AAF0 / ST33HTPH2E32AAF0 / ST33HTPH2E28AAF1 / ST33HTPH2E32AAF1 ST33HTPH2028AAF3 / ST33HTPH2032AAF3 FIPS 140-2 Security Policy Level 2 Firmware revision: 49.00 / 4A.00 HW version: ST33HTPH revision A Date: 2017/07/19 Document Version: 01-11 NON-PROPRIETARY DOCUMENT FIPS 140-2 SECURITY POLICY NON-PROPRIETARY DOCUMENT Page 1 of 43 Table of Contents 1 MODULE DESCRIPTION .................................................................................................................... 3 1.1 DEFINITION ..................................................................................................................................... 3 1.2 MODULE IDENTIFICATION ................................................................................................................. 3 1.2.1 AAF0 / AAF1 ......................................................................................................................... 3 1.2.2 AAF3 ..................................................................................................................................... 4 1.3 PINOUT DESCRIPTION ...................................................................................................................... 6 1.4 BLOCK DIAGRAMS ........................................................................................................................... 8 1.4.1 HW block diagram ............................................................................................................... -
Dev/Random and FIPS
/dev/random and Your FIPS 140-2 Validation Can Be Friends Yes, Really Valerie Fenwick Manager, Solaris Cryptographic Technologies team Oracle May 19, 2016 Photo by CGP Grey, http://www.cgpgrey.com/ Creative Commons Copyright © 2016, Oracle and/or its affiliates. All rights reserved. Not All /dev/random Implementations Are Alike • Your mileage may vary – Even across OS versions – Solaris 7‘s /dev/random is nothing like Solaris 11’s – Which look nothing like /dev/random in Linux, OpenBSD, MacOS, etc – Windows gets you a whole ‘nother ball of wax… • No common ancestry – Other than concept Copyright © 2016, Oracle and/or its affiliates. All rights reserved 3 /dev/random vs /dev/urandom • On most OSes, /dev/urandom is a PRNG (Pseudo-Random Number Generator) – In some, so is their /dev/random • Traditionally, /dev/urandom will never block – /dev/random will block • For fun, on some OSes /dev/urandom is a link to /dev/random Copyright © 2016, Oracle and/or its affiliates. All rights reserved 4 FreeBSD: /dev/random • /dev/urandom is a link to /dev/random • Only blocks until seeded • Based on Fortuna Copyright © 2016, Oracle and/or its affiliates. All rights reserved 5 OpenBSD: /dev/random • Called /dev/arandom • Does not block • Formerly based on ARCFOUR – Now based on ChaCha20 – C API still named arc4random() Copyright © 2016, Oracle and/or its affiliates. All rights reserved 6 MacOS: /dev/random • /dev/urandom is a link to /dev/random • 160-bit Yarrow PRNG, uses SHA1 and 3DES Copyright © 2016, Oracle and/or its affiliates. All rights reserved 7 Linux: /dev/random • Blocks when entropy is depleted • Has a separate non-blocking /dev/urandom Copyright © 2016, Oracle and/or its affiliates. -
Linux Random Number Generator
Not-So-Random Numbers in Virtualized Linux and the Whirlwind RNG Adam Everspaugh, Yan Zhai, Robert Jellinek, Thomas Ristenpart, Michael Swift Department of Computer Sciences University of Wisconsin-Madison {ace, yanzhai, jellinek, rist, swift}@cs.wisc.edu Abstract—Virtualized environments are widely thought to user-level cryptographic processes such as Apache TLS can cause problems for software-based random number generators suffer a catastrophic loss of security when run in a VM that (RNGs), due to use of virtual machine (VM) snapshots as is resumed multiple times from the same snapshot. Left as an well as fewer and believed-to-be lower quality entropy sources. Despite this, we are unaware of any published analysis of the open question in that work is whether reset vulnerabilities security of critical RNGs when running in VMs. We fill this also affect system RNGs. Finally, common folklore states gap, using measurements of Linux’s RNG systems (without the that software entropy sources are inherently worse on virtu- aid of hardware RNGs, the most common use case today) on alized platforms due to frequent lack of keyboard and mouse, Xen, VMware, and Amazon EC2. Despite CPU cycle counters interrupt coalescing by VM managers, and more. Despite providing a significant source of entropy, various deficiencies in the design of the Linux RNG makes its first output vulnerable all this, to date there have been no published measurement during VM boots and, more critically, makes it suffer from studies evaluating the security of Linux (or another common catastrophic reset vulnerabilities. We show cases in which the system RNG) in modern virtualized environments.