New Key Exchange Protocol Based on Mandelbrot and Julia Fractal Sets Mohammad Ahmad Alia and Azman Bin Samsudin
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Fractal (Mandelbrot and Julia) Zero-Knowledge Proof of Identity
Journal of Computer Science 4 (5): 408-414, 2008 ISSN 1549-3636 © 2008 Science Publications Fractal (Mandelbrot and Julia) Zero-Knowledge Proof of Identity Mohammad Ahmad Alia and Azman Bin Samsudin School of Computer Sciences, University Sains Malaysia, 11800 Penang, Malaysia Abstract: We proposed a new zero-knowledge proof of identity protocol based on Mandelbrot and Julia Fractal sets. The Fractal based zero-knowledge protocol was possible because of the intrinsic connection between the Mandelbrot and Julia Fractal sets. In the proposed protocol, the private key was used as an input parameter for Mandelbrot Fractal function to generate the corresponding public key. Julia Fractal function was then used to calculate the verified value based on the existing private key and the received public key. The proposed protocol was designed to be resistant against attacks. Fractal based zero-knowledge protocol was an attractive alternative to the traditional number theory zero-knowledge protocol. Key words: Zero-knowledge, cryptography, fractal, mandelbrot fractal set and julia fractal set INTRODUCTION Zero-knowledge proof of identity system is a cryptographic protocol between two parties. Whereby, the first party wants to prove that he/she has the identity (secret word) to the second party, without revealing anything about his/her secret to the second party. Following are the three main properties of zero- knowledge proof of identity[1]: Completeness: The honest prover convinces the honest verifier that the secret statement is true. Soundness: Cheating prover can’t convince the honest verifier that a statement is true (if the statement is really false). Fig. 1: Zero-knowledge cave Zero-knowledge: Cheating verifier can’t get anything Zero-knowledge cave: Zero-Knowledge Cave is a other than prover’s public data sent from the honest well-known scenario used to describe the idea of zero- prover. -
Authentication in Key-Exchange: Definitions, Relations and Composition
Authentication in Key-Exchange: Definitions, Relations and Composition Cyprien Delpech de Saint Guilhem1;2, Marc Fischlin3, and Bogdan Warinschi2 1 imec-COSIC, KU Leuven, Belgium 2 Dept Computer Science, University of Bristol, United Kingdom 3 Computer Science, Technische Universit¨atDarmstadt, Germany [email protected], [email protected], [email protected] Abstract. We present a systematic approach to define and study authentication notions in authenti- cated key-exchange protocols. We propose and use a flexible and expressive predicate-based definitional framework. Our definitions capture key and entity authentication, in both implicit and explicit vari- ants, as well as key and entity confirmation, for authenticated key-exchange protocols. In particular, we capture critical notions in the authentication space such as key-compromise impersonation resis- tance and security against unknown key-share attacks. We first discuss these definitions within the Bellare{Rogaway model and then extend them to Canetti{Krawczyk-style models. We then show two useful applications of our framework. First, we look at the authentication guarantees of three representative protocols to draw several useful lessons for protocol design. The core technical contribution of this paper is then to formally establish that composition of secure implicitly authenti- cated key-exchange with subsequent confirmation protocols yields explicit authentication guarantees. Without a formal separation of implicit and explicit authentication from secrecy, a proof of this folklore result could not have been established. 1 Introduction The commonly expected level of security for authenticated key-exchange (AKE) protocols comprises two aspects. Authentication provides guarantees on the identities of the parties involved in the protocol execution. -
2.3 Diffie–Hellman Key Exchange
2.3. Di±e{Hellman key exchange 65 q q q q q q 6 q qq q q q q q q 900 q q q q q q q qq q q q q q q q q q q q q q q q q 800 q q q qq q q q q q q q q q qq q q q q q q q q q q q 700 q q q q q q q q q q q q q q q q q q q q q q q q q q qq q 600 q q q q q q q q q q q q qq q q q q q q q q q q q q q q q q q qq q q q q q q q q 500 q qq q q q q q qq q q q q q qqq q q q q q q q q q q q q q qq q q q 400 q q q q q q q q q q q q q q q q q q q q q q q q q 300 q q q q q q q q q q q q q q q q q q qqqq qqq q q q q q q q q q q q 200 q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q qq q q qq q q 100 q q q q q q q q q q q q q q q q q q q q q q q q q 0 q - 0 30 60 90 120 150 180 210 240 270 Figure 2.2: Powers 627i mod 941 for i = 1; 2; 3;::: any group and use the group law instead of multiplication. -
Rendering Hypercomplex Fractals Anthony Atella [email protected]
Rhode Island College Digital Commons @ RIC Honors Projects Overview Honors Projects 2018 Rendering Hypercomplex Fractals Anthony Atella [email protected] Follow this and additional works at: https://digitalcommons.ric.edu/honors_projects Part of the Computer Sciences Commons, and the Other Mathematics Commons Recommended Citation Atella, Anthony, "Rendering Hypercomplex Fractals" (2018). Honors Projects Overview. 136. https://digitalcommons.ric.edu/honors_projects/136 This Honors is brought to you for free and open access by the Honors Projects at Digital Commons @ RIC. It has been accepted for inclusion in Honors Projects Overview by an authorized administrator of Digital Commons @ RIC. For more information, please contact [email protected]. Rendering Hypercomplex Fractals by Anthony Atella An Honors Project Submitted in Partial Fulfillment of the Requirements for Honors in The Department of Mathematics and Computer Science The School of Arts and Sciences Rhode Island College 2018 Abstract Fractal mathematics and geometry are useful for applications in science, engineering, and art, but acquiring the tools to explore and graph fractals can be frustrating. Tools available online have limited fractals, rendering methods, and shaders. They often fail to abstract these concepts in a reusable way. This means that multiple programs and interfaces must be learned and used to fully explore the topic. Chaos is an abstract fractal geometry rendering program created to solve this problem. This application builds off previous work done by myself and others [1] to create an extensible, abstract solution to rendering fractals. This paper covers what fractals are, how they are rendered and colored, implementation, issues that were encountered, and finally planned future improvements. -
Golden Ratio: a Subtle Regulator in Our Body and Cardiovascular System?
See discussions, stats, and author profiles for this publication at: https://www.researchgate.net/publication/306051060 Golden Ratio: A subtle regulator in our body and cardiovascular system? Article in International journal of cardiology · August 2016 DOI: 10.1016/j.ijcard.2016.08.147 CITATIONS READS 8 266 3 authors, including: Selcuk Ozturk Ertan Yetkin Ankara University Istinye University, LIV Hospital 56 PUBLICATIONS 121 CITATIONS 227 PUBLICATIONS 3,259 CITATIONS SEE PROFILE SEE PROFILE Some of the authors of this publication are also working on these related projects: microbiology View project golden ratio View project All content following this page was uploaded by Ertan Yetkin on 23 August 2019. The user has requested enhancement of the downloaded file. International Journal of Cardiology 223 (2016) 143–145 Contents lists available at ScienceDirect International Journal of Cardiology journal homepage: www.elsevier.com/locate/ijcard Review Golden ratio: A subtle regulator in our body and cardiovascular system? Selcuk Ozturk a, Kenan Yalta b, Ertan Yetkin c,⁎ a Abant Izzet Baysal University, Faculty of Medicine, Department of Cardiology, Bolu, Turkey b Trakya University, Faculty of Medicine, Department of Cardiology, Edirne, Turkey c Yenisehir Hospital, Division of Cardiology, Mersin, Turkey article info abstract Article history: Golden ratio, which is an irrational number and also named as the Greek letter Phi (φ), is defined as the ratio be- Received 13 July 2016 tween two lines of unequal length, where the ratio of the lengths of the shorter to the longer is the same as the Accepted 7 August 2016 ratio between the lengths of the longer and the sum of the lengths. -
Elliptic Curves in Public Key Cryptography: the Diffie Hellman
Elliptic Curves in Public Key Cryptography: The Diffie Hellman Key Exchange Protocol and its relationship to the Elliptic Curve Discrete Logarithm Problem Public Key Cryptography Public key cryptography is a modern form of cryptography that allows different parties to exchange information securely over an insecure network, without having first to agree upon some secret key. The main use of public key cryptography is to provide information security in computer science, for example to transfer securely email, credit card details or other secret information between sender and recipient via the internet. There are three steps involved in transferring information securely from person A to person B over an insecure network. These are encryption of the original information, called the plaintext, transfer of the encrypted message, or ciphertext, and decryption of the ciphertext back into plaintext. Since the transfer of the ciphertext is over an insecure network, any spy has access to the ciphertext and thus potentially has access to the original information, provided he is able to decipher the message. Thus, a successful cryptosystem must be able encrypt the original message in such a way that only the intended receiver can decipher the ciphertext. The goal of public key cryptography is to make the problem of deciphering the encrypted message too difficult to do in a reasonable time (by say brute-force) unless certain key facts are known. Ideally, only the intended sender and receiver of a message should know these certain key facts. Any certain piece of information that is essential in order to decrypt a message is known as a key. -
Generating Fractals Using Complex Functions
Generating Fractals Using Complex Functions Avery Wengler and Eric Wasser What is a Fractal? ● Fractals are infinitely complex patterns that are self-similar across different scales. ● Created by repeating simple processes over and over in a feedback loop. ● Often represented on the complex plane as 2-dimensional images Where do we find fractals? Fractals in Nature Lungs Neurons from the Oak Tree human cortex Regardless of scale, these patterns are all formed by repeating a simple branching process. Geometric Fractals “A rough or fragmented geometric shape that can be split into parts, each of which is (at least approximately) a reduced-size copy of the whole.” Mandelbrot (1983) The Sierpinski Triangle Algebraic Fractals ● Fractals created by repeatedly calculating a simple equation over and over. ● Were discovered later because computers were needed to explore them ● Examples: ○ Mandelbrot Set ○ Julia Set ○ Burning Ship Fractal Mandelbrot Set ● Benoit Mandelbrot discovered this set in 1980, shortly after the invention of the personal computer 2 ● zn+1=zn + c ● That is, a complex number c is part of the Mandelbrot set if, when starting with z0 = 0 and applying the iteration repeatedly, the absolute value of zn remains bounded however large n gets. Animation based on a static number of iterations per pixel. The Mandelbrot set is the complex numbers c for which the sequence ( c, c² + c, (c²+c)² + c, ((c²+c)²+c)² + c, (((c²+c)²+c)²+c)² + c, ...) does not approach infinity. Julia Set ● Closely related to the Mandelbrot fractal ● Complementary to the Fatou Set Featherino Fractal Newton’s method for the roots of a real valued function Burning Ship Fractal z2 Mandelbrot Render Generic Mandelbrot set. -
Iterated Function Systems, Ruelle Operators, and Invariant Projective Measures
MATHEMATICS OF COMPUTATION Volume 75, Number 256, October 2006, Pages 1931–1970 S 0025-5718(06)01861-8 Article electronically published on May 31, 2006 ITERATED FUNCTION SYSTEMS, RUELLE OPERATORS, AND INVARIANT PROJECTIVE MEASURES DORIN ERVIN DUTKAY AND PALLE E. T. JORGENSEN Abstract. We introduce a Fourier-based harmonic analysis for a class of dis- crete dynamical systems which arise from Iterated Function Systems. Our starting point is the following pair of special features of these systems. (1) We assume that a measurable space X comes with a finite-to-one endomorphism r : X → X which is onto but not one-to-one. (2) In the case of affine Iterated Function Systems (IFSs) in Rd, this harmonic analysis arises naturally as a spectral duality defined from a given pair of finite subsets B,L in Rd of the same cardinality which generate complex Hadamard matrices. Our harmonic analysis for these iterated function systems (IFS) (X, µ)is based on a Markov process on certain paths. The probabilities are determined by a weight function W on X. From W we define a transition operator RW acting on functions on X, and a corresponding class H of continuous RW - harmonic functions. The properties of the functions in H are analyzed, and they determine the spectral theory of L2(µ).ForaffineIFSsweestablish orthogonal bases in L2(µ). These bases are generated by paths with infinite repetition of finite words. We use this in the last section to analyze tiles in Rd. 1. Introduction One of the reasons wavelets have found so many uses and applications is that they are especially attractive from the computational point of view. -
Study on the Use of Cryptographic Techniques in Europe
Study on the use of cryptographic techniques in Europe [Deliverable – 2011-12-19] Updated on 2012-04-20 II Study on the use of cryptographic techniques in Europe Contributors to this report Authors: Edward Hamilton and Mischa Kriens of Analysys Mason Ltd Rodica Tirtea of ENISA Supervisor of the project: Rodica Tirtea of ENISA ENISA staff involved in the project: Demosthenes Ikonomou, Stefan Schiffner Agreements or Acknowledgements ENISA would like to thank the contributors and reviewers of this study. Study on the use of cryptographic techniques in Europe III About ENISA The European Network and Information Security Agency (ENISA) is a centre of network and information security expertise for the EU, its member states, the private sector and Europe’s citizens. ENISA works with these groups to develop advice and recommendations on good practice in information security. It assists EU member states in implementing relevant EU leg- islation and works to improve the resilience of Europe’s critical information infrastructure and networks. ENISA seeks to enhance existing expertise in EU member states by supporting the development of cross-border communities committed to improving network and information security throughout the EU. More information about ENISA and its work can be found at www.enisa.europa.eu. Contact details For contacting ENISA or for general enquiries on cryptography, please use the following de- tails: E-mail: [email protected] Internet: http://www.enisa.europa.eu Legal notice Notice must be taken that this publication represents the views and interpretations of the au- thors and editors, unless stated otherwise. This publication should not be construed to be a legal action of ENISA or the ENISA bodies unless adopted pursuant to the ENISA Regulation (EC) No 460/2004 as lastly amended by Regulation (EU) No 580/2011. -
The Mathematics of Art: an Untold Story Project Script Maria Deamude Math 2590 Nov 9, 2010
The Mathematics of Art: An Untold Story Project Script Maria Deamude Math 2590 Nov 9, 2010 Art is a creative venue that can, and has, been used for many purposes throughout time. Religion, politics, propaganda and self-expression have all used art as a vehicle for conveying various messages, without many references to the technical aspects. Art and mathematics are two terms that are not always thought of as being interconnected. Yet they most definitely are; for art is a highly technical process. Following the histories of maths and sciences – if not instigating them – art practices and techniques have developed and evolved since man has been on earth. Many mathematical developments occurred during the Italian and Northern Renaissances. I will describe some of the math involved in art-making, most specifically in architectural and painting practices. Through the medieval era and into the Renaissance, 1100AD through to 1600AD, certain significant mathematical theories used to enhance aesthetics developed. Understandings of line, and placement and scale of shapes upon a flat surface developed to the point of creating illusions of reality and real, three dimensional space. One can look at medieval frescos and altarpieces and witness a very specific flatness which does not create an illusion of real space. Frescos are like murals where paint and plaster have been mixed upon a wall to create the image – Michelangelo’s work in the Sistine Chapel and Leonardo’s The Last Supper are both famous examples of frescos. The beginning of the creation of the appearance of real space can be seen in Giotto’s frescos in the late 1200s and early 1300s. -
Sphere Tracing, Distance Fields, and Fractals Alexander Simes
Sphere Tracing, Distance Fields, and Fractals Alexander Simes Advisor: Angus Forbes Secondary: Andrew Johnson Fall 2014 - 654108177 Figure 1: Sphere Traced images of Menger Cubes and Mandelboxes shaded by ambient occlusion approximation on the left and Blinn-Phong with shadows on the right Abstract Methods to realistically display complex surfaces which are not practical to visualize using traditional techniques are presented. Additionally an application is presented which is capable of utilizing some of these techniques in real time. Properties of these surfaces and their implications to a real time application are discussed. Table of Contents 1 Introduction 3 2 Minimal CPU Sphere Tracing Model 4 2.1 Camera Model 4 2.2 Marching with Distance Fields Introduction 5 2.3 Ambient Occlusion Approximation 6 3 Distance Fields 9 3.1 Signed Sphere 9 3.2 Unsigned Box 9 3.3 Distance Field Operations 10 4 Blinn-Phong Shadow Sphere Tracing Model 11 4.1 Scene Composition 11 4.2 Maximum Marching Iteration Limitation 12 4.3 Surface Normals 12 4.4 Blinn-Phong Shading 13 4.5 Hard Shadows 14 4.6 Translation to GPU 14 5 Menger Cube 15 5.1 Introduction 15 5.2 Iterative Definition 16 6 Mandelbox 18 6.1 Introduction 18 6.2 boxFold() 19 6.3 sphereFold() 19 6.4 Scale and Translate 20 6.5 Distance Function 20 6.6 Computational Efficiency 20 7 Conclusion 2 1 Introduction Sphere Tracing is a rendering technique for visualizing surfaces using geometric distance. Typically surfaces applicable to Sphere Tracing have no explicit geometry and are implicitly defined by a distance field. -
Leonardo Da Vinci's Study of Light and Optics: a Synthesis of Fields in The
Bitler Leonardo da Vinci’s Study of Light and Optics Leonardo da Vinci’s Study of Light and Optics: A Synthesis of Fields in The Last Supper Nicole Bitler Stanford University Leonardo da Vinci’s Milanese observations of optics and astronomy complicated his understanding of light. Though these complications forced him to reject “tidy” interpretations of light and optics, they ultimately allowed him to excel in the portrayal of reflection, shadow, and luminescence (Kemp, 2006). Leonardo da Vinci’s The Last Supper demonstrates this careful study of light and the relation of light to perspective. In the work, da Vinci delved into the complications of optics and reflections, and its renown guided the artistic study of light by subsequent masters. From da Vinci’s personal manuscripts, accounts from his contemporaries, and present-day art historians, the iterative relationship between Leonardo da Vinci’s study of light and study of optics becomes apparent, as well as how his study of the two fields manifested in his paintings. Upon commencement of courtly service in Milan, da Vinci immersed himself in a range of scholarly pursuits. Da Vinci’s artistic and mathematical interest in perspective led him to the study of optics. Initially, da Vinci “accepted the ancient (and specifically Platonic) idea that the eye functioned by emitting a special type of visual ray” (Kemp, 2006, p. 114). In his early musings on the topic, da Vinci reiterated this notion, stating in his notebooks that, “the eye transmits through the atmosphere its own image to all the objects that are in front of it and receives them into itself” (Suh, 2005, p.