Adrian Crenshaw
Total Page：16
File Type：pdf, Size：1020Kb
Load more
Recommended publications
-
The Unicode Cookbook for Linguists: Managing Writing Systems Using Orthography Profiles
Zurich Open Repository and Archive University of Zurich Main Library Strickhofstrasse 39 CH-8057 Zurich www.zora.uzh.ch Year: 2017 The Unicode Cookbook for Linguists: Managing writing systems using orthography profiles Moran, Steven ; Cysouw, Michael DOI: https://doi.org/10.5281/zenodo.290662 Posted at the Zurich Open Repository and Archive, University of Zurich ZORA URL: https://doi.org/10.5167/uzh-135400 Monograph The following work is licensed under a Creative Commons: Attribution 4.0 International (CC BY 4.0) License. Originally published at: Moran, Steven; Cysouw, Michael (2017). The Unicode Cookbook for Linguists: Managing writing systems using orthography profiles. CERN Data Centre: Zenodo. DOI: https://doi.org/10.5281/zenodo.290662 The Unicode Cookbook for Linguists Managing writing systems using orthography profiles Steven Moran & Michael Cysouw Change dedication in localmetadata.tex Preface This text is meant as a practical guide for linguists, and programmers, whowork with data in multilingual computational environments. We introduce the basic concepts needed to understand how writing systems and character encodings function, and how they work together. The intersection of the Unicode Standard and the International Phonetic Al- phabet is often not met without frustration by users. Nevertheless, thetwo standards have provided language researchers with a consistent computational architecture needed to process, publish and analyze data from many different languages. We bring to light common, but not always transparent, pitfalls that researchers face when working with Unicode and IPA. Our research uses quantitative methods to compare languages and uncover and clarify their phylogenetic relations. However, the majority of lexical data available from the world’s languages is in author- or document-specific orthogra- phies. -
UTF-8-Plan9-Paper
Hello World or Kαληµε´ρα κο´σµε or Rob Pike Ken Thompson AT&T Bell Laboratories Murray Hill, New Jersey 07974 ABSTRACT Plan 9 from Bell Labs has recently been converted from ASCII to an ASCII- compatible variant of Unicode, a 16-bit character set. In this paper we explain the rea- sons for the change, describe the character set and representation we chose, and present the programming models and software changes that support the new text format. Although we stopped short of full internationalizationÐfor example, system error mes- sages are in Unixese, not JapaneseÐwe believe Plan 9 is the first system to treat the rep- resentation of all major languages on a uniform, equal footing throughout all its software. Introduction The world is multilingual but most computer systems are based on English and ASCII. The release of Plan 9 [Pike90], a new distributed operating system from Bell Laboratories, seemed a good occasion to correct this chauvinism. It is easier to make such deep changes when building new systems than by refit- ting old ones. The ANSI C standard [ANSIC] contains some guidance on the matter of ‘wide’ and ‘multi-byte’ characters but falls far short of solving the myriad associated problems. We could find no literature on how to convert a system to larger character sets, although some individual programs had been converted. This paper reports what we discovered as we explored the problem of representing multilingual text at all levels of an operating system, from the file system and kernel through the applications and up to the window sys- tem and display. -
Part 1: Introduction to The
PREVIEW OF THE IPA HANDBOOK Handbook of the International Phonetic Association: A guide to the use of the International Phonetic Alphabet PARTI Introduction to the IPA 1. What is the International Phonetic Alphabet? The aim of the International Phonetic Association is to promote the scientific study of phonetics and the various practical applications of that science. For both these it is necessary to have a consistent way of representing the sounds of language in written form. From its foundation in 1886 the Association has been concerned to develop a system of notation which would be convenient to use, but comprehensive enough to cope with the wide variety of sounds found in the languages of the world; and to encourage the use of thjs notation as widely as possible among those concerned with language. The system is generally known as the International Phonetic Alphabet. Both the Association and its Alphabet are widely referred to by the abbreviation IPA, but here 'IPA' will be used only for the Alphabet. The IPA is based on the Roman alphabet, which has the advantage of being widely familiar, but also includes letters and additional symbols from a variety of other sources. These additions are necessary because the variety of sounds in languages is much greater than the number of letters in the Roman alphabet. The use of sequences of phonetic symbols to represent speech is known as transcription. The IPA can be used for many different purposes. For instance, it can be used as a way to show pronunciation in a dictionary, to record a language in linguistic fieldwork, to form the basis of a writing system for a language, or to annotate acoustic and other displays in the analysis of speech. -
Detection of Suspicious IDN Homograph Domains Using Active DNS Measurements
A Case of Identity: Detection of Suspicious IDN Homograph Domains Using Active DNS Measurements Ramin Yazdani Olivier van der Toorn Anna Sperotto University of Twente University of Twente University of Twente Enschede, The Netherlands Enschede, The Netherlands Enschede, The Netherlands [email protected] [email protected] [email protected] Abstract—The possibility to include Unicode characters in problem in the case of Unicode – ASCII homograph domain names allows users to deal with domains in their domains. We propose a low-cost method for proactively regional languages. This is done by introducing Internation- detecting suspicious IDNs. Since our proactive approach alized Domain Names (IDN). However, the visual similarity is based not on use, but on characteristics of the domain between different Unicode characters - called homoglyphs name itself and its associated DNS records, we are able to - is a potential security threat, as visually similar domain provide an early alert for both domain owners as well as names are often used in phishing attacks. Timely detection security researchers to further investigate these domains of suspicious homograph domain names is an important before they are involved in malicious activities. The main step towards preventing sophisticated attacks, since this can contributions of this paper are that we: prevent unaware users to access those homograph domains • propose an improved Unicode Confusion table able that actually carry malicious content. We therefore propose to detect 2.97 times homograph domains compared a structured approach to identify suspicious homograph to the state-of-the-art confusion tables; domain names based not on use, but on characteristics • combine active DNS measurements and Unicode of the domain name itself and its associated DNS records. -
Phonemes Visit the Dyslexia Reading Well
For More Information on Phonemes Visit the Dyslexia Reading Well. www.dyslexia-reading-well.com The 44 Sounds (Phonemes) of English A phoneme is a speech sound. It’s the smallest unit of sound that distinguishes one word from another. Since sounds cannot be written, we use letters to represent or stand for the sounds. A grapheme is the written representation (a letter or cluster of letters) of one sound. It is generally agreed that there are approximately 44 sounds in English, with some variation dependent on accent and articulation. The 44 English phonemes are represented by the 26 letters of the alphabet individually and in combination. Phonics instruction involves teaching the relationship between sounds and the letters used to represent them. There are hundreds of spelling alternatives that can be used to represent the 44 English phonemes. Only the most common sound / letter relationships need to be taught explicitly. The 44 English sounds can be divided into two major categories – consonants and vowels. A consonant sound is one in which the air flow is cut off, either partially or completely, when the sound is produced. In contrast, a vowel sound is one in which the air flow is unobstructed when the sound is made. The vowel sounds are the music, or movement, of our language. The 44 phonemes represented below are in line with the International Phonetic Alphabet. Consonants Sound Common Spelling alternatives spelling /b/ b bb ball ribbon /d/ d dd ed dog add filled /f/ f ff ph gh lf ft fan cliff phone laugh calf often /g/ g gg gh gu -
Mctsbug: Generating Adversarial Text
Under review as a conference paper at ICLR 2019 MCTSBUG:GENERATING ADVERSARIAL TEXT SE- QUENCES VIA MONTE CARLO TREE SEARCH AND HO- MOGLYPH ATTACK Anonymous authors Paper under double-blind review ABSTRACT Crafting adversarial examples on discrete inputs like text sequences is fundamen- tally different from generating such examples for continuous inputs like images. This paper tries to answer the question: under a black-box setting, can we create adversarial examples automatically to effectively fool deep learning classifiers on texts by making imperceptible changes? Our answer is a firm yes. Previous ef- forts mostly replied on using gradient evidence, and they are less effective either due to finding the nearest neighbor word (wrt meaning) automatically is difficult or relying heavily on hand-crafted linguistic rules. We, instead, use Monte Carlo tree search (MCTS) for finding the most important few words to perturb and per- form homoglyph attack by replacing one character in each selected word with a symbol of identical shape. Our novel algorithm, we call MCTSBug, is black-box and extremely effective at the same time. Our experimental results indicate that MCTSBug can fool deep learning classifiers at the success rates of 95% on seven large-scale benchmark datasets, by perturbing only a few characters. Surprisingly, MCTSBug, without relying on gradient information at all, is more effective than the gradient-based white-box baseline. Thanks to the nature of homoglyph attack, the generated adversarial perturbations are almost imperceptible to human eyes. 1 INTRODUCTION Recent studies have shown that adding small modifications to continuous inputs can fool state-of- the-art deep classifiers, resulting in incorrect classifications (Szegedy et al., 2014; Goodfellow et al., 2014). -
Information, Characters, Unicode
Information, Characters, Unicode Unicode © 24 August 2021 1 / 107 Hidden Moral Small mistakes can be catastrophic! Style Care about every character of your program. Tip: printf Care about every character in the program’s output. (Be reasonably tolerant and defensive about the input. “Fail early” and clearly.) Unicode © 24 August 2021 2 / 107 Imperative Thou shalt care about every Ěaracter in your program. Unicode © 24 August 2021 3 / 107 Imperative Thou shalt know every Ěaracter in the input. Thou shalt care about every Ěaracter in your output. Unicode © 24 August 2021 4 / 107 Information – Characters In modern computing, natural-language text is very important information. (“number-crunching” is less important.) Characters of text are represented in several different ways and a known character encoding is necessary to exchange text information. For many years an important encoding standard for characters has been US ASCII–a 7-bit encoding. Since 7 does not divide 32, the ubiquitous word size of computers, 8-bit encodings are more common. Very common is ISO 8859-1 aka “Latin-1,” and other 8-bit encodings of characters sets for languages other than English. Currently, a very large multi-lingual character repertoire known as Unicode is gaining importance. Unicode © 24 August 2021 5 / 107 US ASCII (7-bit), or bottom half of Latin1 NUL SOH STX ETX EOT ENQ ACK BEL BS HT LF VT FF CR SS SI DLE DC1 DC2 DC3 DC4 NAK SYN ETP CAN EM SUB ESC FS GS RS US !"#$%&’()*+,-./ 0123456789:;<=>? @ABCDEFGHIJKLMNO PQRSTUVWXYZ[\]^_ `abcdefghijklmno pqrstuvwxyz{|}~ DEL Unicode Character Sets © 24 August 2021 6 / 107 Control Characters Notice that the first twos rows are filled with so-called control characters. -
Imperceptible NLP Attacks
Bad Characters: Imperceptible NLP Attacks Nicholas Boucher Ilia Shumailov University of Cambridge University of Cambridge Cambridge, United Kingdom Vector Institute, University of Toronto [email protected] [email protected] Ross Anderson Nicolas Papernot University of Cambridge Vector Institute, University of Toronto University of Edinburgh Toronto, Canada [email protected] [email protected] Abstract—Several years of research have shown that machine- Indeed, the title of this paper contains 1000 invisible characters -
Homoglyph a Avancé Des Attaques Par Phishing
Homoglyph a avancé des attaques par phishing Contenu Introduction Homoglyph a avancé des attaques par phishing Cisco relatif prennent en charge des discussions de la Communauté Introduction Ce document décrit l'utilisation des caractères de homoglyph dans des attaques par phishing avancées et comment se rendre compte de ces derniers en utilisant le message et le contenu filtre sur l'appliance de sécurité du courrier électronique de Cisco (ESA). Homoglyph a avancé des attaques par phishing Dans des attaques par phishing avancées aujourd'hui, les emails de phishing peuvent contenir des caractères de homogyph. Un homoglyph est un caractère des textes avec les formes qui sont près d'identique ou de semblable entre eux. Il peut y avoir d'URLs encastré dans les emails phising qui ne seront pas bloqués par des filtres de message ou de contenu configurés sur l'ESA. Un exemple de scénario peut être comme suit : Le client veut bloquer un email qui a eu contient l'URL de www.pɑypal.com. Afin de faire ainsi, on écrit un filtre satisfait d'arrivée qui recherchant l'URL contenant www.paypal.com. L'action de ce filtre satisfait serait configurée pour chuter et annoncer. Le client a reçu l'exemple de contenir d'email : www.pɑypal.com Le filtre satisfait en tant que configuré contient : www.paypal.com Si vous prenez à un regarder l'URL d'effectif par l'intermédiaire des DN vous noterez qu'ils les résolvent différemment : $ dig www.pypal.com ; <<>> DiG 9.8.3-P1 <<>> www.pypal.com ;; global options: +cmd ;; Got answer: ;; ->>HEADER<<- opcode: QUERY, status: NXDOMAIN, id: 37851 ;; flags: qr rd ra; QUERY: 1, ANSWER: 0, AUTHORITY: 1, ADDITIONAL: 0 ;; QUESTION SECTION: ;www.p\201\145ypal.com. -
Integrated Issues Report)
The IDN Variant Issues Project A Study of Issues Related to the Management of IDN Variant TLDs (Integrated Issues Report) 20 February 2012 The IDN Variant Issues Project: A Study of Issues Related to the Management of IDN Variant TLDs 20 February 2012 Contents Executive Summary…………………………………………………………………………………………………………….. 6 1 Overview of this Report………………………………………………………………………………………………. 9 1.1 Fundamental Assumptions…………………………………………………………………………………. 10 1.2 Variants and the Current Environment………………………………………………………………. 12 2 Project Overview……………………………………………………………………………………………………….. 16 2.1 The Variant Issues Project…………………………………………………………………………………… 16 2.2 Objectives of the Integrated Issues Report………………………………………………………… 17 2.3 Scope of the Integrated Issues Report………………………………………………………………… 18 3 Range of Possible Variant Cases Identified………………………………………………………………… 19 3.1 Classification of Variants as Discovered……………………………………………………………… 19 3.1.1 Code Point Variants……………………………………………………………………………………. 20 3.1.2 Whole-String Variants………………………………………………………………………………… 20 3.2 Taxonomy of Identified Variant Cases……………………………………………………………….. 21 3.3 Discussion of Variant Classes……………………………………………………………………………… 28 3.4 Visual Similarity Cases……………………………………………………………………………………….. 33 3.4.1 Treatment of Visual Similarity Cases………………………………………………………….. 33 3.4.2 Cross-Script Visual Similarity ……………………………………………………………………….34 3.4.3 Terminology concerning Visual Similarity ……………………………………………………35 3.5 Whole-String Issues …………………………………………………………………………………………….36 3.6 Synopsis of Issues ……………………………………………………………………………………………….39 -
IETF A. Freytag Internet-Draft ASMUS, Inc. Intended Status: Standards Track J
IETF A. Freytag Internet-Draft ASMUS, Inc. Intended status: Standards Track J. Klensin Expires: December 31, 2018 A. Sullivan Oracle Corp. June 29, 2018 Those Troublesome Characters: A Registry of Unicode Code Points Needing Special Consideration When Used in Network Identifiers draft-freytag-troublesome-characters-02 Abstract Unicode’s design goal is to be the universal character set for all applications. The goal entails the inclusion of very large numbers of characters. It is also focused on written language in general; special provisions have always been needed for identifiers. The sheer size of the repertoire increases the possibility of accidental or intentional use of characters that can cause confusion among users, particularly where linguistic context is ambiguous, unavailable, or impossible to determine. A registry of code points that can be sometimes especially problematic may be useful to guide system administrators in setting parameters for allowable code points or combinations in an identifier system, and to aid applications in creating security aids for users. Status of This Memo This Internet-Draft is submitted in full conformance with the provisions of BCP 78 and BCP 79. Internet-Drafts are working documents of the Internet Engineering Task Force (IETF). Note that other groups may also distribute working documents as Internet-Drafts. The list of current Internet- Drafts is at https://datatracker.ietf.org/drafts/current/. Internet-Drafts are draft documents valid for a maximum of six months and may be updated, replaced, or obsoleted by other documents at any time. It is inappropriate to use Internet-Drafts as reference material or to cite them other than as "work in progress." This Internet-Draft will expire on December 31, 2018. -
MSR-4: Annotated Repertoire Tables, Non-CJK
Maximal Starting Repertoire - MSR-4 Annotated Repertoire Tables, Non-CJK Integration Panel Date: 2019-01-25 How to read this file: This file shows all non-CJK characters that are included in the MSR-4 with a yellow background. The set of these code points matches the repertoire specified in the XML format of the MSR. Where present, annotations on individual code points indicate some or all of the languages a code point is used for. This file lists only those Unicode blocks containing non-CJK code points included in the MSR. Code points listed in this document, which are PVALID in IDNA2008 but excluded from the MSR for various reasons are shown with pinkish annotations indicating the primary rationale for excluding the code points, together with other information about usage background, where present. Code points shown with a white background are not PVALID in IDNA2008. Repertoire corresponding to the CJK Unified Ideographs: Main (4E00-9FFF), Extension-A (3400-4DBF), Extension B (20000- 2A6DF), and Hangul Syllables (AC00-D7A3) are included in separate files. For links to these files see "Maximal Starting Repertoire - MSR-4: Overview and Rationale". How the repertoire was chosen: This file only provides a brief categorization of code points that are PVALID in IDNA2008 but excluded from the MSR. For a complete discussion of the principles and guidelines followed by the Integration Panel in creating the MSR, as well as links to the other files, please see “Maximal Starting Repertoire - MSR-4: Overview and Rationale”. Brief description of exclusion