A Hybrid Model for Sense Guessing of Chinese Unknown Words

PACLIC 23 / City University of Hong Kong / 3-5 December 200

A Survey on Password Guessing

Text password has served as the most popular method for user authentication so far, and is not likely to be totally replaced in foreseeable future. Password authentication offers several desirable properties (e.g., low-cost, highly available, easy-to-implement, reusable). However, it suffers from a critical security issue mainly caused by the inability to memorize complicated strings of humans. Users tend to choose easy-to-remember passwords which are not uniformly distributed in the key space. Thus, user-selected passwords are susceptible to guessing attacks. In order to encourage and support users to use strong passwords, it is necessary to simulate automated password guessing methods to determine the passwords' strength and identify weak passwords. A large number of password guessing models have been proposed in the literature. However, little attention was paid to the task of providing a systematic survey which is necessary to review the state-of-the-art approaches, identify gaps, and avoid duplicate studies. Motivated by that, we conduct a comprehensive survey on all password guessing studies presented in the literature from 1979 to 2022. We propose a generic methodology map to present an overview of existing methods. Then, we explain each representative approach in detail. The experimental procedures and available datasets used to evaluate password guessing models are summarized, and the reported performances of representative studies are compared. Finally, the current limitations and the open problems as future research directions are discussed. We believe that this survey is helpful to both experts and newcomers who are interested in password securityComment: 35 pages, 5 figures, 5 table

Improving the Eco-system of Passwords

Password-based authentication is perhaps the most widely used method for user authentication. Passwords are both easy to understand and use, and easy to implement. With these advantages, password-based authentication is likely to stay as an important part of security in the foreseeable future. One major weakness of password-based authentication is that many users tend to choose weak passwords that are easy to guess. In this dissertation, we address the challenge and improve the eco-system of passwords in multiple aspects. Firstly, we provide methodologies that help password research. To be more specific, we propose Probability Threshold Graphs, which is superior to Guess Number Graphs when comparing password models and password datasets. We also introduce rich literature of statistical language modeling into password modeling and show that if used correctly, whole-string Markov models outperform Probabilistic Context Free Grammar models. Secondly, we improve password policies and practice used by websites by studying how to best check weak passwords. We model different password strength checking methods as Password Ranking Algorithms (PRAs), and introduce two methods for comparing different PRAs: the β-Residual Strength Graph and the Normalized β-Residual Strength Graph. Finally, we examine the security and usability of commonly suggested password generation strategies. We find that for mnemonic sentence-based strategies, differences in the exact instructions have a tremendous impact on the security level of the resulting passwords. For word-based strategies, security of the resulting passwords mainly depends on the number of words required, and requiring at least 3 words is likely to result in passwords stronger than the general passwords chosen by typical users

Entry Generation for New Words by Analogy for Morphological Lexicons

Peer reviewe

A Cognitively-oriented Encapsulation of Strategies Utilized for Lexical Development: In search of a flexible and highly interactive curriculum

The purpose of this paper is to inquire in depth into vocabulary learning/ acquisition strategies and techniques as related to second/foreign language. In doing so, the study is intended to focus particularly on the variables connected to lexical knowledge and accordingly set up a fairly comprehensive framework which includes and accounts for the most important strategies and pertinent factors within the vocabulary acquisition context. The study presents four salient variables; three from Flavell’s cognitive model (1992), and the variable of context is introduced to give meticulous importance to review. The organic notion underlying this investigation is that the most effectual and successful lexical development will occur in multipurpose and highly interactive curriculums that attain a pedagogically well-reasoned equilibrium between explicit and implicit activities for L2 learners at all levels of their progress.El objetivo de este trabajo es comprobar en profundidad las estrategias y técnicas de adquisición/aprendizaje de vocabulario relacionadas con una lengua extranjera. El trabajo se centra en las variables que tiene que ver con el conocimiento léxico y consecuentemente establecer un marco comprensivo que tenga en cuenta las estrategias más importantes y los factores más pertinentes dentro del contexto de adquisición de vocabulario. El estudio presenta cuatro variables, tres del modelo cognitivo de Flavell (1992) y una cuarta, el contexto se añade para dar más importancia a la revisión. La noción que subyace a esta investigación es que los desarrollos léxicos con mayor éxito se darán en curriculums que ofrezcan múltiples objetivos y que sean muy interactivos para obtener un equilibrio pedagógico equilibrado y bien razonado entre actividades explícitas e implícitas para estudiantes de una segunda lengua en todos niveles de su progreso

Hybrid tag-set for natural language processing.

Leung Wai Kwong.Thesis (M.Phil.)--Chinese University of Hong Kong, 1999.Includes bibliographical references (leaves 90-95).Abstracts in English and Chinese.Chapter 1 --- Introduction --- p.1Chapter 1.1 --- Motivation --- p.1Chapter 1.2 --- Objective --- p.3Chapter 1.3 --- Organization of thesis --- p.3Chapter 2 --- Background --- p.5Chapter 2.1 --- Chinese Noun Phrases Parsing --- p.5Chapter 2.2 --- Chinese Noun Phrases --- p.6Chapter 2.3 --- Problems with Syntactic Parsing --- p.11Chapter 2.3.1 --- Conjunctive Noun Phrases --- p.11Chapter 2.3.2 --- De-de Noun Phrases --- p.12Chapter 2.3.3 --- Compound Noun Phrases --- p.13Chapter 2.4 --- Observations --- p.15Chapter 2.4.1 --- Inadequacy in Part-of-Speech Categorization for Chi- nese NLP --- p.16Chapter 2.4.2 --- The Need of Semantic in Noun Phrase Parsing --- p.17Chapter 2.5 --- Summary --- p.17Chapter 3 --- Hybrid Tag-set --- p.19Chapter 3.1 --- Objectives --- p.19Chapter 3.1.1 --- Resolving Parsing Ambiguities --- p.19Chapter 3.1.2 --- Investigation of Nominal Compound Noun Phrases --- p.20Chapter 3.2 --- Definition of Hybrid Tag-set --- p.20Chapter 3.3 --- Introduction to Cilin --- p.21Chapter 3.4 --- Problems with Cilin --- p.23Chapter 3.4.1 --- Unknown words --- p.23Chapter 3.4.2 --- Multiple Semantic Classes --- p.25Chapter 3.5 --- Introduction to Chinese Word Formation --- p.26Chapter 3.5.1 --- Disyllabic Word Formation --- p.26Chapter 3.5.2 --- Polysyllabic Word Formation --- p.28Chapter 3.5.3 --- Observation --- p.29Chapter 3.6 --- Automatic Assignment of Hybrid Tag to Chinese Word --- p.31Chapter 3.7 --- Summary --- p.34Chapter 4 --- Automatic Semantic Assignment --- p.35Chapter 4.1 --- Previous Researches on Semantic Tagging --- p.36Chapter 4.2 --- SAUW - Automatic Semantic Assignment of Unknown Words --- p.37Chapter 4.2.1 --- POS-to-SC Association (Process 1) --- p.38Chapter 4.2.2 --- Morphology-based Deduction (Process 2) --- p.39Chapter 4.2.3 --- Di-syllabic Word Analysis (Process 3 and 4) --- p.41Chapter 4.2.4 --- Poly-syllabic Word Analysis (Process 5) --- p.47Chapter 4.3 --- Illustrative Examples --- p.47Chapter 4.4 --- Evaluation and Analysis --- p.49Chapter 4.4.1 --- Experiments --- p.49Chapter 4.4.2 --- Error Analysis --- p.51Chapter 4.5 --- Summary --- p.52Chapter 5 --- Word Sense Disambiguation --- p.53Chapter 5.1 --- Introduction to Word Sense Disambiguation --- p.54Chapter 5.2 --- Previous Works on Word Sense Disambiguation --- p.55Chapter 5.2.1 --- Linguistic-based Approaches --- p.56Chapter 5.2.2 --- Corpus-based Approaches --- p.58Chapter 5.3 --- Our Approach --- p.60Chapter 5.3.1 --- Bi-gram Co-occurrence Probabilities --- p.62Chapter 5.3.2 --- Tri-gram Co-occurrence Probabilities --- p.63Chapter 5.3.3 --- Design consideration --- p.65Chapter 5.3.4 --- Error Analysis --- p.67Chapter 5.4 --- Summary --- p.68Chapter 6 --- Hybrid Tag-set for Chinese Noun Phrase Parsing --- p.69Chapter 6.1 --- Resolving Ambiguous Noun Phrases --- p.70Chapter 6.1.1 --- Experiment --- p.70Chapter 6.1.2 --- Results --- p.72Chapter 6.2 --- Summary --- p.78Chapter 7 --- Conclusion --- p.80Chapter 7.1 --- Summary --- p.80Chapter 7.2 --- Difficulties Encountered --- p.83Chapter 7.2.1 --- Lack of Training Corpus --- p.83Chapter 7.2.2 --- Features of Chinese word formation --- p.84Chapter 7.2.3 --- Problems with linguistic sources --- p.85Chapter 7.3 --- Contributions --- p.86Chapter 7.3.1 --- Enrichment to the Cilin --- p.86Chapter 7.3.2 --- Enhancement in syntactic parsing --- p.87Chapter 7.4 --- Further Researches --- p.88Chapter 7.4.1 --- Investigation into words that undergo semantic changes --- p.88Chapter 7.4.2 --- Incorporation of more information into the hybrid tag-set --- p.89Chapter A --- POS Tag-set by Tsinghua University (清華大學） --- p.96Chapter B --- Morphological Rules --- p.100Chapter C --- Syntactic Rules for Di-syllabic Words Formation --- p.10