DOCSLIB.ORG

A Human Computation Approach to Graph Isomorphism

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
A Human Computation Approach to Graph Isomorphism A Human Computation Approach to Graph Isomorphism Sriswetha Rajagopal Master of Science School of Computer Science McGill University Montreal,Quebec 2016-02-12 Requirements Statement Copyright Statement ACKNOWLEDGEMENTS Firstly, I would like to express my sincere gratitude to my Professor J´er^ome Waldisp¨uhlfor his continuous support throughout the course of my degree and re- search. This thesis could not have been complete without his knowledge and guid- ance. I would like to extend my gratitude to Olivier Tremblay-Savard for his helpful comments, for answering questions related to my research and for helping me with the french translation of my abstract. I would also like to thank my sister, Charana, my friends, Aman, Mohana and Jaskaran for their participation in testing and playing the game, as well as their helpful feedback. Special thanks to all my friends who played the game. Finally, I take this opportunity to thank my parents whose unwavering faith in me made this thesis possible. ii ABSTRACT Statistics note that people spend an average 8 to 10 hours per week on mo- bile/computer games. Human computation research has already tapped the potential in this area. Games such as Phylo and FoldIt have successfully combined a scien- tific purpose with doing something fun. In this thesis, we aim to present a strategic puzzle as a two player game to approach the problem of graph isomorphism. Graph isomorphism is a well-known computational problem due to its uncertain complexity. We aim to study how humans perform when the problem of graph isomorphism is presented as a game. We introduce \Isorcise", adapted from the mathematical Ehrenfeucht-Fra¨ıss´egame as an interactive two player game called playable on PCs. We conducted experiments on a small group of players (6 players) playing on different graph pairs (11 graph pairs). We show that humans are able to perform reasonably well on small and medium sized graphs as well as some large graphs. We also show that humans can successfully pinpoint non-isomorphism without exploring the whole graph. Finally, we note that our game can be used for other related problems such as maximum common subgraph isomorphism and the counting problem of graph isomorphism. iii ABREG´ E´ Les statistiques d´emontrent qu'en moyenne, les gens jouent de 8 `a10 heures par semaine `ades jeux vid´eossur diff´erentes plateformes (mobile, ordinateur). La recherche en calcul humain exploite d´ej`ace potentiel. Des jeux comme Phylo et FoldIt ont r´eussi`acombiner la r´ealisationd'un objectif scientifique avec une ac- tivit´eplaisante pour le joueur. Dans ce m´emoire,nous pr´esentons un casse-t^ete strat´egiquesous la forme d'un jeu `adeux joueurs dans le but de r´esoudreun probl`eme d'isomorphisme de graphes. L'isomorphisme de graphes est un probl`emebien connu en informatique `acause de sa complexit´eincertaine. Nous introduisons Isorcise, un jeu-avec-propos inspir´edu jeu math´ematiqued'Ehrenfeucht- Fra¨ıss´e,dont l'objectif est de d´ecidersi 2 graphes sont isomorphes. Isorcise est impl´ement´ecomme un jeu interactif `adeux joueurs jouable sur PCs. Nous avons men´eune s´eried'exp´eriencessur un petit groupe de joueurs (6 joueurs) et diff´erentes paires de graphes (11 paires de graphes). Nos r´esultatsmontrent que les humains sont obtiennent des performances raisonnables sur des graphes de petite et moyenne tailles, m^emequelques grands graphes. Nous montrons aussi que les humains peuvent r´eussirrelativement efficacement `aidentifier une absence d'isomorphisme sans explorer l'ensemble du graphe. Enfin, nous notons que notre jeu peut ^etreutilis´epour d'autres probl`emesconnexes tels que l'isomorphisme de sous- graphe commun maximale et le probl`emede comptage du graphe isomorphisme. iv TABLE OF CONTENTS ACKNOWLEDGEMENTS . ii ABSTRACT . iii ABREG´ E......................................´ iv LIST OF TABLES . vii LIST OF FIGURES . ix 1 Introduction . .1 1.1 Introduction . .1 1.1.1 Graph Isomorphism : An overview . .4 1.1.2 Contributions of this Thesis . .5 1.1.3 Thesis Overview . .6 2 Related Work and Literature . .7 2.1 Human computation: Previous work . .7 2.2 Graph isomorphism : Complexity . 13 2.2.1 Practical Algorithms for Graph Isomorphism . 14 3 Isorcise - A two-player graph isomorphism game . 16 3.1 Ehrenfeucht-Fra¨ıss´egame : A brief introduction . 16 3.2 Isorcise - The implementation . 18 3.2.1 The basic setup . 19 3.2.2 Networking . 23 3.2.3 The Algorithm behind Isorcise . 26 4 Isorcise : How to play . 29 4.1 The basic game play . 29 4.1.1 Starting the game . 29 v 4.1.2 Playing the game . 31 4.1.3 Scoring points . 31 4.1.4 Winning the game . 31 4.2 Making smart moves . 33 4.2.1 Sorcerer's perspective . 33 4.2.2 Dweller's perspective . 36 5 Experiments and Results . 39 5.1 Results . 41 5.1.1 Non-isomorphic graphs . 45 5.1.2 Isomorphic graphs . 52 5.1.3 How smart moves help . 58 5.2 Factors affecting game results . 60 5.3 Summary of results . 61 6 Conclusion . 62 6.1 Future Work . 63 Appendix A . 64 References . 68 vi LIST OF TABLES Table page 5{1 The table shows a summary of the various isomorphic graph pairs used. 40 5{2 The table shows a summary of the various non-isomorphic graph pair used. 40 5{3 This table shows results of all levels played in some game instances for isomorphic graphs. The full tables (6{1, 6{2) are in Appendix A. 43 5{4 The table shows results of all levels played on some game instances on non-isomorphic graphs. The full table (6{3) is in Appendix A. 44 5{5 This table shows the average success rate taken from column Game Result of Table 5{3 and column Error of Table 5{4. The last column refers to the total number of levels played on each graph pair by all pairs of players. 46 5{6 Table showing the quickest solution (in terms of number of nodes) found in each pair of non-isomorphic graphs and the time taken to find it. The fraction of graph covered column is defined as the fraction of the Minimum nodes over the total number of Nodes. 48 5{7 Table showing the maximum common subgraph isomorphism (in terms of number of nodes) found in each pair of non-isomorphic graphs. 49 5{8 Isomorphism mapping on 17-node subgraph of 20-node Praust graph. Each row in the table denotes the round in the game, the node number of the node selected in Graph A (according to fig 5{4) on the left, and the node number of the node selected Graph B (according to fig 5{4), on the right, in a given round. 51 5{9 The table shows the minimum time taken to find isomorphism and the average time along with the standard deviation over all correctly played instances on each pair of isomorphic graphs (except for the 30-node graph pair which had only one correctly played instance). 53 vii 5{10 Two different isomorphism mappings on 8-node graph . 57 5{11 Example of unsuccessful case . 57 5{12 Table showing the two attempts made on the 30-node graph by one pair of players. 59 6{1 The complete version of Table 5{3 in section 5.2 . 64 6{2 Table 6{1 continued . 65 6{3 The complete version of Table 5{4 from section 5.2 . 66 viii LIST OF FIGURES Figure page 3{1 Left: Figure 3{1a shows a sample input text file showing a graph containing 6 nodes and 10 edges. Right: Figure 3{1b shows the graph corresponding to the input text in 3{1a. The node is numbered in black from n0 to n5 to show how the nodes are arranged. This numbering is not visible during the game. 20 3{2 Top row : The board of the game before the game starts (3{2a). Bottom row : From left to right, the icons for a node (3{2b), the Dweller's icons (3{2c), the Sorcerer's icon (3{2d) and an edge between two nodes (3{2e) . 22 3{3 The Level indicator (highlighted in red) shows the current level. The Round indicator shows which round is currently being played and the total number of rounds in the current level. The play/pause button (highlighted in blue) must be clicked at the start of every game. The close button closes the application. 23 3{4 The first player to join the game, registers the game and takes the role of server. The server tells MasterServer its IP, port and other game information like the game name etc. The second player joins as the client. The MasterServer provides the information given by the server and the second player can join the game. 24 3{5 The figure on the top (3{5a) shows a flow chart of the server side events happening in the game and the figure on the bottom (3{5b) shows the client side version. 25 4{1 Top : The figure on the top row (4{1a) shows the game scene as the Sorcerer player views. Bottom : The figure on the bottom row (4{1b) shows the game scene as the Dweller player views. The player indicator (circled in red and blue respectively) on the top left corner indicates this role. 30 ix 4{2 Top : The figure 4{2a shows the game scene after the Dweller has made the second move. The Round indicator (bottom left) shows that the current round is the last round : 3.
Load more

Recommended publications
  • ACM Bytecast Episode Title: Luis Von Ahn
    Podcast Title: ACM Bytecast Episode Title: Luis Von Ahn Welcome to the ACM Bytecast podcast, where researchers, practitioners, and innovators share about their experiences, lessons, and future visions in the field of computing research. In this episode, host Rashmi Mohan welcomes Luis Von Ahn—founder of Duolingo, the most popular foreign language learning app. The conversation starts off with a quick look at Luis’s background, what he does, and what drew him into this field as a whole. Luis’s mother began his interest in computers at 8 years old and he’s never looked back since. While he started off his training in the field of computer science, he has now started 3 businesses, one of which is Duolingo. Rashmi taps into the history on Luis’s first two businesses before jumping into Duolingo. Learn about the creation of CAPTCHA and re-CAPTCHA. While one of these is a challenge-response test to help computers determine whether the user on websites was human or not, the other protects website from spam. The cru- cial foundation for Luis’s businesses were simply real world problems that he sought to help fix. Luis integrated these real issues in the industry and worked on them from the academic world. Being used across countless websites today, Luis’s work proved pivotal. Rashmi asks Luis about his perspective on integrating academia and business more—don’t miss out on his thoughts! Rashmi shifts the conversation to learning the details involved in the transition from academia to actually running a business and the learning curve associated with this.
    [Show full text]
  • Luis Von Ahn - Episode 14 Transcript
    ACM ByteCast Luis von Ahn - Episode 14 Transcript Rashmi Mohan: This is ACM ByteCast, a podcast series from the Association for Computing Machinery, the world's largest educational and scientific computing society. We talk to researchers, practitioners, and innovators who are at the intersection of computing research and practice. They share their experiences, the lessons they've learned, and their own visions for the future of computing. I am your host, Rashmi Mohan. Rashmi Mohan: If you want to boost your brain power, improve your memory, or enhance your multitasking skills, then you're often recommended to learn a foreign language. For many of us, that option has become a reality, thanks to our next guest and his creation. Luis von Ahn is a serial entrepreneur and Founder and CEO of Duolingo. An accomplished researcher and consulting professor of Computer Science at Carnegie Mellon University, he straddles both worlds seamlessly. He's a winner of numerous awards, including the prestigious Lemelson-MIT Prize and the MacArthur Fellowship often known as The Genius Grant. Louis, welcome to ACM ByteCast. Luis von Ahn: Thank you. Thank you for having me. Rashmi Mohan: Wonderful. I'd love to lead with a simple question that I ask all of my guests. If you could please introduce yourself and talk about what you currently do, and also give us some insight into what drew you into the field of computer science. Luis von Ahn: Sure. So my name is Luis. I am currently the CEO and co-founder of a company called Duolingo. Duolingo is a language learning platform.
    [Show full text]
  • The Future of the Internet and How to Stop It the Harvard Community Has
    The Future of the Internet and How to Stop It The Harvard community has made this article openly available. Please share how this access benefits you. Your story matters. Jonathan L. Zittrain, The Future of the Internet -- And How to Citation Stop It (Yale University Press & Penguin UK 2008). Published Version http://futureoftheinternet.org/ Accessed July 1, 2016 4:22:42 AM EDT Citable Link http://nrs.harvard.edu/urn-3:HUL.InstRepos:4455262 This article was downloaded from Harvard University's DASH Terms of Use repository, and is made available under the terms and conditions applicable to Other Posted Material, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms- of-use#LAA (Article begins on next page) YD8852.i-x 1/20/09 1:59 PM Page i The Future of the Internet— And How to Stop It YD8852.i-x 1/20/09 1:59 PM Page ii YD8852.i-x 1/20/09 1:59 PM Page iii The Future of the Internet And How to Stop It Jonathan Zittrain With a New Foreword by Lawrence Lessig and a New Preface by the Author Yale University Press New Haven & London YD8852.i-x 1/20/09 1:59 PM Page iv A Caravan book. For more information, visit www.caravanbooks.org. The cover was designed by Ivo van der Ent, based on his winning entry of an open competition at www.worth1000.com. Copyright © 2008 by Jonathan Zittrain. All rights reserved. Preface to the Paperback Edition copyright © Jonathan Zittrain 2008. Subject to the exception immediately following, this book may not be reproduced, in whole or in part, including illustrations, in any form (beyond that copying permitted by Sections 107 and 108 of the U.S.
    [Show full text]
  • Crowdsourcing
    Crowdsourcing reCAPTCHA Completely Automated Public Turing test to tell Computers and Humans Apart Luis von Ahn • Guatemalan entrepreneur • Consulting Professor at Carnegie Mellon University in Pittsburgh, Pennsylvania. • Known as one of the pioneers of crowdsourcing. The problem: "Anybody can write a program to sign up for millions of accounts, and the idea was to prevent that" Luis von Ahn Ealier CAPTCHAs 2010: Luis invents CAPTCHA Business model B2B/B2C: The Captcha company sells captchas for around 30 $ per 1000 of them The idea Situation before 2007: CAPTCHAs were many and working well The thought of Luis: • Hundreds of thousands of combined human hours were being wasted each day, 200 million captchas were solved daily • Book digitalisation: at the tim Optical Character Recognition (OCR) software couln’t solve 30 % of the ammount of words to be digitalized • A CAPTCHA could be used with the intention of exploiting that to digitalize old books and articles reCAPTCHAs 2007: reCAPTCHA is found and a partnership is established to digitized the previous 20 years of New York ? Times issues within a few months, 13 million articles RESCUED crowdsourcing CARPATHIA ICEBERG reCAPTCHAs In 2009, reCAPTCHA was purchased by Google for an undisclosed amount for Google Books library, which is now one of the largest digital libraries in the world, or identify street names and addresses from Google Maps Street View. If you are not paying for the product, you are the product. Before and after reCAPTCHA : The ESP game and duoligo First of von Ahn projects: giving a name After CAPTCHA: Duoligo to an image: 10 M people playing Providing translations for the web through bought by Google Images a free language learning program.
    [Show full text]
  • The Future of the Internet and How to Stop It the Harvard Community Has
    The Future of the Internet and How to Stop It The Harvard community has made this article openly available. Please share how this access benefits you. Your story matters. Citation Jonathan L. Zittrain, The Future of the Internet -- And How to Stop It (Yale University Press & Penguin UK 2008). Published Version http://futureoftheinternet.org/ Accessed February 18, 2015 9:54:33 PM EST Citable Link http://nrs.harvard.edu/urn-3:HUL.InstRepos:4455262 Terms of Use This article was downloaded from Harvard University's DASH repository, and is made available under the terms and conditions applicable to Other Posted Material, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms- of-use#LAA (Article begins on next page) YD8852.i-x 1/20/09 1:59 PM Page i The Future of the Internet— And How to Stop It YD8852.i-x 1/20/09 1:59 PM Page ii YD8852.i-x 1/20/09 1:59 PM Page iii The Future of the Internet And How to Stop It Jonathan Zittrain With a New Foreword by Lawrence Lessig and a New Preface by the Author Yale University Press New Haven & London YD8852.i-x 1/20/09 1:59 PM Page iv A Caravan book. For more information, visit www.caravanbooks.org. The cover was designed by Ivo van der Ent, based on his winning entry of an open competition at www.worth1000.com. Copyright © 2008 by Jonathan Zittrain. All rights reserved. Preface to the Paperback Edition copyright © Jonathan Zittrain 2008. Subject to the exception immediately following, this book may not be reproduced, in whole or in part, including illustrations, in any form (beyond that copying permitted by Sections 107 and 108 of the U.S.
    [Show full text]
  • Luis Von Ahn
    Luis von Ahn Professional 2011-present A. Nico Habermann Associate Professor. Computer Science Department, Employment Carnegie Mellon University. 2009-present Staff Research Scientist. Google, Inc. 2006-2011 Assistant Professor. Computer Science Department, Carnegie Mellon University. 2008-2009 Founder and CEO. ReCAPTCHA, Inc. (acquired by Google, Inc., in 2009). 2005-2006 Post-Doctoral Fellow. Computer Science Department, Carnegie Mellon University. Education Carnegie Mellon University, Pittsburgh, PA. Ph.D. in Computer Science, 2005. Advisor: Manuel Blum Thesis Title: Human Computation Carnegie Mellon University, Pittsburgh, PA. M.S. in Computer Science, 2003. Duke University, Durham, NC. B.S. in Mathematics (Summa Cum Laude), 2000. Research I am working to develop a new area of computer science that I call Human Computation. In Interests particular, I build systems that combine the intelligence of humans and computers to solve large-scale problems that neither can solve alone. An example of my work is reCAPTCHA, in which over 750 million people—more than 10% of humanity—have helped digitize books and newspapers. Selected MacArthur Fellow, 2006-2011. Honors Packard Fellow, 2009-2014. Discover Magazine: 50 Best Brains in Science, 2008. Fast Company: 100 Most Creative People in Business, 2010. Silicon.com: 50 Most Influential People in Technology, 2007. Microsoft New Faculty Fellow, 2007. Sloan Fellow, 2009. CAREER Award, National Science Foundation, 2011-2015. Smithsonian Magazine: America’s Top Young Innovators in the Arts and Sciences, 2007. Technology Review’s TR35: Young Innovators Under 35, 2007. IEEE Intelligent Systems “Ten to Watch for the Future of AI,” 2008. Popular Science Magazine Brilliant 10 Scientists of 2006. Herbert A.
    [Show full text]
  • Invited Talk: Human Computation Luis Von Ahn Carnegie Mellon University Pittsburgh, PA USA [email protected]
    Invited Talk: Human Computation Luis von Ahn Carnegie Mellon University Pittsburgh, PA USA [email protected] ABSTRACT algorithm—it must be proven correct, its efficiency can be Tasks like image recognition are trivial for humans, but analyzed, a more efficient version can supersede a less effi- continue to challenge even the most sophisticated computer cient one, and so on. Instead of using a silicon processor, programs. This talk discusses a paradigm for utilizing hu- these “algorithms” run on a processor consisting of ordi- man processing power to solve problems that computers nary humans interacting with computers over the Internet. cannot yet solve. Traditional approaches to solving such “Games with a purpose” have a vast range of applications problems focus on improving software. I advocate a novel in areas as diverse as security, computer vision, Internet approach: constructively channel human brainpower using accessibility, adult content filtering, and Internet search. computer games. For example, the ESP Game, described in Two such games under development at Carnegie Mellon this talk, is an enjoyable online game – many people play University, the ESP Game and Peekaboom, demonstrate over 40 hours a week – and when people play, they help how humans, as they play, can solve problems that com- label images on the Web with descriptive keywords. These puters can’t yet solve. keywords can be used to significantly improve the accuracy of image search. People play the game not because they LABELING RANDOM IMAGES want to help, but because they enjoy it. Several important online applications such as search en- gines and accessibility programs for the visually impaired Categories and Subject Descriptors require accurate image descriptions.
    [Show full text]
  • Jonathan Zittrain's “The Future of the Internet: and How to Stop
    The Future of the Internet and How to Stop It The Harvard community has made this article openly available. Please share how this access benefits you. Your story matters Citation Jonathan L. Zittrain, The Future of the Internet -- And How to Stop It (Yale University Press & Penguin UK 2008). Published Version http://futureoftheinternet.org/ Citable link http://nrs.harvard.edu/urn-3:HUL.InstRepos:4455262 Terms of Use This article was downloaded from Harvard University’s DASH repository, and is made available under the terms and conditions applicable to Other Posted Material, as set forth at http:// nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of- use#LAA YD8852.i-x 1/20/09 1:59 PM Page i The Future of the Internet— And How to Stop It YD8852.i-x 1/20/09 1:59 PM Page ii YD8852.i-x 1/20/09 1:59 PM Page iii The Future of the Internet And How to Stop It Jonathan Zittrain With a New Foreword by Lawrence Lessig and a New Preface by the Author Yale University Press New Haven & London YD8852.i-x 1/20/09 1:59 PM Page iv A Caravan book. For more information, visit www.caravanbooks.org. The cover was designed by Ivo van der Ent, based on his winning entry of an open competition at www.worth1000.com. Copyright © 2008 by Jonathan Zittrain. All rights reserved. Preface to the Paperback Edition copyright © Jonathan Zittrain 2008. Subject to the exception immediately following, this book may not be reproduced, in whole or in part, including illustrations, in any form (beyond that copying permitted by Sections 107 and 108 of the U.S.
    [Show full text]
  • Crowdsourcing
    Crowdsourcing CSCI 470: Web Science • Keith Vertanen Overview • Crowdsourcing = Crowd + Outsourcing – Incented cooperaon • Paid tasks • Compeons – Forced cooperaon – Volunteer cooperaon 2 Paid crowdsourcing 3 Amazon Mechanical Turk • Human Intelligence Task (HIT) – Workers and requestors – Web-based • HTML + JavaScript if hosted en6rely on MTurk – Price per HIT – # of workers per HIT – Qualificaons for workers – Accept/reject work hVp://www.behind-the-enemy-lines.com/2010/03/new- demographics-of-mechanical-turk.html hVp://waxy.org/2008/11/the_faces_of_mechanical_turk/ 4 Specialty paid markets 5 Crowdsourcing for prizes • 2009 DARPA network challenge – Defense Advanced Research Projects Agency – 40th anniversary of the Internet – $40,000 first team to locate • 10 moored, 8 foot, red, weather balloons • 10 previously undisclosed locaons – 4,000 teams competed 6 7 MIT team’s strategy • Mul6-level marke6ng – $2000: whoever sends correct coordinates – $1000: whoever invited them – $500: whoever invited person who invited them – $250: … • Mobilizing people requires right incen6ve • Georgia Tech – Promised to donate proceeds to charity – 2nd place hVp://www.youtube.com/watch?v=6Ga_EJWLzHA 8 NelliX prize • $1M prize • Predict rangs given past rangs – Goal: 10% improvement over NelliX's algorithm – Started Oct. 2006, won in Sept. 2009 • Data: – Training: 100M rangs, 480K users, 18K movies • user, movie, date of grade, grade – Quiz set (1.4M), Test set (1.4M) – BellKor's Pragmac Chaos • 10.06% improvement 9 Forced crowdsourcing • CAPTCHA – Completely
    [Show full text]
  • Blum Transcript Final with Timestamps
    A. M. Turing Award Oral History Interview with Manuel Blum by Ann Gibbons Pittsburgh, Pennsylvania Oct. 26, 2017 Gibbons: I’m Ann Gibbons. This is Manuel Blum, and I’m interviewing him in his home in Pittsburgh near Carnegie Mellon University. Today is Thursday, the 26th of October, 2017. So Manuel, we’re going to start with your childhood, your bacKground … get some information about your family, your beginnings. Tell me where you were born, where you grew up, and a little bit about your family. Blum: Okay, good. I was born in Caracas, Venezuela. My parents were from Romania. They spoke Romanian in the schools, they spoke German at home, and my first language actually was German, even though I was in Venezuela where people speak Spanish. It’s very fortunate that they got to Venezuela. They tried to get into the US but couldn’t. It was hard to get a visa. They didn’t have much money and the Sephardic Jews in Venezuela put up the money for the Ashkenazi Jews to come in. That’s how they were able to get into Venezuela. Gibbons: Had they faced persecution, or did they just see the writing on the wall in Europe? Why did they leave then? Blum: I think they left because they were hungry. They just didn’t have enough food to eat. My father really wanted to have an education, but he was taken out of school in the sixth grade because they needed him to work. This was pretty sad since he wanted to be a doctor.
    [Show full text]
  • Captchas with a Purpose
    Human Computation AAAI Technical Report WS-12-08 CAPTCHAs with a Purpose Suhas Aggarwal [email protected] Abstract 1.1 Applications CAPTCHAs are used to prevent automated software from In this paper, we develop some new Captchas belong- performing actions which degrade the quality of service of a ing to genre — “CAPTCHAs with a purpose.” These given system, whether due to abuse or resource expenditure. CAPTCHAs apart from having its applications serve CAPTCHAs can be deployed to protect systems vulnera- some useful purpose. reCAPTCHA is one such Captcha developed at Carnegie Mellon University. It helps to ble to e-mail spam, such as the webmail services of Gmail, digitize books. Another such Captcha is Asirra de- Hotmail, and Yahoo! Mail. CAPTCHAs found active use veloped at Microsoft which provides homes for home- in stopping automated posting to blogs, forums and wikis, less animals. In this paper, we present Time based, whether as a result of commercial promotion, or harassment Sentence based, Human Emotion based CAPTCHAs and vandalism. CAPTCHAs also serve an important func- which have range of other useful purpose such as mea- tion in rate limiting, as automated usage of a service might suring reaction time of people, promoting news, gen- be desirable until such usage is done in excess, and to the eral knowledge facts, jokes among people while engag- detriment of human users. In such a case, a CAPTCHA can ing in routine activities such as checking email. Also, enforce automated usage policies as set by the administrator one can be used for conducting online polls on a very when certain usage metrics exceed a given threshold.
    [Show full text]
  • Upper and Lower Bounds on Black-Box Steganography Extended Abstract
    Upper and Lower Bounds on Black-Box Steganography Extended Abstract Nenad Dedi´c, Gene Itkis, Leonid Reyzin, and Scott Russell Boston University Computer Science 111 Cummington St. Boston MA 02215 USA fnenad,itkis,reyzin,[email protected] Abstract. We study the limitations of steganography when the sender is not using any properties of the underlying channel beyond its entropy and the ability to sample from it. On the negative side, we show that the number of samples the sender must obtain from the channel is exponen- tial in the rate of the stegosystem. On the positive side, we present the first secret-key stegosystem that essentially matches this lower bound regardless of the entropy of the underlying channel. Furthermore, for high-entropy channels, we present the first secret-key stegosystem that matches this lower bound statelessly (i.e., without requiring synchronized state between sender and receiver). 1 Introduction Steganography's goal is to conceal the presence of a secret message within an innocuous-looking communication. In other words, steganography consists of hiding a secret hiddentext message within a public covertext to obtain a stegotext in such a way that any observer (except, of course, the intended recipient) is unable to distinguish between a covertext with a hiddentext and one without. The first rigorous complexity-theoretic formulation of secret-key steganogra- phy was provided by Hopper, Langford and von Ahn [HLvA02]. In this formu- lation, steganographic secrecy of a stegosystem is defined as the inability of a polynomial-time adversary to distinguish between observed distributions of un- altered covertexts and stegotexts.
    [Show full text]