Honey Spam 2 0 Profiling Web Spambot Behaviour

Honey. Spam 2. 0 Profiling Web Spambot Behaviour Pedram Hayati Kevin Chai Vidyasagar Potdar Alex Talevsky Prof. Tharam Dillon Prof. Elizabeth Chang Digital Ecosystem and Business Intelligence Institute (DEBII)

Agenda • Introduction • Background – Taxonomy of Spam 2. 0 and Web Spambot – Current Literature Techniques • Honey. Spam 2. 0 Architecture – Navigation Component – Form Tracking Component – Deploying Honey. Spam 2. 0 • Experimental Results • Related Works • Conclusion and future works 2

Little bit what’s going on? Web 2. 0 Spam 2. 0 3

Web Spambot • A kind of Web Robot or Internet Robot • Distribute Spam content in Web 2. 0 applications • Scope – Application-Specific – Website-Specific 4

Countermeasures Web 2. 0 Submission Workflow • CAPTCHA • Hash. Cash • Form variation • Nonce 1. Decrease user convenience and increase complexity of human computer interaction. 2. As programs become better at deciphering CAPTCHA, the image may become difficult for humans to decipher. 3. As computers get more powerful, they will be able to decipher CAPTCHA better than humans. 5

Honey. Spam 2. 0 • Monitor and Track Web Spambots • Idea of Honeypots • Implicitly Track – – – Click-steam Page navigation Keyboard activity Mouse movement Page Scrolling 6

Honey. Spam 2. 0 Architecture 7

Honey. Spam 2. 0 in Action! % of Origin of Web. Spam Bots % of Content Contribution % of Browser Type 8

Honey. Spam 2. 0 in Action! No. of Posts vs. Date No. of Users vs. Date No. of Online Users vs. Date No. of Spam. Bot vs. Hits 9

Honey. Spam 2. 0 in Action! No. Session vs. Dwell Visit Time No. of Spambots Vs. Return Visits 10

Web Spambot Behaviour • Use of search engines to find target websites • Create numerous user accounts • Low website webpage hits and revisit rates • Distribute spam content in a short period of time • No web form interaction • Generated usernames 11

Conclusion • Honey. Spam 2. 0 as framework to monitor/track Web spambot behaviour • Integrated to popular open source web applications • Web Spambots – – – use search engines to find target websites, create numerous user accounts, distribute spam content in a short amount of time, do not revisit the website, do not interact with forms on the website, and register with randomly generated usernames Future Work: Using of Machine 12

Thank You! debii. curtin. edu. au www. curtin. edu. au asrl. debii. curtin. edu. au www. antispamresearchlab. com Honey. Spam 2. 0 Profiling Web Spambot Behaviour Pedram Hayati, Kevin Chai, Vidyasagar Potdar, Alex Talevsky Homepage: debii. curtin. edu. au/~pedram/ 13