摘要(英) |
Phishing is a form of social engineering attack combined with web development techniques. This is one of the important processes on cyber-attacks. Many cyber-attacks start from phishing emails. The early indiscriminate attacks have gradually transformed into "Spear-phishing" in which emails are well-crafted attacks with very specific targets. It’s a highly targeted attack with a small number of mailings. Hackers lock important people and organizations to send emails. The linked text, files, or pictures are included in the email context trick users into clicking phishing websites created by the hackers. To get people to trust the website, the appearance of the website is almost similar to its corresponding legitimate website. It causes users lower the guards and easily give away personal information, such as account numbers, passwords, and bank account information.
"Spear-phishing" is a more targeted form of phishing. There are no mass victims and the sample amount of feedback is not enough. It needs to analyze for quite a while. These type of phishing websites are highly imitative to legitimate websites. Even so, the websites uptime are short, they get blocked to protect users as soon been reported as malicious sites by reporting phishing sites. It is difficult to detect in real time. Therefore, in this paper we propose a method to analyze phishing websites that are almost identical to legitimate websites and have the act of inputting personal information. We use its Page Jumping behavior to achieve "Time-of-Click Analysis". Before sending sensitive information from the webpage, find the final target in advance. Finally, we can determine whether it is a phishing website. |
參考文獻 |
[1] A. Jain and V. Richariya, “Implementing a web browser with phishing detection techniques,” arXiv preprint arXiv:1110.0360, 2011.
[2] Protecting businesses against cyber threats during COVID-19 and beyond [Online]. Available: https://cloud.google.com/blog/products/identity-security/protecting-against-cyber-threats-during-covid-19-and-beyond
[3] Anti-Phishing Working Group (APWG). Phishing Activity Trends Report 2nd Quarter 2021 [Online]. Available: https://apwg.org/trendsreports/
[4] 知已知彼!深入剖析疫情衝擊下的資安威脅及攻擊手法, OSecure 郵件威脅報告 [Online]. Available: https://www.openfind.com.tw/taiwan/edm/report_2021/report_2021.pdf
[5] TinyURL [Online]. Available: https://tinyurl.com/app
[6] 教你分辨釣魚網址分身術!資安人 [Online]. Available: https://www.informationsecurity.com.tw/article/article_detail.aspx?aid=6813
[7] Attackers Take Advantage of New Google Docs Exploit [Online]. Available: https://www.avanan.com/blog/attackers-take-advantage-of-new-google-doc-exploit, 2021.
[8] 銀行釣魚簡訊最新手法!解析台新簡訊詐騙案:一般民眾應如何自保? [Online]. Available: https://www.managertoday.com.tw/articles/view/62632, 2021.
[9] AbdelKarim Mardini and Guemmy Kim, "Making sign-in safer and more convenient, " [Online]. Available: https://blog.google/technology/safety-security/making-sign-safer-and-more-convenient/, SAFETY & SECURITY CHROME, October 05, 2021.
[10] E. Brunswik, "Representative design and probabilistic theory in functional psychology, " Psychol. Rev., vol. 62, pp. 193–217, 1955.
[11] J. W. Payne, J. R. Bettman, and E. J. Johnson, The Adaptive Decision Maker. Cambridge, UK: Cambridge Univ. Press, 1993.
[12] L. Li, E. Berki, M. Helenius, and S. Ovaska, "Towards a contingency approach with whitelist-and blacklist-based anti-phishing applications: what do usability tests indicate? " in Behaviour & Information Technology, vol. 33, no.11, 2014, pp. 1136-1147.
[13] PhishTank | Join the fight against phishing. [Online]. Available: http://www.phishtank.com/
[14] C. Reis, A. Barth, and C. Pizano, "Browser security: lessons from Google Chrome," Queue, vol. 7, p. 3, 2009.
[15] CYREN. "The Phishing Issue From Targeted Attacks to High-Velocity Phishing," CyberThreat Report [Online]. Available: https://evessio.s3.amazonaws.com/customer/8c4659ee-526a-4e9c-89dc-f6f4c3c1a789/event/ipexpo-europe/2018-Exhibitors/cyren-1_Cyren_Phishing.pdf, p. 18, April 2018.
[16] VirusTotal - Home. [Online]. Available: https://www.virustotal.com/gui/home/url/.
[17] URLVoid: Check if a Website is Malicious/Scam or Safe/Legit. [Online]. Available: https://www.urlvoid.com/.
[18] CheckPhish: Url Scanner to Detect Phishing in Real-time. [Online]. Available: https://checkphish.ai/.
[19] Website Traffic - Check and Analyze Any Website | Similarweb. [Online]. Available: https://www.similarweb.com/.
[20] URLVoid 從超過 30 個檢測引擎檢查網頁安全,避免誤入詐欺或惡意連結 [Online]. Available: https://free.com.tw/urlvoid/, 8 October 2019.
[21] Noman Mazher, Imran Ashraf, and Ayesha Altaf, "Which web browser work best for detecting phishing," IEEE, 2013.
[22] C. Almond, "A practical guide to cloud computing security," A white paper from Accenture and Microsoft, 2009.
[23] StatCounter GlobalStats. Browser Market Share Worldwide [Online]. Available: https://gs.statcounter.com/browser-market-share
[24] Amazon.com, "The top 500 sites on the web," [Online]. Available: https://www.alexa.com/topsites, October 2021.
[25] John McGahagan IV, Darshan Bhansali, Darshan Bhansali, and Darshan Bhansali " A Comprehensive Evaluation of Webpage Content Features for Detecting Malicious Websites, " 2019 9th Latin-American Symposium on Dependable Computing (LADC), 19-21 Nov. 2019.
[26] Mozilla Developer Network, “HTTP-Headers,” 2018. [Online]. Available: https://developer.mozilla.org/en-US/docs/Web/HTTP/Headers/.
[27] Python Software Foundation, “Python,” 2018. [Online]. https://www.Python.org/. Available: August 10, 2018.
[28] Selenium 3.141.0. [Online]. https://pypi.org/project/selenium//. Available: August 10, 2018.
[29] Document.write用unescape加载javascript的好处 [Online]. Available: http://www.webkaka.com/tutorial/js/2018/040627/.
[30] Urllib.parse — Parse URLs into components [Online]. Available: https://docs.python.org/3/library/urllib.parse.html.
[31] Beautiful Soup Documentation [Online]. Available: https://beautiful-soup-4.readthedocs.io/en/latest/.
[32] Wikipedia.org, "jQuery" [Online]. Available: https://zh.wikipedia.org/wiki/JQuery.
[33] Huaping Yuan, Xu Chen, Yukun Li, Zhenguo Yang, Wenyin Liu " Detecting Phishing Websites and Targets Based on URLs and Webpage Links, " 2018 24th International Conference on Pattern Recognition (ICPR) Beijing, China, August 20-24, 2018 |