Cited by 9Spam and Phishing DetectionWeb Application Security VulnerabilitiesAdvanced Malware Detection Techniques

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Eyes of a Human, Eyes of a Program: Leveraging Different Views of the Web for Analysis and Detection

Corbetta, Jacopo, Invernizzi, Luca, Kruegel, Christopher, Vigna, Giovanni·2014·Lecture Notes in Computer Science

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Crossref · 10.1007/978-3-319-11379-1_7

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  • The study carried out by J.Corbetta et al. [2014] has demonstrated visual logo spoofing, with manipulated 'seal images', which fool the users but are otherwise seen as non-malicious content to a security system monitoring the web platform.

    “The study carried out by J.Corbetta et al. [2014] has demonstrated visual logo spoofing, with manipulated 'seal images', which fool the users but are otherwise seen as non-malicious content to a security system monitoring the web platform.”

Citations

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Research works printed but not linked: 38

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  3. Bate, R., Jin, G., Mathur, A.: In Whom We Trust: The Role of Certification Agencies in Online Drug Markets. NBER working paper 17955 (2012) · DOI
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  6. Cova, M., Kruegel, C., Vigna, G.: Detection and Analysis of Drive-by-download Attacks and Malicious JavaScript code. In: Proceedings of the World Wide Web Conference, WWW (2010) · DOI · Paper page
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  8. Fumera, G., Pillai, I., Roli, F.: Spam Filtering Based on the Analysis of Text Information Embedded into Images. The Journal of Machine Learning Research 7, 2699–2720 (2006)
  9. Garera, S., Provos, N., Chew, M., Rubin, A.D.: A Framework for Detection and Measurement of Phishing Attacks. In: Proceedings of the ACM Workshop on Recurring Malcode, WORM (2007) · DOI
  10. Hara, M., Yamada, A., Miyake, Y.: Visual Similarity-Based Phishing Detection without Victim Site Information. In: Proceedings of the IEEE Symposium on Computational Intelligence in Cyber Security (CICS), pp. 30–36. IEEE (March 2009) · DOI
  11. Invernizzi, L., Benvenuti, S., Comparetti, P.M., Cova, M., Kruegel, C., Vigna, G.: EVILSEED: A Guided Approach to Finding Malicious Web Pages. In: Proceedings of the IEEE Symposium on Security and Privacy, S&P (2012) · DOI
  12. Invernizzi, L., Miskovic, S., Torres, R., Saha, S., Lee, S.J., Mellia, M., Kruegel, C., Vigna, G.: Nazca: Detecting Malware Distribution in Large-Scale Networks. In: Proceedings of the Network and Distributed System Security Symposium, NDSS (2014) · DOI
  13. Kapravelos, A., Shoshitaishvili, Y., Cova, M., Kruegel, C., Vigna, G.: Revolver: An Automated Approach to the Detection of Evasive Web-based Malware. In: Proceedings of the USENIX Security Symposium (2013)
  14. Kirda, E., Kruegel, C.: Protecting Users Against Phishing Attacks with AntiPhish. In: Proceedings of the International Conference on Computer Software and Applications (COMPSAC), vol. 1, pp. 517–524. IEEE (2005) · DOI
  15. Lee, S., Kim, J.: WarningBird: Detecting Suspicious URLs in Twitter Stream. In: Proceedings of the Network and Distributed System Security Symposium, NDSS (2010)
  16. Li, Z., Alrwais, S., Xie, Y., Yu, F., Wang, X.: Finding the Linchpins of the Dark Web: A Study on Topologically Dedicated Hosts on Malicious Web Infrastructures. In: Proceedings of the IEEE Symposium on Security and Privacy (S&P), pp. 112–126 (May 2013)
  17. Lin, E., Greenberg, S., Trotter, E., Ma, D., Aycock, J.: Does Domain Highlighting Help People Identify Phishing Sites? In: Proceedings of the Conference on Human Factors in Computing Systems (CHI), p. 2075. ACM Press, New York (2011) · DOI · Paper page
  18. Lu, L., Perdisci, R., Lee, W.: SURF: Detecting and Measuring Search Poisoning Categories. In: Proceedings of the ACM Conference on Computer and Communications Security, CCS (2011) · DOI
  19. Jung, J., Milito, R.A., Paxson, V.: On the Effectiveness of Techniques to Detect Phishing Sites. In: Hämmerli, B.M., Sommer, R. (eds.) DIMVA 2007. LNCS, vol. 4579, pp. 20–39. Springer, Heidelberg (2007) · DOI
  20. Mcgrath, D.K., Gupta, M.: Behind Phishing: An Examination of Phisher Modi Operandi. In: Proceedings of the USENIX Workshop on Large-Scale Exploits and Emergent Threats, LEET (2008)
  21. Medvet, E., Kirda, E., Kruegel, C.: Visual-Similarity-Based Phishing Detection. In: Proceedings of the International Conference on Security and Privacy in Communication Networks (SecureComm), p. 1. ACM Press, New York (2008) · DOI
  22. Neupane, A., Saxena, N., Kuruvilla, K., Georgescu, M., Kana, R.: Neural Signatures of User-Centered Security: An fMRI Study of Phishing, and Malware Warnings. In: Proceedings of the Network and Distributed System Security Symposium (NDSS). pp. 1–16 (2014) · DOI · Paper page
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  25. Rosiello, A.P.E., Kirda, E., Kruegel, C., Ferrandi, F.: A Layout-Similarity-Based Approach for Detecting Phishing Pages. In: Proceedings of the International Conference on Security and Privacy in Communication Networks, SecureComm (2007) · DOI
  26. Ruzzo, W., Tompa, M.: A Linear Time Algorithm for Finding All Maximal Scoring Subsequences. In: Proceedings of the Seventh International Conference on Intelligent Systems for Molecular Biology. AAAI (1999)
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  30. Sheng, S., Wardman, B., Warner, G., Cranor, L.F., Hong, J.: An Empirical Analysis of Phishing Blacklists. In: Proceedings of the Conference on Email and Anti-Spam, CEAS (2009)
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  33. Wang, D.Y., Savage, S., Voelker, G.M.: Cloak and Dagger: Dynamics of Web Search Cloaking. In: Proceedings of the ACM Conference on Computer and Communications Security (CCS), pp. 477–489 (2011) · DOI
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  37. Zauner, C.: Implementation and Benchmarking of Perceptual Image Hash Functions. Master’s thesis, Upper Austria University of Applied Sciences, Hagenberg Campus (2010)
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Metadata

Authors
Corbetta, J., Invernizzi, L., Kruegel, C., & Vigna, G.
Affiliations
University of California, Santa Barbara (US)
Venue
Lecture Notes in Computer Science
Published
2014
Pages
130-149
ISSN
  • 0302-9743 (ISSN-L)
  • 1611-3349
OpenAlex
W172763728
Cited by
9
References
0
Citations by year
2024: 2 · 2023: 1 · 2019: 1 · 2018: 1 · 2017: 2 · 2016: 1 · 2015: 1
FWCI
1.39
Type
conference paper
Language
en
Open access
closed
Locations
Lecture notes in computer science (publishedVersion)
Topics
  • Physical Sciences › Computer Science › Information Systems › Spam and Phishing Detection
  • Physical Sciences › Computer Science › Information Systems › Web Application Security Vulnerabilities
  • Physical Sciences › Computer Science › Software › Advanced Malware Detection Techniques
Keywords
JavaScript obfuscation, malware detection, malicious web pages, heuristic detection, website analysis

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