[go: up one dir, main page]
More Web Proxy on the site http://driver.im/ skip to main content
article

An overview of phishing attacks and their detection techniques

Published: 01 January 2017 Publication History

Abstract

With rapid spread of the internet and cyber space, it has gained numerous applications and has been used as a powerful tool for social collaborations, communications and trades. The internet has superior performance to the traditional ways, as well as many useful features. This has been a reason for its growing usage in online trade and emergence of electronic commerce e-commerce. Security is an essential requirement in electronic interactions. In this context, phishing attacks are among the most important challenges e-commerce is faced with. On the other hand, it is one of the mostly used methods for password stealing. In phishing attacks, the attacker redirects the victim to their fake web pages in order to steal their sensitive information such as passwords. Numerous methods have been devised to defeat such attacks. Web pages, e-mails and URLs used for phishing attacks have some features which can be used to identify fake pages. In this article, we try to introduce different types of phishing attacks and possible detection techniques for them, then discuss about advantages and disadvantages of each technique. Finally, we state that which anti phishing techniques can be used for detection of each phishing types.

References

[1]
Aburrous, M., Hossain, M.A., Dahal, K. and Thabatah, F. (2010a) 'Intelligent phishing detection system for e-banking using fuzzy data mining', Expert Systems with Applications, Vol. 37, No. 12, pp. 7913-7921.
[2]
Aburrous, M., Hossain, M.A., Dahal, K. and Thabtah, F. (2010b) 'Predicting phishing websites using classification mining techniques with experimental case studies', in Proceedings of Seventh International Conference on Information Technology (IEEE), pp. 176-181.
[3]
Agarwal, N., Renfro, S. and Bejar, A. (2009) 'Yahoo Sign-In seal and current anti-phishing solutions', in eCrime Researchers Summit, pp. 1-4.
[4]
Ali, M.M. and Rajamani, L. (2012) 'APD: ARM deceptive phishing detector system phishing detection in instant messengers using data mining approach', Global Trends in Computing and Communication Systems, Vol. 269, pp. 490-502 [online] https://link.springer.com/chapter/10.1007/978-3-642-29219-4_56.
[5]
Alkhateeb, F., Manasrah, A. and Bsoul, A. (2012) 'Bank web sites phishing detection and notification system based on semantic web technologies', International Journal of Security & its Applications, Vol. 6, No. 4, pp. 1-14.
[6]
Almomani, A., Gupta, B.B., Atawneh, S., Meulenberg, A. and Almomani, E. (2013) 'A survey of phishing email filtering techniques', Communications Surveys & Tutorials, Vol. 15, No. 4, pp. 2070-2090.
[7]
Alto, P. (2014) HP Networking Communication: Open SSL Vulnerabilities, pp. 1-4, Hewlett-Packard Development Company (White Paper).
[8]
Bian, K., Park, J.M., Hsiao, M.S., Belanger, F. and Hiller, J. (2009) 'Evaluation of online resources in assisting phishing detection', in Proceedings of Ninth Annual International Symposium on Applications and the Internet (IEEE), pp. 30-36.
[9]
Chawla, M. and Chouhan, S.S. (2014) 'A survey of phishing attack techniques', International Journal of Computer Applications, Vol. 93, No. 3, pp. 32-334.
[10]
Chen, J. and Guo, C. (2006) 'Online detection and prevention of phishing attacks', in Proceedings of First International Conference on Communications and Networking (IEEE), pp. 1-7.
[11]
Dadkhah, M. and Jazi, M.D. (2014a) 'A novel approach to deal with keyloggers', Oriental Journal of Computer Science & Technology, Vol. 7, No. 1, pp. 25-28.
[12]
Dadkhah, M. and Jazi, M.D. (2014b) 'Secure payment in e-commerce: deal with keyloggers and phishings', International Journal of Electronics Communication and Computer Engineering, Vol. 5, No. 3, pp. 656-660.
[13]
Dave, D.B., Ramanathan, V. and Wechsler, H. (2013) 'Phishing detection using traffic behavior, spectral clustering, and random forests', in Proceedings of International Conference on Intelligence and Security Informatics, pp. 67-72.
[14]
Desmedt, Y. (2005) 'Man-in-the-middle attack', in Encyclopedia of Cryptography and Security, pp. 759-759, Springer, USA.
[15]
Dunlop, M., Groat, S. and Shelly, D. (2010) 'Gold phish: using images for content-based phishing analysis', in Proceedings of Fifth International Conference on Internet Monitoring and Protection (IEEE), pp. 123-128.
[16]
Hong, J. (2012) 'The state of phishing attacks', Communications of the ACM, Vol. 55, No. 1, pp. 74-81.
[17]
Kazemian, H.B. and Ahmed, S. (2015) 'Comparisons of machine learning techniques for detecting malicious web pages', Expert Systems with Applications, Vol. 42, No. 3, pp. 1166-1177.
[18]
Khonji, M., Iraqi, Y. and Jones, A. (2013) 'Phishing detection: a literature survey', Communications Surveys & Tutorials, Vol. 15, No. 4, pp. 2091-2121.
[19]
Khonji, M., Jones, A. and Iraqi, Y. (2011) 'A novel phishing classification based on URL features', in Proceedings of GCC Conference and Exhibition (IEEE), pp. 221-224.
[20]
Larose, D. (2014) Discovering Knowledge in Data: An Introduction to Data Mining, Wiley, New York.
[21]
Li, S. and Schmitz, R. (2009) 'A novel anti-phishing framework based on honeypots', in eCrime Researchers Summit (IEEE), pp. 1-13.
[22]
Liao, N., Shengfeng, T. and Tinghua, W. (2009) 'Network forensics based on fuzzy logic and expert system', Computer Communications, Vol. 32, No. 17, pp. 1881-1892.
[23]
Liu, G., Qiu, B. and Wenyin, L. (2010) 'Automatic detection of phishing target from phishing webpage', in Proceedings of International Conference on Pattern Recognition (IEEE), pp. 4153-4156.
[24]
Pradhan, S.K. and Negi, A. (2014) 'An improved approach of dictionary based syntactic PR using trie', in Proceedings of International Conference on Electronic Systems, Signal Processing and Computing Technologies, pp. 386-391.
[25]
Reddy, V.P., Radha, V. and Jindal, M. (2011) 'Client side protection from phishing attack', International Journal of Advanced Engineering Sciences and Technologies, Vol. 3, No. 1, pp. 39-45.
[26]
Ruth, R.K., Priyanka, K., Anusha, K., Jyosthna, C.H. and Siva, P.Y.A. (2011) 'An effective strategy for identifying phishing websites using class-based approach', International Journal of Scientific & Engineering Research, Vol. 2, No. 12, pp. 1-7.
[27]
Sachin, R. (2013) SURL - Tweets and Phishing, E Scan Company [online] http://blog.escanav.com/2013/01/15/surl-tweets-and-phishing/?lang=en (accessed 20 March 2015).
[28]
Sanglerdsinlapachai, N. and Rungsawang, A. (2010) 'Using domain top-page similarity feature in machine learning-based web phishing detection', in Proceedings of Third International Conference on Knowledge Discovery and Data Mining (IEEE), pp. 187-190.
[29]
Shi, J. and Saleem, S. (2012) Phishing, University of Arizona [online] http://www.cs.arizona.edu/~collberg/Teaching/466-566/2012/Resources/presentations/2012/reports.pdf (accessed 20 March 2015).
[30]
Shreeram, V., Suban, M., Shanthi, P. and Manjula, K. (2010) 'Anti-phishing detection of phishing attacks using genetic algorithm', in Proceedings of IEEE International Conference on Communication Control and Computing Technologies (ICCCCT), pp. 447-450.
[31]
Zhuge, J., Holz, T., Song, C., Guo, J., Han, X. and Zou, W. (2009) Managing Information Risk and the Economics of Security, Springer, USA.

Cited By

View all
  1. An overview of phishing attacks and their detection techniques

    Recommendations

    Comments

    Please enable JavaScript to view thecomments powered by Disqus.

    Information & Contributors

    Information

    Published In

    cover image International Journal of Internet Protocol Technology
    International Journal of Internet Protocol Technology  Volume 9, Issue 4
    January 2017
    57 pages
    ISSN:1743-8209
    EISSN:1743-8217
    Issue’s Table of Contents

    Publisher

    Inderscience Publishers

    Geneva 15, Switzerland

    Publication History

    Published: 01 January 2017

    Author Tags

    1. anti-phishing
    2. attack detection
    3. malware
    4. network security
    5. phishing attacks
    6. social engineering

    Qualifiers

    • Article

    Contributors

    Other Metrics

    Bibliometrics & Citations

    Bibliometrics

    Article Metrics

    • Downloads (Last 12 months)0
    • Downloads (Last 6 weeks)0
    Reflects downloads up to 14 Dec 2024

    Other Metrics

    Citations

    Cited By

    View all

    View Options

    View options

    Media

    Figures

    Other

    Tables

    Share

    Share

    Share this Publication link

    Share on social media