skip to main content
10.1145/3343147.3343154acmotherconferencesArticle/Chapter ViewAbstractPublication PagesieccConference Proceedingsconference-collections
research-article

PhishLedger: A Decentralized Phishing Data Sharing Mechanism

Authors Info & Claims
Published:07 July 2019Publication History

ABSTRACT

In recent years, phishing has become one of the biggest security threats on the Internet. To combat phishing, it requires multiple steps and multi-agency participation and thus desperately need uniform data sharing format and unobstructed sharing channels, which unfortunately is just what is lacking currently. This paper proposes a novel phishing data sharing mechanism based on the consortium blockchain. It designs four types of nodes, including reporting node, accounting node, servicing node and supervising node and illustrates the roles of each type. Then it demonstrates the process of reporting, accounting and servicing and designs the process of post-supervision, which ensures the operation of the mechanism stable and fastest; and then discusses its implementation on Hyperledger Fabric. The proposed mechanism includes multi-source reporting, anti-tamper accounting, multi-channel disposal of phishing data and post-supervision. It provides a platform for multi-party participation, transparent and efficient coordination and unified standard and overcomes the current prominent problems of phishing data sharing; and the participants on the consortium blockchain all have a strong desire to combat phishing, which ensures the proposed mechanism is also very practical and highly feasible.

References

  1. Symantec Corporation.2015. Symantec intelligence report {online}.Available: https://www.symantec.com/content/en/us/enterprise/other_resources/b-intelligence-report-01-2015-en-us.pdfGoogle ScholarGoogle Scholar
  2. Khalid, J., Jalil, R., Khalid, M., Maryam, M., Shafique, M.A. and Rasheed, W. 2019. Anti-phishing models for mobile application development: A review paper. In: Bajwa I., Kamareddine F., Costa A. (eds) Intelligent Technologies and Applications. INTAP 2018. Communications in Computer and Information Science, vol 932. Springer, Singapore.Google ScholarGoogle Scholar
  3. Jeeva, S.C. and Rajsingh, E.B.2016. Intelligent phishing URL detection using association rule mining. Human-centric Computing and Information Sciences, 6, 10. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. APWG. 2018. ICANN's temporary specification survey{online}. Available: https://apwg.org/apwg-news-center/icann-whois-access/temporySpecSurveyGoogle ScholarGoogle Scholar
  5. Abutair, H., Belghith, A. and AlAhmadi, S. J. 2018. CBR-PDS: A case-based reasoning phishing detection system. Journal of Ambient Intelligence and Humanized Computing.Google ScholarGoogle Scholar
  6. Rao, R.S., Pais, A. R. 2018. Detection of phishing websites using an efficient feature-based machine learning framework. Neural Computing and Applications.Google ScholarGoogle Scholar
  7. Heartfield, R. and Loukas, G. 2018. Protection against semantic social engineering attacks. In: Conti, M., Somani, G., Poovendran R. (eds) Versatile Cybersecurity. Advances in Information Security, vol 72. Springer, Cham.Google ScholarGoogle Scholar
  8. IETF. 2010. RFC5901. Extensions to the IODEF-document class for reporting phishing{online}. Available: https://www.rfc-editor.org/rfc/pdfrfc/rfc5901.txt.pdf.Google ScholarGoogle Scholar
  9. IETF. 2010. RFC5941. Sharing transaction fraud data. {online}. Available: https://www.rfc-editor.org/rfc/pdfrfc/rfc5941.txt.pdf.Google ScholarGoogle Scholar
  10. China Telecom Professional Network. 2016. YD/T 3038--2016. Technical requirements for a data exchange protocol for phishing attacks reporting{online}. Available: http://www.bzfxw.com/e/DownSys/DownSoft/?classid=109&id=328542Google ScholarGoogle Scholar
  11. Geersdaele, F.V. 2015. The promise of the blockchain: The trust machine. The Economist. Available online: https://www.economist.com/leaders/2015/10/31/the-trust-machine.Google ScholarGoogle Scholar
  12. Singhal, B., Dhameja, G. and Panda, P.S. 2018. How Blockchain Works. In: Beginning Blockchain. Apress, Berkeley, CA.Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. Esposito, C., Santis, A. D., Tortora, G., Chang, H., and Choo, K. K. R.. 2018. Blockchain: a panacea for healthcare cloud-based data security and privacy? IEEE Cloud Computing, 5, 1.Google ScholarGoogle ScholarCross RefCross Ref
  14. Dorri, A., Steger, M., Kanhere, S. S., and Jurdak, R. 2017. BlockChain: A distributed solution to automotive security and privacy. IEEE Communications Magazine, 55, 12. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. Zhang, A., and Lin, X. 2018. Towards secure and privacy-preserving data sharing in e-health systems via consortium blockchain. Journal of Medical Systems, 42, 8. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. Pathak N. and Bhandari A. 2018. Implementing Blockchain as a Service. In: IoT, AI, and Blockchain for .NET. Apress, Berkeley, CA.Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. The Linux Foundation. 2018. The Linux Foundation helps Hyperledger build the most vibrant open source ecosystem for blockchain{online}. Available: https://www.linuxfoundation.org/projects/case-studies/hyperledger/.Google ScholarGoogle Scholar
  18. Thakkar, P., Nathan, S., and Vishwanathan, B. 2018. Performance benchmarking and optimizing Hyperledger fabric blockchain platform. IEEE 26th International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS).Google ScholarGoogle Scholar
  19. APWG. 2019. Phishing Activity Trends Report 4th Quarter 2018{online}. Available: http://docs.apwg.org/reports/apwg_trends_report_q4_2018.pdf.Google ScholarGoogle Scholar

Index Terms

  1. PhishLedger: A Decentralized Phishing Data Sharing Mechanism

    Recommendations

    Comments

    Login options

    Check if you have access through your login credentials or your institution to get full access on this article.

    Sign in
    • Published in

      cover image ACM Other conferences
      IECC '19: Proceedings of the 1st International Electronics Communication Conference
      July 2019
      163 pages
      ISBN:9781450371773
      DOI:10.1145/3343147

      Copyright © 2019 ACM

      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 7 July 2019

      Permissions

      Request permissions about this article.

      Request Permissions

      Check for updates

      Qualifiers

      • research-article
      • Research
      • Refereed limited

    PDF Format

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader