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A Quantitative Evaluation of Trust in the Quality of Cyber Threat Intelligence Sources

Published: 26 August 2019 Publication History

Abstract

Threat intelligence sharing has become a cornerstone of cooperative and collaborative cybersecurity. Sources providing such data have become more widespread in recent years, ranging from public entities (driven by legislatorial changes) to commercial companies and open communities that provide threat intelligence in order to help organisations and individuals to better understand and assess the cyber threat landscape putting their systems at risk. Tool support to automatically process this information is emerging concurrently. It has been observed that the quality of information received by the sources varies significantly and that in order to assess the quality of a threat intelligence source it is not sufficient to only consider qualitative indications of the source itself, but it is necessary to monitor the data provided by the source continuously to be able to draw conclusions about the quality of information provided by a source. In this paper, we propose a methodology for evaluating cyber threat information sources based on quantitative parameters. The methodology aims to facilitate trust establishment to threat intelligence sources, based on a weighted evaluation method that allows each entity to adapt it to its own needs and priorities. The approach facilitates automated tools utilising threat intelligence, since information to be considered can be prioritised based on which source is trusted the most at the time the intelligence arrives.

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Cited By

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  • (2024)You Might Have Known It Earlier: Analyzing the Role of Underground Forums in Threat IntelligenceProceedings of the 27th International Symposium on Research in Attacks, Intrusions and Defenses10.1145/3678890.3678930(368-383)Online publication date: 30-Sep-2024
  • (2024)Sharing Is Caring: Hurdles and Prospects of Open, Crowd-Sourced Cyber Threat IntelligenceIEEE Transactions on Engineering Management10.1109/TEM.2023.3279274(1-20)Online publication date: 2024
  • (2024)A Methodology for Developing & Assessing CTI Quality MetricsIEEE Access10.1109/ACCESS.2024.335110812(6225-6238)Online publication date: 2024
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Published In

cover image ACM Other conferences
ARES '19: Proceedings of the 14th International Conference on Availability, Reliability and Security
August 2019
979 pages
ISBN:9781450371643
DOI:10.1145/3339252
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 the author(s) 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].

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 26 August 2019

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Author Tags

  1. Cooperative and collaborative cybersecurity
  2. cyber threat information sharing
  3. cyber threat intelligence source evaluation
  4. quality parameters
  5. trust indicators

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  • Refereed limited

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ARES '19

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Overall Acceptance Rate 228 of 451 submissions, 51%

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Cited By

View all
  • (2024)You Might Have Known It Earlier: Analyzing the Role of Underground Forums in Threat IntelligenceProceedings of the 27th International Symposium on Research in Attacks, Intrusions and Defenses10.1145/3678890.3678930(368-383)Online publication date: 30-Sep-2024
  • (2024)Sharing Is Caring: Hurdles and Prospects of Open, Crowd-Sourced Cyber Threat IntelligenceIEEE Transactions on Engineering Management10.1109/TEM.2023.3279274(1-20)Online publication date: 2024
  • (2024)A Methodology for Developing & Assessing CTI Quality MetricsIEEE Access10.1109/ACCESS.2024.335110812(6225-6238)Online publication date: 2024
  • (2024)Improving quality of indicators of compromise using STIX graphsComputers & Security10.1016/j.cose.2024.103972144(103972)Online publication date: Sep-2024
  • (2024)Comprehensive Threat Analysis in Additive Manufacturing Supply Chain: A Hybrid Qualitative and Quantitative Risk Assessment FrameworkProduction Engineering10.1007/s11740-024-01283-1Online publication date: 9-May-2024
  • (2023)Dynamic Risk Assessment in Cybersecurity: A Systematic Literature ReviewFuture Internet10.3390/fi1510032415:10(324)Online publication date: 28-Sep-2023
  • (2023)Blockchain-Based Cyber Threat Intelligence Sharing Using Proof-of-Quality ConsensusSecurity and Communication Networks10.1155/2023/33031222023Online publication date: 1-Jan-2023
  • (2023)An Exploratory Study on the Use of Threat Intelligence Sharing Platforms in Germany, Austria and SwitzerlandProceedings of the 18th International Conference on Availability, Reliability and Security10.1145/3600160.3600185(1-7)Online publication date: 29-Aug-2023
  • (2023)Understanding Indicators of Compromise against Cyber-attacks in Industrial Control Systems: A Security PerspectiveACM Transactions on Cyber-Physical Systems10.1145/35872557:2(1-33)Online publication date: 19-Apr-2023
  • (2023)HDA-TIP: A Framework for Heterogeneous Data Aggregation for Threat Intelligence Platform2023 17th International Conference on Ubiquitous Information Management and Communication (IMCOM)10.1109/IMCOM56909.2023.10035604(1-7)Online publication date: 3-Jan-2023
  • Show More Cited By

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