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1H2020 FINSEC – DIGITAL FINANCE ACADEMY FOR SECURITY
Consorzio Interuniversitario Nazionale per l'Informatica (CINI) & INNOV-ACTS, Limited
E-mail: cini@finsec-project.eu , info@innov-acts.com
H2020 FINSEC Project
The FINSEC project is co-funded from the European Union’s Horizon 2020 programme under grant Agreement No
786727
FINSTIX: A Security Data Model for the
Financial Sector
15/04/2020
2H2020 FINSEC – DIGITAL FINANCE ACADEMY FOR SECURITY
Objectives
▪ Learn about the security knowledge base model
▪ Understand how STIX was extended to serve the needs of the
FINSEC project
Topic
▪ Understand what a knowledge base is
▪ Learn about the different types of knowledge bases
▪ Understand the basics of Cyber Threat Intelligence
▪ Discover the relevance of Structured Threat Information
eXpression (STIX)
Goal
Existing
solutions - STIX
The FINSTIX
solution
3H2020 FINSEC – DIGITAL FINANCE ACADEMY FOR SECURITY
Introduction
▪ Cybersecurity incidents against financial institutions is growing
▪ Benefits
- growing sophistication of recent technological innovations
- complex processes
- multiple organizations
- services are becoming more digitized and interconnected
▪ Need for financial institutions
- Increase their robustness
- Develop integrated approaches for addressing physical and cyber attack
FINSEC project: Integrated Framework for Predictive and Collaborative Security of Financial
Sector
4H2020 FINSEC – DIGITAL FINANCE ACADEMY FOR SECURITY
Existing
solutions
5H2020 FINSEC – DIGITAL FINANCE ACADEMY FOR SECURITY
Cyber Threat Intelligence
Holistic approach to the automated sharing of threat intelligence
Considered one of the most promising strategies in the cyber-security topic
Propose a classification and distinction among existing threat intelligence types
Summarize and compare the most prevalent information-sharing models
Structured Threat Information Expression (STIX) the most commonly used CTI
standard
6H2020 FINSEC – DIGITAL FINANCE ACADEMY FOR SECURITY
Structured Threat Information eXpression (STIX)
▪ STIX:
▪ Provides a modular format that can also efficiently incorporate other standards
▪ Adopted in different contexts of different nature
▪ STIX has been designed with a focus on four different use cases that
include:
▪ Analyzing Cyber Threats
▪ Specifying Indicator Patterns for Cyber Threats
▪ Managing Cyber Threat Response Activities
▪ Sharing Cyber Threat Information
7H2020 FINSEC – DIGITAL FINANCE ACADEMY FOR SECURITY
Structured Threat Information eXpression (STIX) (cont.)
Limitations of STIX:
▪very complex to implement
▪lacks support to reasoning
FINSTIX
▪includes both cyber and physical security threats
▪enables the description of organization assets
▪accounts for how they are inter-connected
8H2020 FINSEC – DIGITAL FINANCE ACADEMY FOR SECURITY
STIX Domain Objects
9H2020 FINSEC – DIGITAL FINANCE ACADEMY FOR SECURITY
STIX Domain Objects (cont.)
10H2020 FINSEC – DIGITAL FINANCE ACADEMY FOR SECURITY
STIX Relationship Objects
11H2020 FINSEC – DIGITAL FINANCE ACADEMY FOR SECURITY
The Knowledge Base (1)
▪ Definition: Technology is used to collect, organize, share and retrieve complex
structured and unstructured information representing facts and assertions about
the world.
▪ Difference from a simple database:
▪ Does not consist only of tables with numbers, strings, dates, etc.
▪ Contains objects with pointers to other objects that, in turn, have additional pointers
▪ Two major types of knowledge bases:
▪ human-readable : knowledge base enables the users to access and use the knowledge
▪ machine readable
12H2020 FINSEC – DIGITAL FINANCE ACADEMY FOR SECURITY
The Knowledge Base (2)
▪Two major types of knowledge bases:
▪ Human-readable :
▪ knowledge base enables the users to access and use the knowledge
▪ consist of documents, manuals, troubleshooting information, and
frequently answered questions
▪ interactive and can lead the users to the solutions to their problems, relying
on the information provided by expert users to guide the process
▪ Machine-readable :
▪ stores knowledge in system-readable forms
▪ limited in interactivity
13H2020 FINSEC – DIGITAL FINANCE ACADEMY FOR SECURITY
FINSEC Security Knowledge Base (1)
▪Information from different external sources of Cyber Threat
Intelligence is collected
▪Structure of the knowledge base = definition of relationships
between the different assets and of their interactions as part of the
critical
▪Definitions enable identification and registration of known attack
patterns against the infrastructure
▪Type of knowledge base :
▪mixture of human and machine-readable
14H2020 FINSEC – DIGITAL FINANCE ACADEMY FOR SECURITY
FINSEC Security Knowledge Base (2)
To suit the FINSEC needs, the content of the Security Knowledge
Base satisfies two essential requirements:
1. It should be structured in order to enable automatic processing
2. It should include information on the infrastructure and the
organization assets, for enabling the FINSEC Platform to perform
Cyber and Physical Threat Intelligence
15H2020 FINSEC – DIGITAL FINANCE ACADEMY FOR SECURITY
The
FINSTIX
solution
16H2020 FINSEC – DIGITAL FINANCE ACADEMY FOR SECURITY
The Security Knowledge Base Data Model
▪ To realize a knowledge base, need to design the appropriate data model, which
is the format used to represent the information contained in the knowledge
base
▪ Option #1 :
▪ Define a completely new set of objects coping with the business
requirements of the considered use cases
▪ This approach incorporates the risk of missing other relevant cases
▪ Option #2:
▪ Employ an existing standard (or mix of standards) and then extend is such
that missing components can be added The Edge Tier contains the Actuation
Enabler and a Data Collection module
▪ FINSEC follows option #2
17H2020 FINSEC – DIGITAL FINANCE ACADEMY FOR SECURITY
From STIX to FINSTIX
▪STIX limitations:
▪ it does not provide for an accurate representation of the financial
institution infrastructure
▪ does not envisage physical systems, but it is rather limited to the cyber ones
▪Two possible extensions of STIX:
1. consists in the definition of custom parameters into STIX Domain Objects
already defined by the standard itself
2. consists in the definition of brand-new custom objects.
FINSEC follows both approaches
18H2020 FINSEC – DIGITAL FINANCE ACADEMY FOR SECURITY
FINSTIX Domain Objects (1)
Name Description
Organization Financial organization.
Asset Organizations’ valuable infrastructure. PCs, server rooms, ATMs, applications,
and everything inside an organization that is crucial.
Area of Interest Logical/physical area, for example, an indoor area (server room).
Service A collection of assets forming a publicly exposed service, for example, a web
application.
Probe Object used to support monitoring infrastructure. A Probe usually monitors
one or more areas of interest.
Probe Configuration Data sent to a probe to configure details such as the area under monitoring
or the bit rate of the monitoring process.
Event Information on something happened/happening.
19H2020 FINSEC – DIGITAL FINANCE ACADEMY FOR SECURITY
FINSTIX Domain Objects (2)
Name Description
Collected data A group of observed data collected by the network probe.
Agent Person involved in the events created by the probes.
Risk The calculated risk for a specific asset or service. The upper levels of FINSEC
calculate it in real-time.
Risk Configuration Parameter specification to optimize the risk assessment process. It defines the
triggers and other useful options.
Regulation An object used to depict a regulation violation.
Vulnerability score Rating used to provide a score to a vulnerability.
Cyber-Physical
Threat Intelligence
Data set fed and enriched by threat information as soon as they are gathered
from the probes and processed by the Predictive Analytics module.
20H2020 FINSEC – DIGITAL FINANCE ACADEMY FOR SECURITY
Security Knowledge Base Architecture (1)
▪The SKB Database, which stores the knowledge
▪SKB Engine, which manages the operations on the
database. It exposes REST API to interact with the other
modules
▪The connectors (one for each external source), which
translate the information coming from external threat
intelligence sources into the data model to promote
homogeneity and integrity among the FINSEC services
21H2020 FINSEC – DIGITAL FINANCE ACADEMY FOR SECURITY
Security Knowledge Base Architecture (2)
22H2020 FINSEC – DIGITAL FINANCE ACADEMY FOR SECURITY
The FINSEC Security Knowledge Base
One of the modules contained in the Data Tier of the FINSEC Reference Architecture
Security Knowledge Base will be to collect information coming from different sources of Cyber Threat
Intelligence
Value of the Security Knowledge Base compared to the existing ones is the definition of the relationships
between different assets and their interactions as part of the critical infrastructures of the financial sector
Service Tier to consume the information contained in the Knowledge Base for producing new Cyber and
Physical Threat Intelligence
Service Tier will feed the Security Knowledge Base with this new information
23H2020 FINSEC – DIGITAL FINANCE ACADEMY FOR SECURITY
Integration with the Dashboard and the Collaborative
Risk Management Module
▪The Collaborative Risk Management module:
▪ Retrieves the vulnerabilities and the related scores affecting the assets that
compose the service;
▪ Calculates the individual asset risk for each asset composing the service,
based on the affecting vulnerabilities, the impact and the threat level for the
asset itself;
▪ Calculates the service risk starting from the assets’ individual risks.
▪ The user (e.g., Security Officer, Member of CERT/CSIRT teams) can see
information on the organization services in the Service page of the Dashboard
24H2020 FINSEC – DIGITAL FINANCE ACADEMY FOR SECURITY
Visualization of the Criticality of vulnerabilities
25H2020 FINSEC – DIGITAL FINANCE ACADEMY FOR SECURITY
Visualization of Vulnerabilities affecting the infrastructure
26H2020 FINSEC – DIGITAL FINANCE ACADEMY FOR SECURITY
The Risk management module
Risk Management module to calculate the risk associated with the
infrastructure services. The Collaborative Risk Management module:
▪Retrieves the vulnerabilities and the related scores affecting the
assets that compose the service;
▪Calculates the individual asset risk for each asset composing the
service, based on the affecting vulnerabilities, the impact and the
threat level for the asset itself;
▪Calculates the service risk starting from the assets’ individual risks.
27H2020 FINSEC – DIGITAL FINANCE ACADEMY FOR SECURITY
Visualization of Risk Associated with the Service

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10 the-finstix-data-model

  • 1. 1H2020 FINSEC – DIGITAL FINANCE ACADEMY FOR SECURITY Consorzio Interuniversitario Nazionale per l'Informatica (CINI) & INNOV-ACTS, Limited E-mail: cini@finsec-project.eu , info@innov-acts.com H2020 FINSEC Project The FINSEC project is co-funded from the European Union’s Horizon 2020 programme under grant Agreement No 786727 FINSTIX: A Security Data Model for the Financial Sector 15/04/2020
  • 2. 2H2020 FINSEC – DIGITAL FINANCE ACADEMY FOR SECURITY Objectives ▪ Learn about the security knowledge base model ▪ Understand how STIX was extended to serve the needs of the FINSEC project Topic ▪ Understand what a knowledge base is ▪ Learn about the different types of knowledge bases ▪ Understand the basics of Cyber Threat Intelligence ▪ Discover the relevance of Structured Threat Information eXpression (STIX) Goal Existing solutions - STIX The FINSTIX solution
  • 3. 3H2020 FINSEC – DIGITAL FINANCE ACADEMY FOR SECURITY Introduction ▪ Cybersecurity incidents against financial institutions is growing ▪ Benefits - growing sophistication of recent technological innovations - complex processes - multiple organizations - services are becoming more digitized and interconnected ▪ Need for financial institutions - Increase their robustness - Develop integrated approaches for addressing physical and cyber attack FINSEC project: Integrated Framework for Predictive and Collaborative Security of Financial Sector
  • 4. 4H2020 FINSEC – DIGITAL FINANCE ACADEMY FOR SECURITY Existing solutions
  • 5. 5H2020 FINSEC – DIGITAL FINANCE ACADEMY FOR SECURITY Cyber Threat Intelligence Holistic approach to the automated sharing of threat intelligence Considered one of the most promising strategies in the cyber-security topic Propose a classification and distinction among existing threat intelligence types Summarize and compare the most prevalent information-sharing models Structured Threat Information Expression (STIX) the most commonly used CTI standard
  • 6. 6H2020 FINSEC – DIGITAL FINANCE ACADEMY FOR SECURITY Structured Threat Information eXpression (STIX) ▪ STIX: ▪ Provides a modular format that can also efficiently incorporate other standards ▪ Adopted in different contexts of different nature ▪ STIX has been designed with a focus on four different use cases that include: ▪ Analyzing Cyber Threats ▪ Specifying Indicator Patterns for Cyber Threats ▪ Managing Cyber Threat Response Activities ▪ Sharing Cyber Threat Information
  • 7. 7H2020 FINSEC – DIGITAL FINANCE ACADEMY FOR SECURITY Structured Threat Information eXpression (STIX) (cont.) Limitations of STIX: ▪very complex to implement ▪lacks support to reasoning FINSTIX ▪includes both cyber and physical security threats ▪enables the description of organization assets ▪accounts for how they are inter-connected
  • 8. 8H2020 FINSEC – DIGITAL FINANCE ACADEMY FOR SECURITY STIX Domain Objects
  • 9. 9H2020 FINSEC – DIGITAL FINANCE ACADEMY FOR SECURITY STIX Domain Objects (cont.)
  • 10. 10H2020 FINSEC – DIGITAL FINANCE ACADEMY FOR SECURITY STIX Relationship Objects
  • 11. 11H2020 FINSEC – DIGITAL FINANCE ACADEMY FOR SECURITY The Knowledge Base (1) ▪ Definition: Technology is used to collect, organize, share and retrieve complex structured and unstructured information representing facts and assertions about the world. ▪ Difference from a simple database: ▪ Does not consist only of tables with numbers, strings, dates, etc. ▪ Contains objects with pointers to other objects that, in turn, have additional pointers ▪ Two major types of knowledge bases: ▪ human-readable : knowledge base enables the users to access and use the knowledge ▪ machine readable
  • 12. 12H2020 FINSEC – DIGITAL FINANCE ACADEMY FOR SECURITY The Knowledge Base (2) ▪Two major types of knowledge bases: ▪ Human-readable : ▪ knowledge base enables the users to access and use the knowledge ▪ consist of documents, manuals, troubleshooting information, and frequently answered questions ▪ interactive and can lead the users to the solutions to their problems, relying on the information provided by expert users to guide the process ▪ Machine-readable : ▪ stores knowledge in system-readable forms ▪ limited in interactivity
  • 13. 13H2020 FINSEC – DIGITAL FINANCE ACADEMY FOR SECURITY FINSEC Security Knowledge Base (1) ▪Information from different external sources of Cyber Threat Intelligence is collected ▪Structure of the knowledge base = definition of relationships between the different assets and of their interactions as part of the critical ▪Definitions enable identification and registration of known attack patterns against the infrastructure ▪Type of knowledge base : ▪mixture of human and machine-readable
  • 14. 14H2020 FINSEC – DIGITAL FINANCE ACADEMY FOR SECURITY FINSEC Security Knowledge Base (2) To suit the FINSEC needs, the content of the Security Knowledge Base satisfies two essential requirements: 1. It should be structured in order to enable automatic processing 2. It should include information on the infrastructure and the organization assets, for enabling the FINSEC Platform to perform Cyber and Physical Threat Intelligence
  • 15. 15H2020 FINSEC – DIGITAL FINANCE ACADEMY FOR SECURITY The FINSTIX solution
  • 16. 16H2020 FINSEC – DIGITAL FINANCE ACADEMY FOR SECURITY The Security Knowledge Base Data Model ▪ To realize a knowledge base, need to design the appropriate data model, which is the format used to represent the information contained in the knowledge base ▪ Option #1 : ▪ Define a completely new set of objects coping with the business requirements of the considered use cases ▪ This approach incorporates the risk of missing other relevant cases ▪ Option #2: ▪ Employ an existing standard (or mix of standards) and then extend is such that missing components can be added The Edge Tier contains the Actuation Enabler and a Data Collection module ▪ FINSEC follows option #2
  • 17. 17H2020 FINSEC – DIGITAL FINANCE ACADEMY FOR SECURITY From STIX to FINSTIX ▪STIX limitations: ▪ it does not provide for an accurate representation of the financial institution infrastructure ▪ does not envisage physical systems, but it is rather limited to the cyber ones ▪Two possible extensions of STIX: 1. consists in the definition of custom parameters into STIX Domain Objects already defined by the standard itself 2. consists in the definition of brand-new custom objects. FINSEC follows both approaches
  • 18. 18H2020 FINSEC – DIGITAL FINANCE ACADEMY FOR SECURITY FINSTIX Domain Objects (1) Name Description Organization Financial organization. Asset Organizations’ valuable infrastructure. PCs, server rooms, ATMs, applications, and everything inside an organization that is crucial. Area of Interest Logical/physical area, for example, an indoor area (server room). Service A collection of assets forming a publicly exposed service, for example, a web application. Probe Object used to support monitoring infrastructure. A Probe usually monitors one or more areas of interest. Probe Configuration Data sent to a probe to configure details such as the area under monitoring or the bit rate of the monitoring process. Event Information on something happened/happening.
  • 19. 19H2020 FINSEC – DIGITAL FINANCE ACADEMY FOR SECURITY FINSTIX Domain Objects (2) Name Description Collected data A group of observed data collected by the network probe. Agent Person involved in the events created by the probes. Risk The calculated risk for a specific asset or service. The upper levels of FINSEC calculate it in real-time. Risk Configuration Parameter specification to optimize the risk assessment process. It defines the triggers and other useful options. Regulation An object used to depict a regulation violation. Vulnerability score Rating used to provide a score to a vulnerability. Cyber-Physical Threat Intelligence Data set fed and enriched by threat information as soon as they are gathered from the probes and processed by the Predictive Analytics module.
  • 20. 20H2020 FINSEC – DIGITAL FINANCE ACADEMY FOR SECURITY Security Knowledge Base Architecture (1) ▪The SKB Database, which stores the knowledge ▪SKB Engine, which manages the operations on the database. It exposes REST API to interact with the other modules ▪The connectors (one for each external source), which translate the information coming from external threat intelligence sources into the data model to promote homogeneity and integrity among the FINSEC services
  • 21. 21H2020 FINSEC – DIGITAL FINANCE ACADEMY FOR SECURITY Security Knowledge Base Architecture (2)
  • 22. 22H2020 FINSEC – DIGITAL FINANCE ACADEMY FOR SECURITY The FINSEC Security Knowledge Base One of the modules contained in the Data Tier of the FINSEC Reference Architecture Security Knowledge Base will be to collect information coming from different sources of Cyber Threat Intelligence Value of the Security Knowledge Base compared to the existing ones is the definition of the relationships between different assets and their interactions as part of the critical infrastructures of the financial sector Service Tier to consume the information contained in the Knowledge Base for producing new Cyber and Physical Threat Intelligence Service Tier will feed the Security Knowledge Base with this new information
  • 23. 23H2020 FINSEC – DIGITAL FINANCE ACADEMY FOR SECURITY Integration with the Dashboard and the Collaborative Risk Management Module ▪The Collaborative Risk Management module: ▪ Retrieves the vulnerabilities and the related scores affecting the assets that compose the service; ▪ Calculates the individual asset risk for each asset composing the service, based on the affecting vulnerabilities, the impact and the threat level for the asset itself; ▪ Calculates the service risk starting from the assets’ individual risks. ▪ The user (e.g., Security Officer, Member of CERT/CSIRT teams) can see information on the organization services in the Service page of the Dashboard
  • 24. 24H2020 FINSEC – DIGITAL FINANCE ACADEMY FOR SECURITY Visualization of the Criticality of vulnerabilities
  • 25. 25H2020 FINSEC – DIGITAL FINANCE ACADEMY FOR SECURITY Visualization of Vulnerabilities affecting the infrastructure
  • 26. 26H2020 FINSEC – DIGITAL FINANCE ACADEMY FOR SECURITY The Risk management module Risk Management module to calculate the risk associated with the infrastructure services. The Collaborative Risk Management module: ▪Retrieves the vulnerabilities and the related scores affecting the assets that compose the service; ▪Calculates the individual asset risk for each asset composing the service, based on the affecting vulnerabilities, the impact and the threat level for the asset itself; ▪Calculates the service risk starting from the assets’ individual risks.
  • 27. 27H2020 FINSEC – DIGITAL FINANCE ACADEMY FOR SECURITY Visualization of Risk Associated with the Service