Managing application risk has a lot to do with managing data. To mitigate application risks, it is necessary to gather data from heterogeneous and sometimes far-flung sources—data about assets, vulnerabilities, business impact, users, threat intelligence, remediation workflows and more. According to Syed Abdur, Director of Products, Brinqa, without coherent ontology, application security will become both inefficient and deficient.
There are numerous approaches to mitigating application risk. One of them is to manage application risks proactively. This approach can be initiated either as part of a broader cyber risk management program or as a standalone vulnerability management initiative. Consequently, it is possible to identify and triage application risks accurately and prioritize mitigation or remediation efforts towards the most critical ones.
However, all the stages of application risk management—risk assessment and vulnerability identification, risk analysis and prioritization, and risk remediation and mitigation—need mature data management and analytical processes. Primarily, because accomplishing the tasks calls for going beyond the technical asset and vulnerability information reported by the assessment and monitoring tools. For instance, more information in the form of business context and threat intelligence is required. In addition, risk mediation actions must be aligned with the existing IT service management systems and processes.
In sum, there are multiple sources of data and with the addition of another data source; data management becomes a daunting task. Consequently, comprehensive and coherent data ontology is required to ensure that relevant information is at the analyst’s fingertips when needed.
How can ontology help in application risk management? Typically, application risk data ontologies map application risk data points to all the other relevant, connected pieces of information. Furthermore, data correlation and enrichment functions build the relationships between data points in the ontology to highlight contexts necessary for informed decision making. This will help enterprises understand where the threat of vulnerability fits into the overall context of the application—including business context, user access considerations, and threat intelligence and remediation attempts.
Therefore, along with prioritizing vulnerabilities intelligently and tracking remediation continuously building an accurate data ontology, will deliver reliable, consistent improvements in the security posture of applications.
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