Accenture Global Solutions Limited (20240250979). AUTOMATED CYBERSECURITY VULNERABILITY PRIORITIZATION simplified abstract

AUTOMATED CYBERSECURITY VULNERABILITY PRIORITIZATION

Organization Name

Accenture Global Solutions Limited

Inventor(s)

Aolin Ding of Piscataway NJ (US)

Hodaya Binyamini of Beer Sheva (IL)

Gal Engelberg of Pardes-hana (IL)

Louis William Divalentin of Arlington VA (US)

Benjamin Glen Mccarty of Washington DC (US)

Dan Klein of Rosh Ha'ayin (IL)

Amin Hass of Arlington VA (US)

AUTOMATED CYBERSECURITY VULNERABILITY PRIORITIZATION - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240250979 titled 'AUTOMATED CYBERSECURITY VULNERABILITY PRIORITIZATION

The patent application describes a computer-implemented method for identifying and mitigating cybersecurity issues in an enterprise network.

• The method involves obtaining data representing observed conditions in the network, each associated with a cybersecurity issue such as a vulnerability or weakness.
• Multiple exploitation prediction models are used to determine the probabilities of exploitation for these cybersecurity issues.
• A priority ranking is assigned to each observed condition based on the probabilities of exploitation.
• Actions are then taken to mitigate the observed conditions in the network based on their priority rankings.

Potential Applications: - This technology can be applied in various industries to enhance cybersecurity measures and protect sensitive data. - It can be used by cybersecurity professionals to proactively identify and address potential vulnerabilities in enterprise networks.

Problems Solved: - Helps in early detection and mitigation of cybersecurity issues before they can be exploited by malicious actors. - Provides a systematic approach to prioritize and address vulnerabilities in enterprise networks.

Benefits: - Enhances the overall security posture of an organization by effectively managing cybersecurity risks. - Improves operational efficiency by automating the process of identifying and mitigating cybersecurity issues.

Commercial Applications: Title: "Enhancing Cybersecurity Measures in Enterprise Networks" This technology has significant commercial potential in industries where data security is paramount, such as finance, healthcare, and government sectors. It can be marketed to cybersecurity firms, IT departments, and organizations looking to strengthen their network security.

Prior Art: Readers interested in exploring prior art related to this technology can start by researching existing cybersecurity risk assessment methodologies, predictive modeling in cybersecurity, and vulnerability management systems.

Frequently Updated Research: Researchers in the field of cybersecurity are constantly developing new techniques and tools to combat evolving cyber threats. Stay updated on the latest advancements in exploitation prediction models and vulnerability management strategies to enhance the effectiveness of this technology.

Questions about Cybersecurity Risk Assessment: 1. How does this technology improve the efficiency of cybersecurity risk assessment processes? - This technology streamlines the identification and prioritization of cybersecurity issues in enterprise networks, enabling organizations to focus on mitigating the most critical vulnerabilities first.

2. What sets this method apart from traditional cybersecurity risk assessment approaches? - Unlike traditional methods that rely on manual assessments and subjective judgments, this method leverages data-driven exploitation prediction models to objectively evaluate the probabilities of cybersecurity issues being exploited.

Original Abstract Submitted

implementations include a computer-implemented method comprising: obtaining data representing observed conditions in an enterprise network, each observed condition being associated with at least one cybersecurity issue, a cybersecurity issue comprising one of (i) a vulnerability comprising an instance of a vulnerable condition or (ii) a weakness that is likely to cause a vulnerability to occur; using a plurality of exploitation prediction models to determine probabilities of exploitation of the cybersecurity issues associated with the observed conditions in the enterprise network, wherein the plurality of exploitation prediction models are trained using a knowledge mesh generated using data from cybersecurity repositories; assigning a priority ranking to each of the observed conditions in the enterprise network based on the respective probabilities of exploitation for the cybersecurity issues associated with the observed conditions; and performing one or more actions to mitigate the observed conditions in the enterprise network based on the priority rankings.