International Business Machines Corporation

Virginia Mayo

Jinho Hwang

Sai Zeng

Muhammed Fatih Bulut

Lisa M Chavez

Vugranam Chakravarthy Sreedhar

Maja Vukovic

Milton H Hernandez

Karin Murthy

Cindy J Mullen

Xinli Wang

A system includes a memory that stores computer executable components and neural network data, and a processor executes computer executable components stored in the memory. An assessment component assesses a computer network, and classifies the computer network relative to M network classifications stored in a repository, wherein M is an integer greater than one. A risk component determines risk of vulnerability subject to change impact regarding protection against a computer virus or cyber-attack based on historical information regarding vulnerability exposure and vulnerability remediation changes relative to the classification of the computer network. A recommendation component that generates recommendations and best action to mitigate risk and impact, and remediate the vulnerabilities based on the risk assessment and business priorities.

Method and system to manage risk of vulnerabilities and corresponding change actions to address malware threats

Techniques that facilitate group patching recommendation and/or remediation with risk assessment are provided. In one example, a system includes a vertical stack component, a horizontal stack component and a risk classification component. The vertical stack component identifies a first patch profile from a software system associated with a computer system environment. The horizontal stack component identifies a second patch profile from a hardware system associated with network nodes of the computer system environment. The system learns over time to identify repetitive patterns using machine learning techniques. Then, the risk classification component performs a machine learning process to determine a risk classification for the computer system environment based on the first patch profile and the second patch profile.

Group patching recommendation and/or remediation with risk assessment

A method and system of identifying technical experts for an identified vulnerability is provided. One or more technical experts for each of one or more categories of the vulnerability are identified. Questions are sent to and answers are received from the one or more identified technical experts for each of the one or more categories of vulnerabilities, via a chatbot module. Answers to parameters that are missing for a Common Vulnerability Scoring System (CVSS) for the identified vulnerability are determined from the received answers to the parameters. The answers to the parameters are validated and a CVSS score is calculated based on the validated determined answers.

Automatically assessing a severity of a vulnerability via social media

Growing community of inventors

Piscataway, NJ, United States of America

Virginia Mayo