US2019268364A1PendingUtilityA1

Auto-tuning security analysis tool configuration via correlation analysis

Assignee: IBMPriority: Sep 20, 2016Filed: May 10, 2019Published: Aug 29, 2019
Est. expirySep 20, 2036(~10.1 yrs left)· nominal 20-yr term from priority
G06F 2221/033H04L 63/1433G06F 11/3696G06F 21/577G06F 11/00G06F 16/285H04L 63/20H04L 63/1425
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Claims

Abstract

A configuration for a security analysis tool is received from a user. The configuration includes two or more configuration items. Each configuration item is a parameter in the configuration of the security analysis tool that has a plurality of possible values. A correlation between the two or more configuration items is determined. The correlation is based on one or more pre-determined empirical correlations.

Claims

exact text as granted — not AI-modified
What is claimed is: 
     
         1 . A computer program product for automatically tuning a configuration of a security analysis tool based on a correlation analysis, the computer program product comprising:
 one or more non-transitory computer readable storage media and program instructions stored on the one or more non-transitory computer readable storage media, the program instructions comprising:   program instructions to receive a configuration from a user for the security analysis tool, wherein:
 the configuration includes two or more configuration items; 
 the security analysis tool is used to analyze an Internet application for security vulnerabilities during development of the Internet application; 
 each configuration item is a parameter, in the configuration of the security analysis tool, that has a plurality of possible values; and 
 each configuration item is selected from the group consisting of case sensitive uniform resource locators (URLs), in-session detection, automatic form fill requirements, parameters and paths being tracked; 
   program instructions to determine a correlation between the two or more configuration items in the received configuration from the user, wherein the correlation between the two or more configuration items is based on one or more pre-determined empirical correlations, wherein:
 the one or more pre-determined empirical correlations are derived from an Apriori algorithm; 
 the Apriori algorithm generates correlations between two or more items of an input database; 
 the input database includes a plurality of configuration items (p) and a plurality of possible values (v) for each of the plurality of configuration items resulting in a database that ranges over all possible values of (p,v); 
 the Apriori algorithm performs a breadth-first search through all possible values of (p,v) that yields a set of association rules for the (p,v) pair combinations; and 
 the breadth-first search is an algorithm for searching graph data structures that starts at a root and explores neighbor nodes before moving to next level neighbors; 
   program instructions to provide an optimized configuration of the two or more configuration items in the received configuration to the user based on the determined correlation between the two or more configuration items in the received configuration;   program instructions to send a query to the user requesting a priority of the two or more configuration items in the received configuration;   program instructions to receive an input from the user indicating the priority of the two or more configuration items in the received configuration; and   program instructions to send a recommendation to the user, wherein the recommendation includes one or more configuration item values for each configuration item of the two or more configuration items based on the pre-determined empirical correlations and the indicated priority of the two or more configuration items.

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