The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.
The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.
Patent No.:
Date of Patent:
Aug. 04, 2026
Filed:
Nov. 25, 2024
Bank of America Corporation, Charlotte, NC (US);
Jason A. Alizzi, York, SC (US);
John Andres Lozes, Wilmington, DE (US);
Chia-Ho Yu, Ashland, VA (US);
Daniel M. Maniotis, Oakland, NJ (US);
Robert Bosi, Rock Hill, SC (US);
Amit Jain, Hockessin, DE (US);
Pravesh K. Misra, Newtown, PA (US);
Kevin Roy Carlson, Elizabeth, CO (US);
Matthew E. Simon, Staten Island, NY (US);
Tamer Badawy, Charlotte, NC (US);
Sreeni R. Nair, Florence, NJ (US);
Dharmendra Kumar Gupta, Mumbai, IN;
Colin Childers, Charlotte, NC (US);
Donna Lee Phillips, Elkton, MD (US);
Richard Michael Foster, Elkton, MD (US);
BANK OF AMERICA CORPORATION, Charlotte, NC (US);
Abstract
Systems, computer program products, and methods are described herein for optimized fingerprinting and tokenization in server drift analysis. The present disclosure is configured to detect configuration drift across entire computer servers by utilizing distributed agents that collect and analyze metadata such as file modification dates, sizes, and cryptographic hashes. These agents sanitize sensitive information and conditionally tokenize environment-specific values, such as server names, IP addresses, and timestamps, to ensure accurate comparison across different servers and time periods. By automating the detection process, the system reduces manual intervention and minimizes resource usage, making it highly scalable for large, multi-server environments. Additionally, the system can group servers based on predefined parameters, compare their configurations, and identify discrepancies that may impact performance or security. The invention improves efficiency, accuracy, and security in server drift detection, making it particularly suited for complex, dynamic infrastructures such as enterprise data centers or cloud environments.