MUMBAI, India, Jan. 2 -- Intellectual Property India has published a patent application (202541123133 A) filed by Malla Reddy (MR) Deemed to be University; Malla Reddy College Of Engineering and Technology; Malla Reddy Engineering College For Womens; Malla Reddy University; Malla Reddy Vishwavidyapeeth; and Dr. P. Raghunadh, Medchal-Malkajgiri, Telangana, on Dec. 6, 2025, for 'context aware cybersecurity framework for remote workforce management.'
Inventor(s) include Dr. P. Raghunadh; Patibandla Anitha; Mr. Rajkumar Pogaku; Dr. G. Gifta Jerith; Mrs. Madduri Deepika; and D. Panduranga.
The application for the patent was published on Jan. 2, under issue no. 01/2026.
According to the abstract released by the Intellectual Property India: "Modern organization is highly dependent on remote work environment, where users access the systems from different places, with different devices and network conditions. Such environments present erratic security postures and unpredictable risks that cannot be well dealt with by conventional cybersecurity controls. A context-aware cybersecurity framework provides a systematic approach to analyzing real-time situations into the conditions leading up to each remote access attempt and applying dynamic parameters for protection against them without adding unnecessary pressure on employees. The framework always monitors context indicators like user identity patterns, device health state, geo location changes, network characteristics, behavioral deviations, ongoing activities and sensitivity levels of requested resources. These inputs create a dynamic context profile which represents the level of risk for a given session. When a user tries to access organizational applications or data, the system computes a contextual risk score and performs related security action. Depending on the situation assessed, be granted access, challenged with additional authentication, restricted access to limited resources, monitored more closely or blocked off temporarily. Risk evaluation models are able to adjust for long-term trends by learning from repeated behaviours, unusual access patterns and incident history. This enables even minute anomalies like compromised accounts to be identified by the framework, unauthorized devices, suspicious location, or irregular times of the activity timeline. By considering the user's environment as well as his behavior, the approach promotes robust security for distributed teams while ensuring smooth and uninterrupted workflow. The framework is appropriate for enterprise remote operating, hybrid work models, and working field teams and cloud-connected infrastructures that need continuous and intelligent security adaptation."
Disclaimer: Curated by HT Syndication.
