DATA ACCESS MANAGEMENT SYSTEMS FOR APPLICATION OPERATIONS

Abstract

ABSTRACT Data Access Management Systems for Application Operations The present disclosure introduces a data access management system for application operations which enhances secure, adaptive data handling through a multi-layered architecture. The system incorporates an access control layer 102 for dynamic, role-based permissions and an authentication module 104 for multi-factor verification. Real-time monitoring and auditing module 106 logs user activity, while an anomaly detection module 112 flags unusual access patterns using machine learning. Compliance is managed via a data governance framework 108 and compliance dashboard 120, offering centralized oversight and regulatory alignment. Integration layer 110 ensures interoperability with existing security systems. Privacy-preserving data sharing mechanism 124 applies anonymization for secure data sharing, while adaptive learning and policy refinement system 118 continuously improves access controls based on user patterns. Additional components include secure API access management module 128, user behavior analytics module 132, cross-application access management 134, multi-tiered access control levels 136, and AI-driven threat intelligence integration 140. Reference Fig 1

Specification

Description:DETAILED DESCRIPTION

[00022] The following detailed description illustrates embodiments of the present disclosure and ways in which they can be implemented. Although some modes of carrying out the present disclosure have been disclosed, those skilled in the art would recognise that other embodiments for carrying out or practising the present disclosure are also possible.

[00023] The description set forth below in connection with the appended drawings is intended as a description of certain embodiments of data access management system for application operations and is not intended to represent the only forms that may be developed or utilised. The description sets forth the various structures and/or functions in connection with the illustrated embodiments; however, it is to be understood that the disclosed embodiments are merely exemplary of the disclosure that may be embodied in various and alternative forms. The figures are not necessarily to scale; some features may be exaggerated or minimised to show details of particular components. Therefore, specific structural and functional details disclosed herein are not to be interpreted as limiting, but merely as a representative basis for teaching one skilled in the art to variously employ the present invention.

[00024] While the disclosure is susceptible to various modifications and alternative forms, specific embodiment thereof has been shown by way of example in the drawings and will be described in detail below. It should be understood, however, that it is not intended to limit the disclosure to the particular forms disclosed, but on the contrary, the disclosure is to cover all modifications, equivalents, and alternatives falling within the scope of the disclosure.

[00025] The terms "comprises", "comprising", "include(s)", or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a setup, or system that comprises a list of components or steps does not include only those components or steps but may include other components or steps not expressly listed or inherent to such setup or system. In other words, one or more elements in a system or apparatus preceded by "comprises... a" does not, without more constraints, preclude the existence of other elements or additional elements in the system or apparatus.

[00026] In the following detailed description of the embodiments of the disclosure, reference is made to the accompanying drawings and which are shown by way of illustration-specific embodiments in which the disclosure may be practiced. These embodiments are described in sufficient detail to enable those skilled in the art to practice the disclosure, and it is to be understood that other embodiments may be utilized and that changes may be made without departing from the scope of the present disclosure. The following description is, therefore, not to be taken in a limiting sense.

[00027] The present disclosure will be described herein below with reference to the accompanying drawings. In the following description, well-known functions or constructions are not described in detail since they would obscure the description with unnecessary detail.

[00028] Referring to Fig. 1, data access management system for application operations 100 is disclosed in accordance with one embodiment of the present invention. It comprises of access control layer 102, authentication module 104, monitoring and auditing module 106, data governance framework 108, integration layer 110, anomaly detection module 112, user self-service portal 114, data sensitivity tagging and classification module 116, adaptive learning and policy refinement system 118, compliance dashboard 120, automated remediation and alerting system 122, privacy-preserving data sharing mechanism 124, decision support system 126, secure API access management module 128, geofencing and location-based access control 130, user behavior analytics module 132, cross-application access management 134, multi-tiered access control levels 136, chain of custody and granular audit trails 138, AI-driven threat intelligence integration 140, customizable workflow automation tools 142, privacy compliance assessment tools 144, user interface and experience customization 146.

[00029] Referring to Fig. 1, the present disclosure provides details of data access management system for application operations 100. It is designed to secure, monitor, and control data access within dynamic environments using real-time insights and adaptive controls. In one embodiment, the DAMS includes components such as access control layer 102, authentication module 104, and monitoring and auditing module 106, ensuring role-based access and security. The system incorporates a data governance framework 108 and integration layer 110 to facilitate compliance and interoperability. Advanced features like anomaly detection module 112 and user self-service portal 114 enable proactive threat detection and streamlined user access. Additional components, such as compliance dashboard 120 and privacy-preserving data sharing mechanism 124, enhance data governance and secure sharing across platforms.

[00030] Referring to Fig. 1, data access management system for application operations 100 is provided with access control layer 102, which implements dynamic role-based access control to manage user permissions in real-time based on contextual factors such as time, location, and operational role. The access control layer 102 interacts with the authentication module 104 to verify user identity before granting access to sensitive data, ensuring that permissions are enforced at each access point. This component works closely with data sensitivity tagging and classification module 116 to apply relevant access restrictions based on the sensitivity of the data being accessed.

[00031] Referring to Fig. 1, data access management system for application operations 100 is provided with authentication module 104, which employs multi-factor authentication methods to validate user identity through biometrics, passwords, and device recognition. This module enhances security by working in conjunction with the access control layer 102 to ensure that only authorized users gain entry based on predefined access controls. Additionally, it integrates with the real-time monitoring and auditing module 106 to log each authentication attempt, adding an extra layer of security by tracking access history for compliance purposes.

[00032] Referring to Fig. 1, data access management system for application operations 100 is provided with monitoring and auditing module 106, which continuously tracks user activity within the system, recording successful and failed access attempts. This module collaborates with the anomaly detection module 112 to identify unusual behavior patterns, triggering alerts for potential security risks. The detailed logs generated by monitoring and auditing module 106 are also essential for compliance reporting and are accessible through the compliance dashboard 120 for administrative review.

[00033] Referring to Fig. 1, data access management system for application operations 100 is provided with data governance framework 108, which structures and manages data access policies to comply with regulatory requirements and organizational standards. This framework includes tools for data classification, access request workflows, and data lifecycle management, ensuring that all data access aligns with security and legal guidelines. The data governance framework 108 interacts with integration layer 110 to coordinate policy implementation across third-party security systems, enabling a unified approach to data governance.

[00034] Referring to Fig. 1, data access management system for application operations 100 is provided with integration layer 110, which connects the DAMS with external security and enterprise systems like identity and access management (IAM) platforms and cloud service providers. This layer allows for centralized management of access policies by synchronizing configurations across multiple platforms. The integration layer 110 also works closely with the compliance dashboard 120 to consolidate access control data, supporting streamlined regulatory reporting and oversight.

[00035] Referring to Fig. 1, data access management system for application operations 100 is provided with anomaly detection module 112, which leverages machine learning algorithms to detect deviations from normal user access patterns, flagging potential security threats. This module analyzes data from the monitoring and auditing module 106 to identify unusual behaviors that might indicate unauthorized access attempts. By assigning risk scores to flagged activities, anomaly detection module 112 helps prioritize security responses and informs the automated remediation and alerting system 122.

[00036] Referring to Fig. 1, data access management system for application operations 100 is provided with user self-service portal 114, which allows users to request data access based on their roles, with automated workflows for approval. This portal interacts with access control layer 102 to streamline access requests, enabling faster response times while maintaining control over permissions. All access requests and decisions are logged in the monitoring and auditing module 106 for transparency and compliance purposes.

[00037] Referring to Fig. 1, data access management system for application operations 100 is provided with data sensitivity tagging and classification module 116, which automatically categorizes data according to its sensitivity level, applying appropriate access restrictions. This module works in conjunction with access control layer 102 to ensure that only users with relevant permissions can access highly sensitive data. Additionally, it supports the data governance framework 108 in enforcing compliance with data handling policies.

[00038] Referring to Fig. 1, data access management system for application operations 100 is provided with adaptive learning and policy refinement system 118, which uses historical data to refine access policies over time, minimizing excessive permissions. This system adjusts access settings based on user behavior and feedback, optimizing security measures. It collaborates with the anomaly detection module 112 to update policies when unusual access patterns are detected, enhancing the overall adaptability of the DAMS.

[00039] Referring to Fig. 1, data access management system for application operations 100 is provided with compliance dashboard 120, a centralized interface that presents data access activities, compliance status, and audit trails. This dashboard pulls data from monitoring and auditing module 106 and integrates with the data governance framework 108 to provide comprehensive insights for regulatory reporting. The compliance dashboard 120 also supports customizable reporting tools to assist administrators in assessing security and compliance metrics.

[00040] Referring to Fig. 1, data access management system for application operations 100 is provided with automated remediation and alerting system 122, which automatically initiates responses, such as revoking access or alerting security teams, when security threats are detected. This system works in tandem with anomaly detection module 112 to promptly address potential breaches, minimizing risk. Alerts and remediation actions are recorded in monitoring and auditing module 106 for a complete security audit trail.

[00041] Referring to Fig. 1, data access management system 100 is provided with privacy-preserving data sharing mechanism 124, which ensures sensitive information is protected during access requests through anonymization and encryption techniques. This component works closely with data sensitivity tagging and classification module 116 to implement appropriate privacy controls, enabling secure data sharing without exposing sensitive details.

[00042] Referring to Fig. 1, data access management system for application operations 100 is provided with decision support system 126, which assists administrators in making informed policy adjustments and access decisions using machine learning-driven recommendations. This system analyzes data from user behavior analytics module 132 to suggest changes that enhance data governance and security. It also interacts with compliance dashboard 120 to present insights that support regulatory decision-making.

[00043] Referring to Fig. 1, data access management system for application operations 100 is provided with secure API access management module 128, which controls and monitors API access to ensure that only authorized applications can interact with sensitive data. This module is essential in microservices architectures and interacts with integration layer 110 to enforce security policies across connected applications, supporting consistent data protection.

[00044] Referring to Fig. 1, data access management system for application operations 100 is provided with geofencing and location-based access control 130, which restricts data access based on predefined geographic boundaries. This component enhances security in remote work settings by working with authentication module 104 to validate access attempts according to the user's location. It ensures that sensitive data is only accessible within authorized geographic zones.

[00045] Referring to Fig. 1, data access management system for application operations 100 is provided with user behavior analytics module 132, which tracks and analyzes user actions to establish baseline behavior patterns. Any deviation from these patterns triggers alerts, helping detect insider threats or account compromise. This module works closely with anomaly detection module 112 to refine the risk assessment process and enhance security responses.

[00046] Referring to Fig. 1, data access management system for application operations 100 is provided with cross-application access management 134, which allows for consistent application of access control policies across various applications. This component simplifies the management of data access in diverse environments by working with integration layer 110 to synchronize configurations, supporting unified data protection.

[00047] Referring to Fig. 1, data access management system for application operations 100 is provided with multi-tiered access control levels 136, which assigns users to different levels of access (e.g., read, write, execute) based on role and data sensitivity. This component allows for granular control, aligning with access control layer 102 to restrict specific actions based on user privileges, enhancing data governance.

[00048] Referring to Fig. 1, data access management system for application operations 100 is provided with chain of custody and granular audit trails 138, which records detailed information on every data access event, including user identity and action timestamps. This component is crucial for regulatory compliance, as it provides a traceable history of access events. It integrates with compliance dashboard 120 to present a complete audit trail for administrative review.

[00049] Referring to Fig. 1, data access management system for application operations 100 is provided with AI-driven threat intelligence integration 140, which receives real-time updates on emerging threats from external sources, dynamically adjusting access controls as needed. This component enhances system security by working with automated remediation and alerting system 122 to implement preventive measures based on the current threat landscape.

[00050] Referring to Fig. 1, data access management system for application operations 100 is provided with customizable workflow automation tools 142, which enable organizations to define specific workflows for access requests, approvals, and escalations. These tools streamline access management by automating routine tasks and work closely with user self-service portal 114 to provide a seamless access request experience.

[00051] Referring to Fig. 1, data access management system for application operations 100 is provided with privacy compliance assessment tools 144, which help organizations evaluate adherence to regulations like GDPR and HIPAA. These tools provide actionable recommendations for improving data access practices and work in conjunction with compliance dashboard 120 to display compliance assessments.

[00052] Referring to Fig. 1, data access management system for application operations 100 is provided with user interface and experience customization 146, which allows users to personalize their interaction with the DAMS based on their roles and preferences. This customization enhances usability and efficiency, especially when combined with user self-service portal 114 for ease of access requests and monitoring.

[00053] Referring to Fig 2, there is illustrated method 200 for data access management system for application operations 100. The method comprises:
At step 202, method 200 includes the user initiating an access request through the user self-service portal 114 to gain permission for specific data resources;
At step 204, method 200 includes the system verifying user identity through the authentication module 104, using multi-factor authentication methods such as biometrics or device recognition to enhance security;
At step 206, method 200 includes the access control layer 102 evaluating the access request based on the user's role and contextual factors like location and time to determine if the permissions align with predefined access controls;
At step 208, method 200 includes the data sensitivity tagging and classification module 116 identifying the sensitivity level of the requested data and adjusting access permissions accordingly to restrict highly sensitive information;
At step 210, method 200 includes the monitoring and auditing module 106 recording the access event in real time, logging details such as user identity, timestamp, and the nature of the request for audit purposes;
At step 212, method 200 includes the anomaly detection module 112 analyzing user behavior patterns to detect any unusual access attempt that could indicate a security threat, assigning a risk score to the activity if needed;
At step 214, method 200 includes the automated remediation and alerting system 122 issuing an alert to administrators if a high-risk activity is detected, enabling a quick response to potential threats;
At step 216, method 200 includes the data governance framework 108 applying regulatory and organizational policies to ensure that the access granted aligns with compliance standards and data lifecycle management;
At step 218, method 200 includes the compliance dashboard 120 providing administrators with real-time visibility into the data access activities and compliance status, facilitating oversight and reporting;
At step 220, method 200 includes the cross-application access management 134 ensuring consistent application of access policies across various connected applications, streamlining multi-application access management;
At step 222, method 200 includes the privacy-preserving data sharing mechanism 124 securing data during access requests, applying anonymization or encryption to prevent exposure of sensitive information;
At step 224, method 200 includes the user behavior analytics module 132 monitoring user actions within the system, establishing baseline behavior patterns and triggering alerts if any deviations are detected, providing an additional layer of security;
At step 226, method 200 includes the adaptive learning and policy refinement system 118 using historical data and feedback to refine access policies over time, ensuring they remain optimized and aligned with evolving security requirements;
At step 228, method 200 includes the decision support system 126 analyzing historical data to offer recommendations for policy adjustments or access decisions, assisting administrators in making informed decisions;
At step 230, method 200 includes the compliance dashboard 120 generating periodic compliance reports using data from monitoring and auditing module 106 and privacy compliance assessment tools 144 to support regulatory audits;
At step 232, method 200 includes the integration layer 110 coordinating with existing IAM systems and other security infrastructure to centralize control and facilitate seamless interoperability of the DAMS with other enterprise systems.
[00054] In the description of the present invention, it is also to be noted that, unless otherwise explicitly specified or limited, the terms "fixed" "attached" "disposed," "mounted," and "connected" are to be construed broadly, and may for example be fixedly connected, detachably connected, or integrally connected, either mechanically or electrically. They may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meaning of the above terms in the present invention can be understood in specific cases to those skilled in the art.

[00055] Modifications to embodiments of the present disclosure described in the foregoing are possible without departing from the scope of the present disclosure as defined by the accompanying claims. Expressions such as "including", "comprising", "incorporating", "have", "is" used to describe and claim the present disclosure are intended to be construed in a non- exclusive manner, namely allowing for items, components or elements not explicitly described also to be present. Reference to the singular is also to be construed to relate to the plural where appropriate.

[00056] Although embodiments have been described with reference to a number of illustrative embodiments thereof, it should be understood that numerous other modifications and embodiments can be devised by those skilled in the art that will fall within the spirit and scope of the principles of this disclosure. More particularly, various variations and modifications are possible in the component parts and/or arrangements of the subject combination arrangement within the scope of the present disclosure, the drawings and the appended claims. In addition to variations and modifications in the component parts and/or arrangements, alternative uses will also be apparent to those skilled in the art.
, Claims:WE CLAIM:
1. A data access management system for application operations 100 comprising of
access control layer 102 to manage user permissions dynamically based on role and context;
authentication module 104 to enhance security by verifying user identity through multi-factor methods;
monitoring and auditing module 106 to track and log user activity in real-time for compliance;
data governance framework 108 to ensure regulatory compliance and enforce data lifecycle policies;
integration layer 110 to connect DAMS with existing security and enterprise systems;
anomaly detection module 112 to identify unusual behavior patterns and assign risk scores;
user self-service portal 114 to streamline data access requests with automated workflows;
data sensitivity tagging and classification module 116 to categorize data based on sensitivity for secure access;
adaptive learning and policy refinement system 118 to refine access policies based on historical data and feedback;
compliance dashboard 120 to provide real-time visibility into data access and compliance activities;
automated remediation and alerting system 122 to alert administrators and revoke access for detected threats;
privacy-preserving data sharing mechanism 124 to secure sensitive information through anonymization and encryption;
decision support system 126 to assist administrators with policy adjustments based on data analysis;
secure API access management module 128 to manage and secure API interactions with sensitive data;
geofencing and location-based access control 130 to restrict data access based on geographic location;
user behavior analytics module 132 to monitor user actions and establish behavior patterns for security;
cross-application access management 134 to apply consistent access policies across multiple applications;
multi-tiered access control levels 136 to assign specific access privileges based on role and data sensitivity;
chain of custody and granular audit trails 138 to record every access event for accountability;
AI-driven threat intelligence integration 140 to receive real-time threat updates for enhanced security;
customizable workflow automation tools 142 to define workflows for access requests and approvals;
privacy compliance assessment tools 144 to evaluate adherence to privacy regulations like GDPR and HIPAA; and
user interface and experience customization 146 to personalize the DAMS for different user roles and preferences.

2. The data access management system for application operations 100 as claimed in claim 1, wherein the access control layer 102 is configured to dynamically assign and modify user permissions in real-time based on contextual factors such as user role, location, and operational conditions, enabling adaptive, context-aware access control to enhance security.

3. The data access management system for application operations 100 as claimed in claim 1, wherein the authentication module 104 enhances security by utilizing multi-factor authentication methods, combining biometrics, device recognition, and behavioral analysis to verify user identity before access.

4. The data access management system for application operations 100 as claimed in claim 1, wherein the monitoring and auditing module 106 continuously records user activity, logging detailed access events for real-time tracking and comprehensive compliance audits.

5. The data access management system for application operations 100 as claimed in claim 1, wherein the anomaly detection module 112 uses machine learning to identify deviations from established user behavior patterns, assigning risk scores to flagged activities for immediate threat response.

6. The data access management system for application operations 100 as claimed in claim 1, wherein the compliance dashboard 120 provides centralized, real-time visibility into data access activities and compliance metrics, facilitating regulatory reporting and oversight.

7. The data access management system for application operations 100 as claimed in claim 1, wherein the privacy-preserving data sharing mechanism 124 applies anonymization and encryption to secure sensitive information during access requests, preventing unauthorized exposure.

8. The data access management system for application operations 100 as claimed in claim 1, wherein the adaptive learning and policy refinement system 118 refines access policies based on historical data and user behavior, enabling continuous optimization of security measures..

9. The data access management system for application operations 100 as claimed in claim 1, wherein the secure API access management module 128 restricts API interactions to authorized applications only, safeguarding sensitive data within microservices and distributed application architectures..

10. The data access management system for application operations 100 as claimed in claim 1, wherein method comprises of
user initiating an access request through the user self-service portal 114 to gain permission for specific data resources;
system verifying user identity through the authentication module 104, using multi-factor authentication methods such as biometrics or device recognition to enhance security;
access control layer 102 evaluating the access request based on the user's role and contextual factors like location and time to determine if the permissions align with predefined access controls;
data sensitivity tagging and classification module 116 identifying the sensitivity level of the requested data and adjusting access permissions accordingly to restrict highly sensitive information;
monitoring and auditing module 106 recording the access event in real time, logging details such as user identity, timestamp, and the nature of the request for audit purposes;
anomaly detection module 112 analyzing user behavior patterns to detect any unusual access attempt that could indicate a security threat, assigning a risk score to the activity if needed;
automated remediation and alerting system 122 issuing an alert to administrators if a high-risk activity is detected, enabling a quick response to potential threats;
data governance framework 108 applying regulatory and organizational policies to ensure that the access granted aligns with compliance standards and data lifecycle management;
compliance dashboard 120 providing administrators with real-time visibility into the data access activities and compliance status, facilitating oversight and reporting;
cross-application access management 134 ensuring consistent application of access policies across various connected applications, streamlining multi-application access management;
privacy-preserving data sharing mechanism 124 securing data during access requests, applying anonymization or encryption to prevent exposure of sensitive information;
user behavior analytics module 132 monitoring user actions within the system, establishing baseline behavior patterns and triggering alerts if any deviations are detected, providing an additional layer of security;
adaptive learning and policy refinement system 118 using historical data and feedback to refine access policies over time, ensuring they remain optimized and aligned with evolving security requirements;
decision support system 126 analyzing historical data to offer recommendations for policy adjustments or access decisions, assisting administrators in making informed decisions;
compliance dashboard 120 generating periodic compliance reports using data from monitoring and auditing module 106 and privacy compliance assessment tools 144 to support regulatory audits;
integration layer 110 coordinating with existing systems and other security infrastructure to centralize control and facilitate seamless interoperability of the dams with other enterprise systems.

Documents