Endpoint Security Update Prioritization via Reputation Scores
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Traditional systems for distributing security updates to endpoint devices often fail to provide adequate protection for devices with poor security states, such as those infected with malware, as they follow a standard update frequency or rate, leading to increased security deficiencies until the next update cycle.
Innovation Solution
A method and system that prioritize security updates for endpoint devices based on their reputation scores, where devices with poor security states request updates with higher urgency, potentially through more frequent requests or higher priority queues, ensuring timely updates and balancing the workload of the security server.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If endpoint devices use a standard update frequency to request security updates, then the security server workload is evenly distributed, but endpoint devices with poor security states experience increased security deficiencies until their next update cycle
Solution Approach 1:
The system dynamically adjusts the update request frequency and priority of endpoint devices based on their real-time security state (reputation score). Devices with poor security states automatically increase their update request frequency and priority, while devices with good security states maintain standard update patterns. This dynamic adaptation resolves the contradiction by making update timing responsive to actual security needs rather than following a fixed schedule.
Solution Approach 2:
The system changes key parameters (update request frequency, update priority queue position) based on the endpoint device's security state. When a device's reputation score indicates poor security, the system modifies these parameters to ensure faster update delivery. This parameter adjustment mechanism allows the system to prioritize updates for vulnerable devices without affecting the overall update distribution schedule.
2Reliability
If endpoint devices with poor security states request security updates more frequently with higher urgency, then they receive updates promptly, but the security server workload becomes unbalanced
Solution Approach 1:
The system applies different update distribution treatments to different endpoint devices based on their local security conditions. Instead of a uniform update distribution approach, each device receives updates according to its specific security state (reputation score). This local quality differentiation allows the server to focus resources on vulnerable devices while maintaining standard operations for secure devices, resolving the workload balance issue.
Solution Approach 2:
The update distribution system is segmented into multiple priority queues based on endpoint device security states. Devices are divided into different groups (high priority, normal priority) according to their reputation scores, and updates are distributed to each segment according to its needs. This segmentation prevents any single device or group from overwhelming the server while ensuring vulnerable devices receive timely updates.
3Ease of operation
If the security server processes update requests from all endpoint devices simultaneously, then all devices receive updates at the same time, but devices with poor security states experience delayed protection
Solution Approach 1:
The system performs preliminary assessment of endpoint device security states (calculating reputation scores) before distributing updates. This preliminary action allows the server to pre-determine update priorities and queue assignments based on current security conditions, ensuring that vulnerable devices are prepared to receive updates immediately when available, rather than waiting in standard queues.
Solution Approach 2:
The system uses feedback from endpoint device security states (reputation scores, unsafe behaviors, detected threats) to dynamically adjust update distribution priorities. This feedback mechanism ensures that the update distribution process responds to actual security needs, automatically prioritizing devices that require protection more urgently while maintaining simple operation through automated decision-making.
Data Source
AI summary
The disclosed computer-implemented method for applying security updates to endpoint devices may include (1) calculating a reputation score for an endpoint device that indicates a security state of the endpoint device, (2) transmitting, from the endpoint device to a security server that provides security updates, a request to receive a security update with a degree of urgency based on the reputation score of the endpoint device, (3) receiving the security update from the security server in accordance with the degree of urgency, and then (4) applying the security update within the endpoint device. Various other methods, systems, and computer-readable media are also disclosed.