Advertisement Reputation Server for Malicious Ad Blocking
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Modern computing ecosystems are vulnerable to malicious advertisements that can compromise user devices and data, as they often rely on "always on" Internet connections, making it difficult to distinguish between legitimate and malicious ads without disrupting the advertising business model.
Innovation Solution
A system and method utilizing an advertisement reputation server that analyzes advertiser identifiers, assigns reputations based on behavior analytics and machine learning, and publishes reputation information to block or alert on malicious ads, while allowing legitimate ads to pass through, using a hardware platform with a processor and memory, and a network interface to receive and analyze advertisement instances.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all advertisements are blocked to protect users from malicious ads, then user security is improved, but legitimate advertising revenue is lost
Solution Approach 1:
The patent introduces a reputation server as an intermediary between advertisers and users. This server analyzes advertisements and assigns reputation scores, allowing the system to differentiate between legitimate and malicious ads. The intermediary enables selective blocking based on reputation analysis rather than blanket blocking, thus protecting users while preserving revenue from trustworthy advertisers.
Solution Approach 2:
The system changes the parameter of advertisement evaluation by introducing a reputation score parameter. Instead of treating all ads uniformly, the system evaluates each advertisement based on multiple parameters including source credibility, content analysis, and historical behavior. This parameter-based differentiation allows legitimate ads to pass through while blocking malicious ones.
2Measurement precision
If advertisement analysis is performed to identify malicious ads, then detection accuracy is improved, but system complexity increases
Solution Approach 1:
The patent segments the advertisement analysis system into distinct functional components: a reputation server that performs analysis, a database for storing reputation information, and client devices that enforce blocking decisions. This segmentation allows the complex analysis functionality to be isolated in a dedicated server, keeping individual system components simpler while achieving high detection accuracy through coordinated operation.
Solution Approach 2:
The system performs preliminary analysis of advertisements by the reputation server before they reach users. By pre-evaluating ads and assigning reputation scores in advance, the system avoids the need for complex real-time analysis at the user end. This preliminary action shifts computational complexity to a centralized server with appropriate resources while keeping client devices simple.
3Speed
If real-time advertisement monitoring is implemented to block malicious ads, then response speed is improved, but processing overhead increases
Solution Approach 1:
The reputation server performs analysis and assigns reputation scores to advertisements in advance, before they need to be evaluated by user systems. This preliminary action creates a cache of pre-evaluated advertisement data that can be quickly referenced in real-time, achieving fast response speeds without the processing overhead of real-time analysis for each ad.
Solution Approach 2:
The system creates copies of reputation information and stores them in databases that can be quickly accessed by multiple client devices. Instead of each system performing independent real-time analysis, they use pre-computed reputation data copies, significantly reducing processing overhead while maintaining fast response capabilities.
Data Source
AI summary
There is disclosed in one example an advertisement reputation server, including: a hardware platform including a processor and a memory; a network interface; and an advertisement reputation engine including instructions encoded in memory to instruct the processor to: receive via the network interface a plurality of advertisement instances displayed on client devices; extract from the advertisement instances an advertiser identifier; analyze one or more advertisements associated with the advertiser identifier to assign an advertiser reputation; and publish via the network interface advertisement reputation information derived from the reputation for the advertisement identifier.