Digital Vulnerability Scoring via Clear and Dark Web PII Analysis
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Solution Overview
Problem
It is challenging to assess the risk of an individual being targeted for a cyberattack due to the increasing frequency and secrecy of cyberattacks, and the vast number of online locations where personally identifying information (PII) may be posted, making it difficult to quantify digital vulnerability.
Innovation Solution
A method and system to determine an individual's or entity's risk of being targeted by a cyberattack by quantifying their online presence through accessing and evaluating PII features from both the clear web and dark web, using web browsing and automation tools, spider programs, natural language processing extractors, and a scoring module to generate a digital vulnerability (DV) score.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If comprehensive online information is accessed from multiple sources including dark web, then measurement precision of digital vulnerability is improved, but device complexity increases
Solution Approach 1:
The system segments the online information landscape into distinct domains (clear web, dark web, deep web) and employs specialized access methods for each. Spider programs navigate clear web structures, while specialized browsers access dark web resources, and automated tools explore deep web databases. This segmentation allows comprehensive coverage without requiring a single complex system to handle all web types simultaneously.
Solution Approach 2:
The system introduces intermediary components including automated spider programs that act as intermediaries between the assessment system and online sources, specialized browsers that mediate access to dark web resources, and natural language processing extractors that serve as intermediaries between raw online information and vulnerability assessment data. These intermediaries simplify the overall system architecture by handling complex access and processing tasks independently.
2Productivity
If automated tools and spider programs are used to access online information, then productivity of information gathering is improved, but ease of operation deteriorates
Solution Approach 1:
The spider programs and automated access tools are designed to autonomously navigate online sources, extract relevant information, and feed data to the vulnerability assessment system without requiring manual configuration or intervention. The system self-manages the complex tasks of accessing different web types, parsing diverse data formats, and processing information streams, thereby maintaining high productivity while preserving operational simplicity for the end user.
3Loss of information
If natural language processing extractors are deployed, then loss of information is reduced, but device complexity increases
Solution Approach 1:
The system replaces manual information extraction and analysis methods with natural language processing extractors that automatically parse, understand, and extract meaningful data from diverse online sources. This substitution of mechanical/manual processes with automated NLP technology reduces information loss while managing complexity through specialized software components designed for specific extraction tasks.
Data Source
AI summary
Methods, systems and computer program products are provided to determine an individual's risk of being targeted by a cyberattack based on quantifying their online presence. In some embodiments, online information pertaining to an individual, accessible through the clear web (e.g., Internet) or the dark web, is identified and used to calculate a digital vulnerability (DV) score. The DV score is used to determine the susceptibility of an individual of being targeted for a cyberattack or cybercrime based upon their online presence, and may be computed based upon personally identifying information (PII) features present on clear web and deep/dark web resources.