Close this search box.

Home Case Studies Corporate Security Threat Actors Identification with Syntactic-Semantic Analysis

Case Study:

Threat Actors Identification with Syntactic-Semantic Analysis

Immigration departments face daily challenges as thousands cross their borders that must be protected from dangerous entries. It is the responsibility of immigration department to identify known or potential suspects as they enter the country. To do this effectively, border control personnel must be able to process mass amounts of data on individuals and spot out those that appear questionable, and may need to be investigated. It is difficult to identify suspicious individuals without knowledge of their history or awareness of their online activity.

With social media becoming an integral part of society, people without social media accounts are a minority. Sorting through many social media profiles can be hugely time-consuming, along with understanding who the actual person is behind the online profiles. Understanding a social profile and processing its data to make full sense of it is tedious work.


When analyzing a profile, it is important to frequently inspect the words used and understand their context and sentiment. Our solutions combine basic text analysis with deep syntactic-semantic analysis with the objective to expose relations between screened individuals and others.

Cobwebs’ solutions offer an automated intelligence platform that quickly analyzes online profiles and provides insights regarding online activity that may be indicative of criminal activity.

The company was able to identify the source of the information and ensure its removal. While the information was posted on social media, its quick identification and proceeding actions allowed the company to mitigate the impact of the release of data and the compliance risks at hand. Over and above this, the company changed and improved its social media posting policies for increased prevention of concerns.

Cobwebs’ solutions were created to handle big data while using artificial intelligence to recognize patterns of threats, and discover hidden associations of suspicious individuals. The solutions provide alerts of divergent incidents, threats, or disruptions as they happen. Our automated technology performs ongoing batch processing for individual profiling and scoring, supporting mass amounts of data for immigration departments. The border control solution can unveil affiliations to blacklisted organizations or political groups, alerting users of suspicious individuals in real time.


Request this Case Study

Share This Case Study:

Skip to content