iKy: The Future of User Profiling on Social Media
As more and more people connect and share information through various social media platforms, the capacity for cyber threats has increased exponentially. This reality has accelerated the need for advanced tools that can efficiently monitor and analyze user activity on these platforms. One such pioneering project is iKy, a Github project developed by Kenn Bro.
iKy is a tool that collects information from an email and shows results in a nice visual interface. It is a project aiming to simplify the process of gathering and analyzing information about a user through their social media accounts from a cybersecurity perspective. This article will comprehensively discuss the project's unique features, technology stack, and how you can contribute to it.
Project Overview:
iKy seeks to collect information from an email and present the results in an easy-to-understand interface. Given the growth of social media scams and misinformation campaigns, iKy plays an essential role in identifying potential threats. Its primary users are cybersecurity experts, investigators, and anyone in need of a qualitative evaluation of an individual's online activities.
Project Features:
iKy offers several outstanding features that enable it to fulfill its project's objectives effectively. The core feature is its ability to use an email address as a starting point and collect data about the corresponding user's activities across various social media platforms. This feature provides a comprehensive activity profile of users, which is vital in anomaly detection and threat identification.
Another feature is its impressive visual interface that makes results easy to understand and interpret. The system organizes collected data and administers its visualization, making detailed assessments readily accessible for the user.
Technology Stack:
iKy operates on a robust technology stack. It is wholly developed in Python due to its versatility, simplicity, and wide range of libraries and frameworks suitable for web scraping and data manipulation. It also adopts Elasticsearch for storing and searching large volumes of information and Kibana for data visualization. All these are run on a Docker container that ensures ease of deployment and consistency across different computing environments.
Project Structure and Architecture:
The iKy project has a well-structured and organized architecture. It comprises different components meant for scraping data from various sources, analyzing them, storing, and presenting to the user. The Elasticsearch database acts as the data storage component, while data extraction is handled by multiple Python scripts each tailored for a specific social media platform.
Contribution Guidelines:
