Dark Lookout

Dark Lookout is responsible for analyzing risks and security threats in the cyberspace. For maintaining the security of the organization's data, Dark Lookout provides proactive and reactive services. In this project, Dark Lookout proactive services will only be focused. The proactive

Project Title

Dark Lookout

Project Area of Specialization

Cyber Security

Project Summary

Dark Lookout is responsible for analyzing risks and security threats in the cyberspace. For maintaining the security of the organization's data, Dark Lookout provides proactive and reactive services. In this project, Dark Lookout proactive services will only be focused. The proactive services include security alerts/warnings and discovering new threats via analysis. Dark Lookout provides a web-based graphical user interface through which a person can check the security threats/gaps.

A dynamic web crawler will be used to scrap information from dark web forums and store the information in the database. After storing information (text), text mining techniques will be applied to predict threats in cyberspace. In text mining techniques, first we will process the text. Text processing and Understanding includes text tokenization, text normalization and understanding text structure and syntax. After text processing, the next step will be text classification. Nave Bayes and Support Vector Machines algorithms are available for text classification. Text semantic analysis techniques will be used to understand the meaning of sentences or words. After semantic/sentiment analysis, Machine Learning models will be used to predict the future threats. Data will be visualized after predicting threats through machine learning models.

Project Objectives

Today everyone (company or an organization) wants their data to be secured. A large number of cyber-attacks are occurring in the world. People are suffering from these attacks and lose their data. Due to a large number of Cyber-attacks, company or an organization are always struggling to monitor their data and stop unauthorized access to their data. Currently, cyber-teams are hired to protect company data from unauthorized access. Cyber-teams do manual work to find leakage of data, stop unauthorized access and display threat warnings. Cyber-teams need sufficient time to analyze threats and protect information. To save the cost of manual work and time, a reliable system is needed which is able to automatically find threats and display alerts/warnings to security analysts to protect their information against these threats. Instead of analyzing the whole system for security gaps, now security experts will only focus on the detected security gaps through Dark Lookout to protect the information from threats.

Project Implementation Method

The process methodology for Dark Lookout is Waterfall. We will use waterfall instead of incremental methodology because we need to understand the whole projects flow and working of modules before we start to implement.

Benefits of the Project

Dark Lookout will save time and cost to find and analyse threats in the cyberspace. Cyber teams will easily find threats instead of manually finding threats using different tools.

Technical Details of Final Deliverable

Web Crawler will be used to crawl dark-web and scrape data from dark-web forums. Text Mining techniques will be used to process raw data and then classify the data and find semantics of text. Machine Learning algorithms will be used to find threats from the classified data-set. At the end, visualize these threats to web interface.

Final Deliverable of the Project

Software System

Type of Industry

IT

Technologies

Artificial Intelligence(AI)

Sustainable Development Goals

Industry, Innovation and Infrastructure

Required Resources

If you need this project, please contact me on contact@adikhanofficial.com