$ ls ~/projects
Featured builds, then every repository from the lab organizations.
$ ls featured/
A study app where watching fills at most half of each concept radar and the rest is earned by answering alone and by teaching an AI student.
313 reproducible Docker and VM scenarios scored on closing the exploit and keeping the service up.
$ gh repo list
Measuring how processor-internal hardware behaviour varies across Intel and AMD CPU generations (Cybear Security Lab).
Automated pipeline for building a labeled corpus of benign and packed Windows executables for packer- and malware-detection research.
Assessing the Impact of Access Control Policies on Data Accessibility in Distributed NoSQL Environments; PANACEA (Policy Analysis and NoSQL Access Control Evaluation Approach)
This repository contains the dataset for the paper "Predicting Software Vulnerability Trends with Multi-Recurrent Neural Networks: A Time Series Forecasting Approach", published in the Proceedings of the 1st International Conference on NLP & AI for Cyber Security (NLPAICS 2024).
This repo supports the paper "Leveraging Secure Social Media Crowdsourcing for Gathering Firsthand Accounts in Conflict Zones." We collected 250,000 Telegram messages on the Russo-Ukrainian conflict and developed a framework to identify contextual groupings, revealing 477 new insights from 13 news sources.
This repository presents research on a novel composite framework for enhancing cyber resilience in Cyber Physical Systems (CPS). The framework integrates Dynamic Access Control, utilizing Authorizing Workflow and Task-Role-Based Access Control (AW-TRBAC), with Intrusion Detection Systems (IDSs) powered by Semantic Variational Autoencoders (SVAEs).
$ gh repo list
A Python-based compiler that parses IEC 61131-3 Structured Text (ST) source files and outputs a corresponding Abstract Syntax Tree (AST) in XML format. It utilizes a custom recursive descent parser (pyPEG-like) for grammar matching and supports advanced features like EPAS pragmas for nested comments.
At La Backdoor, our mission is to advance the field of cybersecurity through innovative research, cutting-edge technology, and unparalleled expertise. We strive to protect and empower individuals, organizations, and societies by anticipating, identifying, and mitigating cyber threats, ensuring a secure digital future for all.
This repository contains a Pytorch implementation of a Multi-Recurrent Network (MRN).