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ML x Security: Latest News, Insights, and Analysis

Latest Insights and Analyses

Understanding Surrogate Models in EDR and XDR: Enhancing Cybersecurity with Interpretability

In the continuously evolving landscape of cybersecurity, understanding the complex algorithms and models that power advanced threat detection systems is crucial. Surrogate models serve as…

Open XDR, AI, and Machine Learning

In today's rapidly evolving digital landscape, cybersecurity threats are becoming increasingly sophisticated and complex. To combat these challenges, organizations are turning to advanced technologies like…

Summarizing the Paper "Classification and Online Clustering of Zero-Day Malware"

Summarizing the Paper "Classification and Online Clustering of Zero-Day Malware" Introduction: The Ever-Growing Threat of Malware Malware continues to pose significant threats to cybersecurity. Encompassing…

Summary of Recent Advances in Cybersecurity and Sensor Technology Research

Introduction In recent years, significant advancements have been made in the fields of cybersecurity and sensor technology. This blog post provides a detailed summary of…

Exploitation of Vulnerabilities: A Topic-Based Machine Learning Framework for Explaining and Predicting Exploitation

Authors: Konstantinos Charmanas, Nikolaos Mittas, Lefteris Angelis Published in: Information, 2023 DOI: 10.3390/info14070403 The paper addresses the critical issue of security vulnerabilities in software and…

Understanding Language Model Hallucinations: A Deep Dive

Introduction Language models (LMs) like ChatGPT and GPT-4 are powerful tools in artificial intelligence, capable of generating human-like text based on vast datasets. However, a…

FPGA-Accelerated Password Cracking: Leveraging Parallel Hardware for Improving Cybersecurity

Passwords remain a ubiquitous method for securing access to systems and applications across the digital world. However, their effectiveness relies heavily on using strong passwords…

Summary: Scalable MatMul-free Language Modeling

Authors: Rui-Jie Zhu, Yu Zhang, Ethan Sifferman, Tyler Sheaves, Yiqiao Wang, Dustin Richmond, Peng Zhou, Jason K. Eshraghian Abstract: This paper presents a method to…

How Machine Learning is Transforming Cybersecurity: A Non-Technical Overview

Introduction to AI and Machine Learning Artificial Intelligence (AI) often brings to mind futuristic scenarios where intelligent machines dominate. However, most current AI applications are…

Advancing Cybersecurity through Deception and Adaptive Analysis

Advancing Cybersecurity through Deception and Adaptive Analysis Introduction In the evolving landscape of cybersecurity, traditional defense mechanisms are often insufficient to thwart sophisticated cyber threats.

Understanding Machine Learning for Insider Threat Detection in Corporate Environments

The modern digital age has brought immense convenience and connectivity, but it also comes with its own set of challenges, especially in the realm of…

Outrunning Windows Kernel Notification Routines from User-Mode: Explained

Introduction In today's digital age, security is paramount, especially for operating systems that form the backbone of our computing experience. One such system, Microsoft Windows,…

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