【网络安全】很棒的用于网络安全的机器学习

与使用机器学习进行网络安全相关的令人惊叹的工具和资源的精选列表。

Table of Contents

• Datasets
• Papers
• Books
• Talks
• Tutorials
• Courses
• Miscellaneous

↑ Contributing

Please read CONTRIBUTING if you wish to add tools or resources.

↑ Datasets

• HIKARI-2021 Datasets
• Samples of Security Related Data
• DARPA Intrusion Detection Data Sets [ 1998 / 1999 ]
• Stratosphere IPS Data Sets
• Open Data Sets
• Data Capture from National Security Agency
• The ADFA Intrusion Detection Data Sets
• NSL-KDD Data Sets
• Malicious URLs Data Sets
• Multi-Source Cyber-Security Events
• KDD Cup 1999 Data
• Web Attack Payloads
• WAF Malicious Queries Data Sets
• Malware Training Data Sets
• Aktaion Data Sets
• CRIME Database from DeepEnd Research
• Publicly available PCAP files
• 2007 TREC Public Spam Corpus
• Drebin Android Malware Dataset
• PhishingCorpus Datset
• EMBER
• Vizsec Research
• SHERLOCK
• Probing / Port Scan - Dataset
• Aegean Wireless Intrusion Dataset (AWID)
• BODMAS PE Malware Dataset

↑ Papers

• Generating Network Intrusion Detection Dataset Based on Real and Encrypted Synthetic Attack Traffic
• Fast, Lean, and Accurate: Modeling Password Guessability Using Neural Networks
• Outside the Closed World: On Using Machine Learning for Network Intrusion Detection
• Anomalous Payload-Based Network Intrusion Detection
• Malicious PDF detection using metadata and structural features
• Adversarial support vector machine learning
• Exploiting machine learning to subvert your spam filter
• CAMP – Content Agnostic Malware Protection
• Notos – Building a Dynamic Reputation System for DNS
• Kopis – Detecting malware domains at the upper dns hierarchy
• Pleiades – From Throw-away Traffic To Bots – Detecting The Rise Of DGA-based Malware
• EXPOSURE – Finding Malicious Domains Using Passive DNS Analysis
• Polonium – Tera-Scale Graph Mining for Malware Detection
• Nazca – Detecting Malware Distribution in Large-Scale Networks
• PAYL – Anomalous Payload-based Network Intrusion Detection
• Anagram – A Content Anomaly Detector Resistant to Mimicry Attacks
• Applications of Machine Learning in Cyber Security
• Data Mining для построения систем обнаружения сетевых атак (RUS)
• Выбор технологий Data Mining для систем обнаружения вторжений в корпоративную сеть (RUS)
• Нейросетевой подход к иерархическому представлению компьютерной сети в задачах информационной безопасности (RUS)
• Методы интеллектуального анализа данных и обнаружение вторжений (RUS)
• Dimension Reduction in Network Attacks Detection Systems
• Rise of the machines: Machine Learning & its cyber security applications
• Machine Learning in Cyber Security: Age of the Centaurs
• Automatically Evading Classifiers A Case Study on PDF Malware Classifiers
• Weaponizing Data Science for Social Engineering — Automated E2E Spear Phishing on Twitter
• Machine Learning: A Threat-Hunting Reality Check
• Neural Network-based Graph Embedding for Cross-Platform Binary Code Similarity Detection
• Practical Secure Aggregation for Privacy-Preserving Machine Learning
• DeepLog: Anomaly Detection and Diagnosis from System Logs through Deep Learning
• eXpose: A Character-Level Convolutional Neural Network with Embeddings For Detecting Malicious URLs, File Paths and Registry Keys
• Big Data Technologies for Security Event Correlation Based on Event Type Accounting (RUS)
• Investigation of The Use of Neural Networks for Detecting Low-Intensive Ddоs-Atak of Applied Level (RUS)
• Detecting Malicious PowerShell Commands using Deep Neural Networks
• Machine Learning DDoS Detection for Consumer Internet of Things Devices
• Anomaly Detection in Computer System by Intellectual Analysis of System Journals (RUS)
• EMBER: An Open Dataset for Training Static PE Malware Machine Learning Models
• A state-of-the-art survey of malware detection approaches using data mining techniques.
• Investigation of malicious portable executable file detection on network using supervised learning techniques.
• Machine Learning in Cybersecurity: A Guide
• Outside the Closed World: On Using Machine Learning For Network Intrusion Detection
• Machine Learning Based Network Vulnerability Analysis of Industrial Internet of Things
• Hopper: Modeling and Detecting Lateral Movement
• Finding Effective Security Strategies through Reinforcement Learning and Self-Play
• Intrusion Prevention through Optimal Stopping

↑ Books

• Data Mining and Machine Learning in Cybersecurity
• Machine Learning and Data Mining for Computer Security
• Network Anomaly Detection: A Machine Learning Perspective
• Machine Learning and Security: Protecting Systems with Data and Algorithms
• Introduction To Artificial Intelligence For Security Professionals
• Mastering Machine Learning for Penetration Testing
• Malware Data Science: Attack Detection and Attribution

↑ Talks

• Using Machine Learning to Support Information Security
• Defending Networks with Incomplete Information
• Applying Machine Learning to Network Security Monitoring
• Measuring the IQ of your Threat Intelligence Feeds
• Data-Driven Threat Intelligence: Metrics On Indicator Dissemination And Sharing
• Applied Machine Learning for Data Exfil and Other Fun Topics
• Secure Because Math: A Deep-Dive on ML-Based Monitoring
• Machine Duping 101: Pwning Deep Learning Systems
• Delta Zero, KingPhish3r – Weaponizing Data Science for Social Engineering
• Defeating Machine Learning What Your Security Vendor Is Not Telling You
• CrowdSource: Crowd Trained Machine Learning Model for Malware Capability Det
• Defeating Machine Learning: Systemic Deficiencies for Detecting Malware
• Packet Capture Village – Theodora Titonis – How Machine Learning Finds Malware
• Build an Antivirus in 5 Min – Fresh Machine Learning #7. A fun video to watch
• Hunting for Malware with Machine Learning
• Machine Learning for Threat Detection
• Machine Learning and the Cloud: Disrupting Threat Detection and Prevention
• Fraud detection using machine learning & deep learning
• The Applications Of Deep Learning On Traffic Identification
• Defending Networks With Incomplete Information: A Machine Learning Approach
• Machine Learning & Data Science
• Advances in Cloud-Scale Machine Learning for Cyber-Defense
• Applied Machine Learning: Defeating Modern Malicious Documents
• Automated Prevention of Ransomware with Machine Learning and GPOs
• Learning to Detect Malware by Mining the Security Literature
• Clarence Chio and Anto Joseph - Practical Machine Learning in Infosecurity
• Advances in Cloud-Scale Machine Learning for Cyberdefense
• Machine Learning-Based Techniques For Network Intrusion Detection
• Practical Machine Learning in Infosec
• AI and Security
• AI in InfoSec
• Beyond the Blacklists: Detecting Malicious URL Through Machine Learning
• Machine Learning Fueled Cyber Threat Hunting
• Weaponizing Machine Learning: Humanity Was Overrated
• Machine Learning, Offense, and the future of Automation
• Bringing Red vs. Blue to Machine Learning
• Explaining Machine Learning with Azure and the Titanic Dataset
• Using Machines to exploit Machines
• Analyze active directory event logs using visualize and ML
• Hardening Machine Learning Defenses Against Adversarial Attacks
• Deep Neural Networks for Hackers: Methods, Applications, and Open Source Tools
• ML in the daily work of a threat hunter
• The Real Deal About AI: ML for CyberSecurity - Josh Fu
• Automated Detection of Software Vulnerabilities Using Deep-Learning
• Building and Breaking a Machine Learning System - Johann Rehberger
• Vulnerabilities of Machine Learning Infrastructure - Sergey Gordeychik

↑ Tutorials

• Machine Learning based Password Strength Classification
• Using Machine Learning to Detect Malicious URLs
• Using deep learning to break a Captcha system
• Data mining for network security and intrusion detection
• Applying Machine Learning to Improve Your Intrusion Detection System
• Analyzing BotNets with Suricata & Machine Learning
• fWaf – Machine learning driven Web Application Firewall
• Deep Session Learning for Cyber Security
• DMachine Learning for Malware Detection
• ShadowBrokers Leak: A Machine Learning Approach
• Practical Machine Learning in Infosec - Virtualbox Image and Stuff
• A Machine-Learning Toolkit for Large-scale eCrime Forensics
• WebShells Detection by Machine Learning
• Building Machine Learning Models for the SOC
• Detecting Web Attacks With Recurrent Neural Networks
• Machine Learning for Red Teams, Part 1
• Detecting Reverse Shell with Machine Learning
• Obfuscated Command Line Detection Using Machine Learning
• Обнаружение веб-атак с помощью рекуррентных нейронных сетей (RUS)
• Clear and Creepy Danger of Machine Learning: Hacking Passwords
• Discovering anomalous patterns based on parent-child process relationships
• Machine Learning for Detecting Phishing Websites
• Password Hunting with ML in Active Directory
• Как самому разработать систему обнаружения компьютерных атак на основе машинного обучения (RUS)

↑ Courses

• Data Mining for Cyber Security by Stanford
• Data Science and Machine Learning for Infosec
• Cybersecurity Data Science on Udemy
• Machine Learning for Red Team Hackers on Udemy
• Machine Learning for Security

↑ Miscellaneous

• System predicts 85 percent of cyber-attacks using input from human experts
• A list of open source projects in cyber security using machine learning
• Source code about machine learning and security
• Source code for Mastering Machine Learning for Penetration Testing
• Convolutional neural network for analyzing pentest screenshots
• Big Data and Data Science for Security and Fraud Detection
• StringSifter - a machine learning tool that ranks strings based on their relevance for malware analysis

原文：https://github.com/jivoi/awesome-ml-for-cybersecurity