Email Thread
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Machine Learning for Email
Author: Drew Conway
language: en
Publisher: "O'Reilly Media, Inc."
Release Date: 2011-10-27
This compact book explores standard tools for text classification, and teaches the reader how to use machine learning to decide whether a e-mail is spam or ham (binary classification), based on raw data from The SpamAssassin Public Corpus. Of course, sometimes the items in one class are not created equally, or we want to distinguish among them in some meaningful way. The second part of the book will look at how to not only filter spam from our email, but also placing "more important" messages at the top of the queue. This is a curated excerpt from the upcoming book "Machine Learning for Hackers."
Effective Threat Investigation for SOC Analysts
Author: Mostafa Yahia
language: en
Publisher: Packt Publishing Ltd
Release Date: 2023-08-25
Detect and investigate various cyber threats and techniques carried out by malicious actors by analyzing logs generated from different sources Purchase of the print or Kindle book includes a free PDF eBook Key Features Understand and analyze various modern cyber threats and attackers' techniques Gain in-depth knowledge of email security, Windows, firewall, proxy, WAF, and security solution logs Explore popular cyber threat intelligence platforms to investigate suspicious artifacts Book DescriptionEffective threat investigation requires strong technical expertise, analytical skills, and a deep understanding of cyber threats and attacker techniques. It's a crucial skill for SOC analysts, enabling them to analyze different threats and identify security incident origins. This book provides insights into the most common cyber threats and various attacker techniques to help you hone your incident investigation skills. The book begins by explaining phishing and email attack types and how to detect and investigate them, along with Microsoft log types such as Security, System, PowerShell, and their events. Next, you’ll learn how to detect and investigate attackers' techniques and malicious activities within Windows environments. As you make progress, you’ll find out how to analyze the firewalls, flows, and proxy logs, as well as detect and investigate cyber threats using various security solution alerts, including EDR, IPS, and IDS. You’ll also explore popular threat intelligence platforms such as VirusTotal, AbuseIPDB, and X-Force for investigating cyber threats and successfully build your own sandbox environment for effective malware analysis. By the end of this book, you’ll have learned how to analyze popular systems and security appliance logs that exist in any environment and explore various attackers' techniques to detect and investigate them with ease.What you will learn Get familiarized with and investigate various threat types and attacker techniques Analyze email security solution logs and understand email flow and headers Practically investigate various Windows threats and attacks Analyze web proxy logs to investigate C&C communication attributes Leverage WAF and FW logs and CTI to investigate various cyber attacks Who this book is for This book is for Security Operation Center (SOC) analysts, security professionals, cybersecurity incident investigators, incident handlers, incident responders, or anyone looking to explore attacker techniques and delve deeper into detecting and investigating attacks. If you want to efficiently detect and investigate cyberattacks by analyzing logs generated from different log sources, then this is the book for you. Basic knowledge of cybersecurity and networking domains and entry-level security concepts are necessary to get the most out of this book.
Data Quality and Trust in Big Data
This book constitutes revised selected papers from the International Workshop on Data Quality and Trust in Big Data, QUAT 2018, which was held in conjunction with the International Conference on Web Information Systems Engineering, WISE 2018, in Dubai, UAE, in November 2018. The 9 papers presented in this volume were carefully reviewed and selected from 15 submissions. They deal with novel ideas and solutions related to the problems of exploring, assessing, monitoring, improving, and maintaining the quality of data and trust for Big Data.