Malicious email is, simply put, email with a malicious purpose. The malicious purpose could be fraud, theft, espionage, or malware injection. The processes by which email execute the malicious activity vary widely, from fully manual (e.g. human-directed) to fully automated. One example of a malicious email is one that contains an attachment which the recipient is directed to open. When the attachment is opened, malicious software is installed on the recipient's computer. Because malicious email can vary so broadly in form and function, automated detection is only marginally helpful. The education of all users to detect potential malicious email is important to containing the threat and limiting the damage. It is increasingly necessary for all email users to understand how to recognize and combat malicious email. Detecting and Combating Malicious Email describes the different types of malicious email, shows how to differentiate malicious email from benign email, and suggest protective strategies for both personal and enterprise email environments. - Discusses how and why malicious e-mail is used - Explains how to find hidden viruses in e-mails - Provides hands-on concrete steps to detect and stop malicious e-mail before it is too late - Covers what you need to do if a malicious e-mail slips through

Phishing is one of the most widely-perpetrated forms of cyber attack, used to gather sensitive information such as credit card numbers, bank account numbers, and user logins and passwords, as well as other information entered via a web site. The authors of A Machine-Learning Approach to Phishing Detetion and Defense have conducted research to demonstrate how a machine learning algorithm can be used as an effective and efficient tool in detecting phishing websites and designating them as information security threats. This methodology can prove useful to a wide variety of businesses and organizations who are seeking solutions to this long-standing threat. A Machine-Learning Approach to Phishing Detetion and Defense also provides information security researchers with a starting point for leveraging the machine algorithm approach as a solution to other information security threats. - Discover novel research into the uses of machine-learning principles and algorithms to detect and prevent phishing attacks - Help your business or organization avoid costly damage from phishing sources - Gain insight into machine-learning strategies for facing a variety of information security threats

"Phishing" is the hot new identity theft scam. An unsuspecting victim receives an e-mail that seems to come from a bank or other financial institution, and it contains a link to a Web site where s/he is asked to provide account details. The site looks legitimate, and 3 to 5 percent of people who receive the e-mail go on to surrender their information-to crooks. One e-mail monitoring organization reported 2.3 billion phishing messages in February 2004 alone. If that weren't enough, the crooks have expanded their operations to include malicious code that steals identity information without the computer user's knowledge. Thousands of computers are compromised each day, and phishing code is increasingly becoming part of the standard exploits. Written by a phishing security expert at a top financial institution, this unique book helps IT professionals respond to phishing incidents. After describing in detail what goes into phishing expeditions, the author provides step-by-step directions for discouraging attacks and responding to those that have already happened. In Phishing, Rachael Lininger: Offers case studies that reveal the technical ins and outs of impressive phishing attacks. Presents a step-by-step model for phishing prevention. Explains how intrusion detection systems can help prevent phishers from attaining their goal-identity theft. Delivers in-depth incident response techniques that can quickly shutdown phishing sites.

In recent years, industries have transitioned into the digital realm, as companies and organizations are adopting certain forms of technology to assist in information storage and efficient methods of production. This dependence has significantly increased the risk of cyber crime and breaches in data security. Fortunately, research in the area of cyber security and information protection is flourishing; however, it is the responsibility of industry professionals to keep pace with the current trends within this field. The Handbook of Research on Cyber Crime and Information Privacy is a collection of innovative research on the modern methods of crime and misconduct within cyber space. It presents novel solutions to securing and preserving digital information through practical examples and case studies. While highlighting topics including virus detection, surveillance technology, and social networks, this book is ideally designed for cybersecurity professionals, researchers, developers, practitioners, programmers, computer scientists, academicians, security analysts, educators, and students seeking up-to-date research on advanced approaches and developments in cyber security and information protection.

This book captures the state of the art research in the area of malicious code detection, prevention and mitigation. It contains cutting-edge behavior-based techniques to analyze and detect obfuscated malware. The book analyzes current trends in malware activity online, including botnets and malicious code for profit, and it proposes effective models for detection and prevention of attacks using. Furthermore, the book introduces novel techniques for creating services that protect their own integrity and safety, plus the data they manage.

Discover how the internals of malware work and how you can analyze and detect it. You will learn not only how to analyze and reverse malware, but also how to classify and categorize it, giving you insight into the intent of the malware. Malware Analysis and Detection Engineering is a one-stop guide to malware analysis that simplifies the topic by teaching you undocumented tricks used by analysts in the industry. You will be able to extend your expertise to analyze and reverse the challenges that malicious software throws at you. The book starts with an introduction to malware analysis and reverse engineering to provide insight on the different types of malware and also the terminology used in the anti-malware industry. You will know how to set up an isolated lab environment to safely execute and analyze malware. You will learn about malware packing, code injection, and process hollowing plus how to analyze, reverse, classify, and categorize malware using static and dynamic tools. You will be able to automate your malware analysis process by exploring detection tools to modify and trace malware programs, including sandboxes, IDS/IPS, anti-virus, and Windows binary instrumentation. The book provides comprehensive content in combination with hands-on exercises to help you dig into the details of malware dissection, giving you the confidence to tackle malware that enters your environment. What You Will Learn Analyze, dissect, reverse engineer, and classify malware Effectively handle malware with custom packers and compilers Unpack complex malware to locate vital malware components and decipher their intent Use various static and dynamic malware analysis tools Leverage the internals of various detection engineering tools to improve your workflow Write Snort rules and learn to use them with Suricata IDS Who This Book Is For Security professionals, malware analysts, SOC analysts, incident responders, detection engineers, reverse engineers, and network security engineers "This book is a beast! If you're looking to master the ever-widening field of malware analysis, look no further. This is the definitive guide for you." Pedram Amini, CTO Inquest; Founder OpenRCE.org and ZeroDayInitiative

bull; Real-world tools needed to prevent, detect, and handle malicious code attacks. bull; Computer infection from viruses, worms, Trojan Horses etc., collectively known as malware is a growing cost problem for businesses. bull; Discover how attackers install malware and how you can peer through their schemes to keep systems safe. bull; Bonus malware code analysis laboratory.