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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 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.
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
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.
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.
Cyber attacks are rapidly becoming one of the most prevalent issues in the world. As cyber crime continues to escalate, it is imperative to explore new approaches and technologies that help ensure the security of the online community. The Handbook of Research on Threat Detection and Countermeasures in Network Security presents the latest methodologies and trends in detecting and preventing network threats. Investigating the potential of current and emerging security technologies, this publication is an all-inclusive reference source for academicians, researchers, students, professionals, practitioners, network analysts, and technology specialists interested in the simulation and application of computer network protection.
Phishing and Counter-Measures discusses how and why phishing is a threat, and presents effective countermeasures. Showing you how phishing attacks have been mounting over the years, how to detect and prevent current as well as future attacks, this text focuses on corporations who supply the resources used by attackers. The authors subsequently deliberate on what action the government can take to respond to this situation and compare adequate versus inadequate countermeasures.
Viruses today are more prevalent than ever and the need to protect the network or company against attacks is imperative. Grimes gives strategies, tips and tricks needed to secure any system. He explains what viruses can and can't do, and how to recognize, remove and prevent them.
This book presents the latest advances in machine intelligence and big data analytics to improve early warning of cyber-attacks, for cybersecurity intrusion detection and monitoring, and malware analysis. Cyber-attacks have posed real and wide-ranging threats for the information society. Detecting cyber-attacks becomes a challenge, not only because of the sophistication of attacks but also because of the large scale and complex nature of today’s IT infrastructures. It discusses novel trends and achievements in machine intelligence and their role in the development of secure systems and identifies open and future research issues related to the application of machine intelligence in the cybersecurity field. Bridging an important gap between machine intelligence, big data, and cybersecurity communities, it aspires to provide a relevant reference for students, researchers, engineers, and professionals working in this area or those interested in grasping its diverse facets and exploring the latest advances on machine intelligence and big data analytics for cybersecurity applications.