Detecting And Combating Malicious Email

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

Learn how to detect, analyze, and respond to phishing emails, the top infection vector used by cybercriminals. The repeatable process described in this book has been cultivated and tested in real-life incidents and validated across multiple threat landscapes and environments. Every organization and individual with an email account is susceptible to deceptive emails sent by attackers with nefarious intentions. This activity, known as phishing, involves an attacker attempting to lure individuals into providing sensitive information or performing a predetermined action. Attacks vary in sophistication, but the core skills and process to detect, analyze, and respond to a suspicious message does not change. Attackers have preyed on victims with convincing and not-so-convincing phishing emails to gain initial footholds into networks around the world for over 30 years. This attack method has been rapidly growing in popularity and continues to be the number one method that organizations and individuals struggle to defend against. Regardless of what any vendor or organization will tell you, no infallible tool exists to eliminate this threat completely. This book teaches you how to analyze suspicious messages using free tools and resources. You will understand the basics of email, tactics used by attackers, and a repeatable process to systematically analyze messages and respond to suspicious activity. You Will Learn How to: Safely save email messages as attachments for analysis Identify what information is in an email header Review header information and extract key indicators or patterns used for detection Identify signs of a suspicious or malicious email message Detect the tactics that attackers use in phishing emails Safely examine email links and attachments Use a variety of free and simple tools to analyze email messages.

An essential anti-phishing desk reference for anyone with an email address Phishing Dark Waters addresses the growing and continuing scourge of phishing emails, and provides actionable defensive techniques and tools to help you steer clear of malicious emails. Phishing is analyzed from the viewpoint of human decision-making and the impact of deliberate influence and manipulation on the recipient. With expert guidance, this book provides insight into the financial, corporate espionage, nation state, and identity theft goals of the attackers, and teaches you how to spot a spoofed e-mail or cloned website. Included are detailed examples of high profile breaches at Target, RSA, Coca Cola, and the AP, as well as an examination of sample scams including the Nigerian 419, financial themes, and post high-profile event attacks. Learn how to protect yourself and your organization using anti-phishing tools, and how to create your own phish to use as part of a security awareness program. Phishing is a social engineering technique through email that deceives users into taking an action that is not in their best interest, but usually with the goal of disclosing information or installing malware on the victim's computer. Phishing Dark Waters explains the phishing process and techniques, and the defenses available to keep scammers at bay. Learn what a phish is, and the deceptive ways they've been used Understand decision-making, and the sneaky ways phishers reel you in Recognize different types of phish, and know what to do when you catch one Use phishing as part of your security awareness program for heightened protection Attempts to deal with the growing number of phishing incidents include legislation, user training, public awareness, and technical security, but phishing still exploits the natural way humans respond to certain situations. Phishing Dark Waters is an indispensible guide to recognizing and blocking the phish, keeping you, your organization, and your finances safe.

There are an increasing number of emails purporting to be from a trusted entity that attempt to deceive users into providing account or identity information, commonly known as phishing emails. Traditional spam filters are not adequately detecting these undesirable emails, and this causes problems for both consumers and businesses wishing to do business online. From a learning perspective, this is a challenging problem. At first glance, the problem appears to be a simple text classification problem, but the classification is confounded by the fact that the class of phishing emails is nearly identical to the class of real emails. We propose a new method for detecting these malicious emails called PILFER. By incorporating features specifically designed to highlight the deceptive methods used to fool users, we are able to accurately classify over 92% of phishing emails, while maintaining a false positive rate on the order of 0.1%. These results are obtained on a dataset of approximately 860 phishing emails and 6950 non-phishing emails. The accuracy of PILFER on this dataset is significantly better than that of SpamAssassin, a widely-used spam filter.

"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

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.

ABSTRACT: The Internet email system as a popular online communication tool has been increasingly misused by ill-willed users to carry out malicious activities including spamming and phishing. Alarmingly, in recent years the nature of the email-based malicious activities has evolved from being purely annoying (with the notorious example of spamming) to being criminal (with the notorious example of phishing). Despite more than a decade of anti-spam and anti-phishing research and development efforts, both the sophistication and volume of spam and phishing messages on the Internet have continuously been on the rise over the years. A key difficulty in the control of email-based malicious activities is that malicious actors have great operational flexibility in performing email-based malicious activities, in terms of both the email delivery infrastructure and email content; moreover, existing anti-spam and anti-phishing measures allow for arms race between malicious actors and the anti-spam and anti-phishing community. In order to effectively control email-based malicious activities such as spamming and phishing, we argue that we must limit (and ideally, eliminate) the operational flexibility that malicious actors have enjoyed over the years. In this dissertation we develop and evaluate a sender-centric approach (SCA) to addressing the problem of email-based malicious activities so as to control spam and phishing emails on the Internet. SCA consists of three complementary components, which together greatly limit the operational flexibility of malicious actors in sending spam and phishing emails. The first two components of SCA focus on limiting the infrastructural flexibility of malicious actors in delivering emails, and the last component focuses on on limiting the flexibility of malicious actors in manipulating the content of emails. In the first component of SCA, we develop a machine-learning based system to prevent malicious actors from utilizing compromised machines to send spam and phishing emails. Given that the vast majority of spam and phishing emails are delivered via compromised machines on the Internet today, this system can greatly limit the infrastructural flexibility of malicious actors. Ideally, malicious actors should be forced to send spam and phishing messages from their own machines so that blacklists and reputation-based systems can be effectively used to block spam and phishing emails. The machine-learning based system we develop in this dissertation is a critical step towards this goal. In recent years, malicious actors also started to employ advanced techniques to hijack network prefixes in conducting email-based malicious activities, which makes the control and attribution of spam and phishing emails even harder. In the second component of SCA, we develop a practical approach to improve the security of the Internet inter-domain routing protocol BGP. Given that the key difficulties in adopting any mechanism to secure the Internet inter-domain routing are the overhead and incremental deployment property of the mechanism, our scheme is designed to have minimum overhead and it can be incrementally deployed by individual networks on the Internet to protect themselves (and their customer networks), so that individual networks have incentives to deploy the scheme. In addition to the infrastructural flexibility in delivering spam and phishing emails, malicious actors have enormous flexibility in manipulating the format and content of email messages. In particular, malicious actors can forge phishing messages as close to legitimate messages in terms of both format and content. Although malicious actors have immense power in manipulating the format and content of phishing emails, they cannot completely hide how a message is delivered to the recipients. Based on this observation, in the last component of SCA, we develop a system to identify phishing emails based on the sender- related information instead of the format or content of email messages. Together, the three complementary components of SCA will greatly limit the operational flexibility and capability that malicious actors have enjoyed over the years in delivering spam and phishing emails, and we believe that SCA will make a significant contribution towards addressing the spam and phishing problem on the Internet.