Detecting and Combating Malicious Email Books

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Detecting and Combating Malicious Email


Detecting and Combating Malicious Email
  • Author : Julie JCH Ryan
  • Publisher : Syngress
  • Release : 2014-10-07
  • ISBN : 9780128005460
  • Language : En, Es, Fr & De
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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

Machine Intelligence and Big Data Analytics for Cybersecurity Applications


Machine Intelligence and Big Data Analytics for Cybersecurity Applications
  • Author : Yassine Maleh
  • Publisher : Springer Nature
  • Release : 2020-12-14
  • ISBN : 9783030570248
  • Language : En, Es, Fr & De
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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.

The Little Black Book of Scams


The Little Black Book of Scams
  • Author : Industry Canada
  • Publisher : Competition Bureau Canada
  • Release : 2014-03-10
  • ISBN : 9781100232409
  • Language : En, Es, Fr & De
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The Canadian edition of The Little Black Book of Scams is a compact and easy to use reference guide filled with information Canadians can use to protect themselves against a variety of common scams. It debunks common myths about scams, provides contact information for reporting a scam to the correct authority, and offers a step-by-step guide for scam victims to reduce their losses and avoid becoming repeat victims. Consumers and businesses can consult The Little Black Book of Scams to avoid falling victim to social media and mobile phone scams, fake charities and lotteries, dating and romance scams, and many other schemes used to defraud Canadians of their money and personal information.

Inside the SPAM Cartel


Inside the SPAM Cartel
  • Author : Spammer-X Spammer-X
  • Publisher : Elsevier
  • Release : 2004-11-13
  • ISBN : 0080478506
  • Language : En, Es, Fr & De
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Authored by a former spammer, Inside the SPAM Cartel is a methodical, technically explicit expose of the inner workings of the SPAM economy. Readers will be shocked by the sophistication and sheer size of this underworld. From the author: "You may hate spam and think all spammers are evil, but listen to my story and see why I do this and more importantly, HOW." For most people, the term "SPAM" conjures up the image of hundreds of annoying, and at times offensive, e-mails flooding their inbox every week. But for a few, SPAM is a way of life that delivers an adrenaline rush fueled by cash, danger, retribution, porn and the avoidance of local, federal, and international law enforcement agencies. Inside the SPAM Cartel offer readers a never-before seen view inside this dark sub-economy. You'll meet the characters that control the flow of money as well as the hackers and programmers committed to keeping the enterprise up and running. You may disagree with their objectives, but you can't help but to marvel at their ingenuity and resourcefulness in defeating spam filters, avoiding being identified, and staying one step ahead of the law. Spam makes up now 64% of all email sent and it is said to be the most annoying part of being online. You'll meet the characters that control the flow of money as well as the hackers and programmers committed to keeping the enterprise up and running. Authored by a former spammer, this is a methodical, technically explicit expose of the innerworkings of the SPAM economy.

A Machine Learning Approach to Phishing Detection and Defense


A Machine Learning Approach to Phishing Detection and Defense
  • Author : Iraj Sadegh Amiri
  • Publisher : Syngress
  • Release : 2014-12-05
  • ISBN : 9780128029466
  • Language : En, Es, Fr & De
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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