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A Machine-Learni
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免費 USPS Media MailTM.
所在地：Austin, Texas, 美國
送達日期：
估計於 10月16日 (星期四)至 10月20日 (星期一)之間送達 運送地點 94104
退貨：
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物品細節
- 物品狀況
- Series
- Syngress
- Subject Area
- Artificial Intelligence
- Book title
- Title
- Educational Level
- Adult & Further Education
- Level
- Advanced, Technical
- Subject
- Computer Science
- ISBN
- 9780128029275
關於產品
Product Identifiers
Publisher
Elsevier Science & Technology Books
ISBN-10
0128029277
ISBN-13
9780128029275
eBay Product ID (ePID)
208739149
Product Key Features
Number of Pages
100 Pages
Publication Name
Machine-Learning Approach to Phishing Detection and Defense
Language
English
Subject
Internet / General, Intelligence (Ai) & Semantics, Security / General, Security / Networking
Publication Year
2014
Type
Textbook
Subject Area
Computers
Format
Trade Paperback
Dimensions
Item Length
9 in
Item Width
6 in
Additional Product Features
Intended Audience
Scholarly & Professional
TitleLeading
A
Illustrated
Yes
Table Of Content
Introduction Literature Review Research Methodology Feature Extraction Implementation and Result Conclusions
Synopsis
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., 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
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