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Titlebook: Understanding Social Engineering Based Scams; Markus Jakobsson Book 2016 Springer Science+Business Media New York 2016 419 Scam.Scam.Busin

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发表于 2025-3-21 17:04:11 | 显示全部楼层 |阅读模式
书目名称Understanding Social Engineering Based Scams
编辑Markus Jakobsson
视频video
概述Describes how scams manipulate human principles of persuasion.Suggests tools for measuring messaging credibility, campaign yields, and clustering and locations of scammers.Provides methods for identif
图书封面Titlebook: Understanding Social Engineering Based Scams;  Markus Jakobsson Book 2016 Springer Science+Business Media New York 2016 419 Scam.Scam.Busin
描述.This book describes trends in email scams and offers tools and techniques..to identify such trends. It also describes automated countermeasures..based on an understanding of the type of persuasive methods used by..scammers. It reviews both consumer-facing scams and enterprise scams,..describing in-depth case studies relating to Craigslist scams and Business..Email Compromise Scams. This book provides a good starting point for..practitioners, decision makers and researchers in that it includes..alternatives and complementary tools to the currently deployed email..security tools, with a focus on understanding the metrics of scams...Both professionals working in security and advanced-level students.interested in privacy or applications of computer science will find this book..a useful reference..
出版日期Book 2016
关键词419 Scam; Scam; Business Email Compromise; CEO scam; Nigerian scam; Trends; Fraud; Email; Metric; Applied sec
版次1
doihttps://doi.org/10.1007/978-1-4939-6457-4
isbn_softcover978-1-4939-8206-6
isbn_ebook978-1-4939-6457-4
copyrightSpringer Science+Business Media New York 2016
The information of publication is updating

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978-1-4939-8206-6Springer Science+Business Media New York 2016
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Scams and Targeting,m filters and related technologies, and as such, vastly improves the profits scammers reap. We overview how to estimate the yield of attacks, and how to identify scams that are likely to become more common.
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Predicting Trendsferences in user vulnerabilities. That allows us to quantify vulnerabilities before they are actively abused. By being able to anticipate what fraudsters will be likely to do eventually, it is possible to build countermeasures that address big open vulnerabilities.
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