Understanding social engineering based scams. (2016)
- Record Type:
- Book
- Title:
- Understanding social engineering based scams. (2016)
- Main Title:
- Understanding social engineering based scams
- Further Information:
- Note: Markus Jakobsson, editor.
- Other Names:
- Jakobsson, Markus
- Contents:
- About the Editor and Contributors; Contributors; Contributor Bios; Contents; An Overview of the Scam Problem ; About Scams and This Book; About This Book; References; 1 Scams and Targeting; 1.1 Yields and Targeting; 1.2 Understanding Yields and Trends; References; Part I Identifying Trends; 2 Identifying Scams and Trends; 2.1 Gathering Hundreds of Thousands of Scam Messages; 2.2 Taxonomy of Scam Emails; 2.2.1 Non-Targeted Scams; 2.2.2 Targeted Scams; 2.2.3 Scams that Are Both Non-targeted and Targeted; 2.2.4 Miscellaneous Scams; 2.3 Scam Classification; 2.4 Scam Trends. 2.4.1 Targeted vs. Non-Targeted Scams2.4.2 Scams on the Rise; 2.4.3 Scams in Decline; References; 3 Predicting Trends; 3.1 Vulnerabilities Point to Trends; 3.2 Measuring Credibility; References; Part II Why Do People Fall for Scams?; 4 Persuasion in Scams; 4.1 Persuasion in Emails; 4.2 Principles of Persuasion; 4.2.1 Principles of Persuasion in Scam Categories; 4.2.2 Scam Terms: Trends and Persuasion; 4.2.3 Comparison Between Scam and Legitimate Term Trends; References; Part III Filtering Technology; 5 Traditional Countermeasures to Unwanted Email; 5.1 The History of Spam. 5.2 Anti-Spam Landscape5.3 Content-Based Spam Filtering; 5.4 Blacklisting Approaches; 5.5 Anti-Spoofing Approaches; 5.5.1 DKIM; 5.5.2 SPF; 5.5.3 DMARC; References; 6 Obfuscation in Spam and Scam; 6.1 Confusable Characters and Homograph Scam Attacks; 6.2 How to Test the Attack; 6.3 Detecting Obfuscated Scam; References; 7 Semantic AnalysisAbout the Editor and Contributors; Contributors; Contributor Bios; Contents; An Overview of the Scam Problem ; About Scams and This Book; About This Book; References; 1 Scams and Targeting; 1.1 Yields and Targeting; 1.2 Understanding Yields and Trends; References; Part I Identifying Trends; 2 Identifying Scams and Trends; 2.1 Gathering Hundreds of Thousands of Scam Messages; 2.2 Taxonomy of Scam Emails; 2.2.1 Non-Targeted Scams; 2.2.2 Targeted Scams; 2.2.3 Scams that Are Both Non-targeted and Targeted; 2.2.4 Miscellaneous Scams; 2.3 Scam Classification; 2.4 Scam Trends. 2.4.1 Targeted vs. Non-Targeted Scams2.4.2 Scams on the Rise; 2.4.3 Scams in Decline; References; 3 Predicting Trends; 3.1 Vulnerabilities Point to Trends; 3.2 Measuring Credibility; References; Part II Why Do People Fall for Scams?; 4 Persuasion in Scams; 4.1 Persuasion in Emails; 4.2 Principles of Persuasion; 4.2.1 Principles of Persuasion in Scam Categories; 4.2.2 Scam Terms: Trends and Persuasion; 4.2.3 Comparison Between Scam and Legitimate Term Trends; References; Part III Filtering Technology; 5 Traditional Countermeasures to Unwanted Email; 5.1 The History of Spam. 5.2 Anti-Spam Landscape5.3 Content-Based Spam Filtering; 5.4 Blacklisting Approaches; 5.5 Anti-Spoofing Approaches; 5.5.1 DKIM; 5.5.2 SPF; 5.5.3 DMARC; References; 6 Obfuscation in Spam and Scam; 6.1 Confusable Characters and Homograph Scam Attacks; 6.2 How to Test the Attack; 6.3 Detecting Obfuscated Scam; References; 7 Semantic Analysis of Messages; 7.1 Example: Stranded Traveler Scams; 7.2 Detecting Storylines; 7.3 Detecting Brand Abuse; Part IV Understanding the Problem Starts with Measuring It; 8 Case Study: Sales Scams; 8.1 The Automated Honeypot Ad System; 8.1.1 Magnetic Honeypot Ads. 8.1.2 Automated Communication with Scammers8.2 Automated Scammer Interaction; 8.3 Where Are the Scammers?; 8.3.1 Collected Emails and Threads; 8.3.2 IP Addresses; 8.3.3 Email Accounts; 8.3.4 Shipping Addresses and Phone Numbers; 8.3.5 Attribution: Performing Scammer Group Classification; 8.4 Discussion; 9 Case Study: Rental Scams; 9.1 Dataset; 9.1.1 Rental Listing Crawling; 9.1.2 Campaign Identification; 9.1.3 Campaign Expansion Phase: Latitudinal; 9.1.4 Campaign Expansion Phase: Longitudinal; 9.1.5 Campaign Summaries; 9.2 Credit Report Rental Scams; 9.2.1 Data Collection. 9.2.2 Dataset Sanity Check9.2.3 Two-Scams-in-One; 9.2.4 In-Depth Analysis; 9.3 Clone Scams; 9.3.1 Data Collection; 9.3.2 In-Depth Analysis of Confirmed Scams; 9.4 Realtor Service Scams; 9.4.1 Data Collection; 9.4.2 American Standard Online; 9.4.3 New Line Equity; 9.4.4 Search Rent to Own; 9.5 Flagged Ad Analysis; References; 10 Case Study: Romance Scams; 10.1 Romance Scams: A Hurtful Crime; 10.2 Collecting Intelligence; 10.3 Romance Scam Taxonomy; 10.3.1 Traditional Romance Scam; 10.3.2 Affiliate Marketing Scam; 10.3.3 Phone Scam; 10.3.4 Simulated Spam Filter Results; 10.4 Filtering Insights. … (more)
- Publisher Details:
- New York, NY : Springer
- Publication Date:
- 2016
- Extent:
- 1 online resource (135 pages)
- Subjects:
- 004.692
004
Computer science
Spam (Electronic mail)
Fraud
COMPUTERS -- Computer Literacy
COMPUTERS -- Computer Science
COMPUTERS -- Data Processing
COMPUTERS -- Hardware -- General
COMPUTERS -- Information Technology
COMPUTERS -- Machine Theory
COMPUTERS -- Reference
Fraud
Spam (Electronic mail)
Computers -- Security -- General
Information retrieval
Coding theory & cryptology
Computer security
Data encryption (Computer science)
Computer security
Electronic books - Languages:
- English
- ISBNs:
- 9781493964574
1493964577 - Related ISBNs:
- 1493964550
9781493964550 - Notes:
- Note: Includes bibliographical references at the end of each chapters and index.
Note: Print version record. - Access Rights:
- Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
- Access Usage:
- Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD.DS.353728
- Ingest File:
- 01_311.xml