Abstract
Social engineering (as used by the military or law-enforcement) is the emerging technique for obtaining classified information by interacting and deceiving people who can access that information. Rather than using traditional techniques of attacking the technical shields such as firewalls, many sophisticated computer hackers find that social engineering is more effective and difficult to detect by humans. Why can people not effectively detect social engineering or more specifically, the art of deception? What can be done to augment human abilities for the task? The current findings warrant several possibilities that influence human ability to detect deception. Factors include such things as truth-bias, stereotypical thinking and processing ability. Knowing that human detection ability is limited, we propose a method to automatically detect deception that potentially assists humans. Results show that a system, using discriminant analysis to classify deception performed significantly better than humans in detecting deception. The findings can also be applied to general situations to ensure information authentication-scenarios other than social engineering.
| Original language | English (US) |
|---|---|
| Title of host publication | ISI 2007: 2007 IEEE Intelligence and Security Informatics |
| Pages | 152-159 |
| Number of pages | 8 |
| State | Published - 2007 |
| Event | ISI 2007: 2007 IEEE Intelligence and Security Informatics - New Brunswick, NJ, United States Duration: May 23 2007 → May 24 2007 |
Other
| Other | ISI 2007: 2007 IEEE Intelligence and Security Informatics |
|---|---|
| Country | United States |
| City | New Brunswick, NJ |
| Period | 5/23/07 → 5/24/07 |
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Keywords
- Automatic deception detection
- Social engineering
ASJC Scopus subject areas
- Computer Science(all)
- Control and Systems Engineering
Cite this
An investigation of heuristics of human judgment in detecting deception and potential implications in countering social engineering. / Qin, Tiantian; Burgoon, Judee K.
ISI 2007: 2007 IEEE Intelligence and Security Informatics. 2007. p. 152-159 4258689.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - An investigation of heuristics of human judgment in detecting deception and potential implications in countering social engineering
AU - Qin, Tiantian
AU - Burgoon, Judee K
PY - 2007
Y1 - 2007
N2 - Social engineering (as used by the military or law-enforcement) is the emerging technique for obtaining classified information by interacting and deceiving people who can access that information. Rather than using traditional techniques of attacking the technical shields such as firewalls, many sophisticated computer hackers find that social engineering is more effective and difficult to detect by humans. Why can people not effectively detect social engineering or more specifically, the art of deception? What can be done to augment human abilities for the task? The current findings warrant several possibilities that influence human ability to detect deception. Factors include such things as truth-bias, stereotypical thinking and processing ability. Knowing that human detection ability is limited, we propose a method to automatically detect deception that potentially assists humans. Results show that a system, using discriminant analysis to classify deception performed significantly better than humans in detecting deception. The findings can also be applied to general situations to ensure information authentication-scenarios other than social engineering.
AB - Social engineering (as used by the military or law-enforcement) is the emerging technique for obtaining classified information by interacting and deceiving people who can access that information. Rather than using traditional techniques of attacking the technical shields such as firewalls, many sophisticated computer hackers find that social engineering is more effective and difficult to detect by humans. Why can people not effectively detect social engineering or more specifically, the art of deception? What can be done to augment human abilities for the task? The current findings warrant several possibilities that influence human ability to detect deception. Factors include such things as truth-bias, stereotypical thinking and processing ability. Knowing that human detection ability is limited, we propose a method to automatically detect deception that potentially assists humans. Results show that a system, using discriminant analysis to classify deception performed significantly better than humans in detecting deception. The findings can also be applied to general situations to ensure information authentication-scenarios other than social engineering.
KW - Automatic deception detection
KW - Social engineering
UR - http://www.scopus.com/inward/record.url?scp=34748869064&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=34748869064&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:34748869064
SN - 1424413303
SN - 9781424413300
SP - 152
EP - 159
BT - ISI 2007: 2007 IEEE Intelligence and Security Informatics
ER -