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 - 2007/1/1
Y1 - 2007/1/1
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
U2 - 10.1109/isi.2007.379548
DO - 10.1109/isi.2007.379548
M3 - Conference contribution
AN - SCOPUS:34748869064
SN - 1424413303
SN - 9781424413300
T3 - ISI 2007: 2007 IEEE Intelligence and Security Informatics
SP - 152
EP - 159
BT - ISI 2007
PB - IEEE Computer Society
T2 - ISI 2007: 2007 IEEE Intelligence and Security Informatics
Y2 - 23 May 2007 through 24 May 2007
ER -