Progress of Keystroke Dynamics in Deception Research

doi:10.12116/j.issn.1004-5619.2021.110801

Abstract

Abstract:

Traditional polygraph techniques mostly rely on the changes of an individual’s physiological indicators, such as electrodermal activity, heart rate, breath, eye movement and function of neural signals and other indicators. They are easily affected by individual physical conditions, counter-tests, external environment and other aspects, and it is difficult to conduct large-scale screening tests based on the traditional polygraph techniques. The application of keystroke dynamics to polygraph can overcome the shortcomings of the traditional polygraph techniques to a large extend, increase the reliability of polygraph results and promote the validity of legal evidence of polygraph results in forensic practice. This paper introduces keystroke dynamics and its application in deception research. Compared with the traditional polygraph techniques, keystroke dynamics can be used with a relatively wider application range, not only for deception research but also for identity identification, network screening and other large-scale tests. At the same time, the development direction of keystroke dynamics in the field of polygraph is prospected.

Key words: forensic psychiatry, keystroke dynamics, deception, lie detection, keystroke behavior, review

CLC Number:

DF795.3

Tian-yu NAN. Progress of Keystroke Dynamics in Deception Research[J]. Journal of Forensic Medicine, 2022, 38(6): 783-787.

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URL: http://www.fyxzz.cn/EN/10.12116/j.issn.1004-5619.2021.110801

http://www.fyxzz.cn/EN/Y2022/V38/I6/783

References 32

1	张亭玉，张雨青. 说谎行为及其识别的心理学研究[J].心理科学进展，2008，16（4）：651-660.
	ZHANG T Y， ZHANG Y Q. A review on studies of lying and lie-detection[J]. Xinli Kexue Jinzhan，2008，16（4）：651-660.
2	丁晓攀. 欺骗行为的发展及其社会认知神经机制[D].上海：华东师范大学，2012.
	DING X P. The development of spontaneous deception and its social， cognitive， and neural correlates[D]. Shanghai： East China Normal University，2012.
3	张广涛，王力. 浅谈刑事案件中心理测试（多导仪测试）技术的假阳性[J].法制与社会，2014（28）：129-130. doi：10.19387/j.cnki.1009-0592.2014.28.069 .
	ZHANG G T， WANG L. A brief discussion on false positive of psychological test （Polygraph Tests） technology in criminal cases[J]. Fazhi Yu Shehui，2014（28）：129-130.
4	TEH P S， TEOH A B J， YUE S. A survey of keystroke dynamics biometrics[J]. Sci World J，2013，2013：408280. doi：10.1155/2013/408280 .
5	GIOT R， EL-ABED M， ROSENBERGER C. GREYC keystroke： A benchmark for keystroke dynamics biometric systems[C]// 2009 IEEE 3rd International Conference on Biometrics： Theory， Applications， and Systems. Washington， DC， USA，2009. doi：10.1109/BTAS.2009.5339051 .
6	GAINES R S， LISOWSKI W， PRESS S J， et al. Authentication by keystroke timing some preliminary results[R]. Santa Monica， CA： Rand Corporation，1980.
7	OBAIDAT M S， SADOUN B. Verification of computer users using keystroke dynamics[J]. IEEE Trans Syst Man Cybern B Cybern，1997，27（2）：261-269. doi：10.1109/3477.558812 .
8	MONROSE F， RUBIN A. Authentication via keystroke dynamics[C]// Proceedings of the 4th ACM Conference on Computer and Communications Security，1997：48-56. doi：10.1145/266420.266434 .
9	ZHONG Y， DENG Y B， JAIN A K. Keystroke dynamics for user authentication[C]// 2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops. Providence， RI， USA，2012. doi：10.1109/CVPRW.2012.6239225 .
10	RYBNIK M， TABEDZKI M， SAEED K. A keystroke dynamics based system for user identification[C]// 2008 7th Computer Information Systems and Industrial Management Applications，2008. doi：10.1109/CISIM.2008.8 .
11	ZAHID S， SHAHZAD M， KHAYAM S A， et al. Keystroke-based user identification on smart phones[C]// Recent Advances in Intrusion Detection， Proceedings of 12th International Symposium， Saint-Malo， France，2009.
12	SOLANKI R， SHUKLA P. Estimation of the user’s emotional state by keystroke dynamics[J]. Int J Comput Appl，2014，94（13）：21-23. doi：10.5120/16403-6099 .
13	张畅，韩继红，李福林，等. 击键动力学研究综述[J].信息工程大学学报，2020，21（3）：310-315，324. doi：10.3969/j.issn.1671-0673.2020.03.010 .
	ZHANG C， HAN J H， LI F L， et al. Review of keystroke dynamics research[J]. Xinxi Gongcheng Da-xue Xuebao，2020，21（3）：310-315，324.
14	龙永明. 基于用户击键行为的身份识别技术研究[D].长沙：中南大学，2014.
	LONG Y M. Identification technology based on user keystroke behavior research[D]. Changsha： Central South University，2014.
15	GRIMES M， JENKINS J， VALACICH J S. Assessing credibility by monitoring changes in typing behavior： The keystrokes dynamics deception detection model[C]// Proceedings of Hawaii International Conference on Computer and Systems Sciences， Symposium on Rapid Screening Technologies， Deception Detection and Credibility Assessment，2013.
16	MONARO M， GAMBERINI L， SARTORI G. Identity verification using a kinematic memory detection technique[M]// HALE K S， STANNEY K M. Advances in neuroergonomics and cognitive engineering. Switzerland： Springer International Publishing，2016：123-132.
17	JOYCE R， GUPTA G. Identity authentication based on keystroke latencies[J]. Commun ACM，1990，33（2）：168-176. doi：10.1145/75577.75582 .
18	KACHOLIA V， PANDIT S. Biometric authentication using random distributions （BioART）[C]// Canadian IT Security Symposium. Ottawa， Canada，2003.
19	KELLY H. 83 million Facebook accounts are fakes and dupes[EB/OL]. （2012-08-03）[2021-06-30]. .
20	MIHALCEA R， STRAPPARAVA C. The lie detector： Explorations in the automatic recognition of deceptive language[C]// Proceedings of the ACL-IJCNLP 2009 Conference Short Papers， Singapore，2009：309- 312.
21	DERRICK D C， MESERVY T O， JENKINS J L， et al. Detecting deceptive chat-based communication using typing behavior and message cues[J]. ACM Trans Manag Inf Syst，2013，4（2）：1-21. doi：10.1145/2499962.2499967 .
22	OTT M， CHOI Y， CARDIE C， et al. Finding deceptive opinion spam by any stretch of the imagination[C]// Proceedings of the 49th annual meeting of the Association for Computational Linguistics， Portland， Oregon，2011：309-319.
23	MUKHERJEE A， VENKATARAMAN V， LIU B， et al. What yelp fake review filter might be doing?[C]// Proceedings of the Seventh International AAAI Conference on Weblogs and Social Media，2013：409-418.
24	ZHOU L. An empirical investigation of deception behavior in instant messaging[J]. IEEE Trans Prof Commun，2005，48（2）：147-160. doi：10.1109/TPC.2005. 849652 .
25	Sessualità， tra sexting e relazioni online. Gli adolescenti alle prese con il sesso[EB/OL]. （2016-04-25）[2021-06-30]. .
26	王雨华. 基于击键动力学的智能手机身份认证技术研究与实现[D].北京：北京邮电大学，2019.
	WANG Y H. Research and implementation of user authentication on smartphone using keystroke biometrics[D]. Beijing： Beijing University of Posts and Telecommunications，2019.
27	MONARO M， FUGAZZA F I， GAMBERINI L， et al. How human-mouse interaction can accurately detect faked responses about identity[C]// GAMBERINI L， SPAGNOLLI A， JACUCCI G， et al. 5th International Workshop on Symbiotic interaction， Padua， Italy，2016：115-124.
28	黄伟豪. 基于击键动力学的身份认证技术的研究与实现[D].北京：北京邮电大学，2018.
	HUANG W H. Research and implementation of identity authentication technology based on keystroke dynamics[D]. Beijing： Beijing University of Posts and Telecommunications，2018.
29	周爱保，田甜. 心理测试技术方法研究之隐藏信息测试法[J].法制与社会，2021（13）：72-73. doi：10.19387/j.cnki.1009-0592.2021.05.035 .
	ZHOU A B， TIAN T. The research of psychological testing technology： Concealed information test method[J]. Fazhi Yu Shehui，2021（13）：72-73.
30	GAO Z， DIAO W， HUANG Y， et al. Identity authentication based on keystroke dynamics for mobile device users[J]. Pattern Recognit Lett，2021，148：61-67. doi：10.1016/j.patrec.2021.04.019 .
31	芦效峰，张胜飞，伊胜伟. 基于CNN和RNN的自由文本击键模式持续身份认证[J].清华大学学报（自然科学版），2018，58（12）：1072-1078. doi：10.16511/j.cnki.qhdxxb.2018.26.048 .
	LU X F， ZHANG S F， YI S W. Free-text keystroke continuous authentication using CNN and RNN[J]. Qinghua Daxue Xuebao （Science and technology），2018，58（12）：1072-1078.
32	钟意. 基于用户交互行为特征的持续身份认证研究[D].重庆：重庆邮电大学，2019.
	ZHONG Y. Research on continuous authentication based on user interaction behavior feature[D]. Chong-qing： Chongqing University of Posts and Telecommunications，2019.

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