Intellectual Contributions: Journal Articles
F. Grossman, C. Tappert, J. Bergin, and S.M. Merritt, "A Research Doctorate for Computing Professionals," Communications of the ACM, Vol 54, No 4, 2011, pp 133-141
Kim, C., Tao, W., Shin, N., and Kim, K. “An Empirical Study of Consumers’ Perceptions of Security and Trust in e-Payment Systems.” Electronic Commerce Research and Applications, vol. 9, no. 1, January-February 2010, pp. 84-95.
Abstract— It is commonly believed that good security improves trust, and that the perceptions of good security and trust will ultimately increase the use of electronic commerce. In fact, customers’ perceptions of the security of e-payment systems have become a major factor in the evolution of electronic commerce in markets. In this paper, we examine issues related to e-payment security from the viewpoint of customers. This study proposes a conceptual model that delineates the determinants of consumers’ perceived security and perceived trust, as well as the effects of perceived security and perceived trust on the use of e-payment systems. To test the model, structural equation modeling is employed to analyze data collected from 219 respondents in Korea. This research provides a theoretical foundation for academics and also practical guidelines for service providers in dealing with the security aspects of e-payment systems.
C.C. Tappert, S. Cha, M. Villani, and R.S. Zack, "A Keystroke Biometric System for Long-Text Input," Int. J. Info. Security and Privacy (IJISP), Vol 4, No 1, 2010, pp 32-60.
S. Choi, S. Cha, and C. C. Tappert, "A Survey of Binary Similarity and Distance Measures," Journal of Systemics, Cybernetics and Informatics, Vol 8, No 1, 2010, pp 43-48.
Hayes, D. R., Qureshi, S., & Reddy, V. The Impact of Microsoft’s Windows 7 on Computer Forensics Examinations. LISAT Conference Proceedings, Farmingdale: IEEE. 2010
Abstract— Windows 7 is a new operating system and, like any new technical environment, it has notable implications for computer forensics examiners. The impact of this new operating system will not be as dramatic as the move from Windows XP to Windows Vista. However, changes to this operating system mirror many changes in consumer usage of technology and present both opportunities and challenges for investigators.
Arguably, the most important challenge to computer forensics examiners is access to the suspect’s files on a computer. The introduction of BitLocker, which debuted with Microsoft’s Vista operating system, provided a major barrier to investigators because this encryption tool could encrypt at the file, folder or drive level. Further advances to this tool in Windows 7 create even greater barriers to access; Microsoft’s BitLocker To Go now goes beyond just hard drive encryption but also encrypts a system’s associated devices.
This research will also identify changes, which were introduced with Windows 7, and in response to a shift in consumer demand. The most notable shift in consumer demand, found by the authors of this research, is in Microsoft’s integrated touch-screen capabilities.
Claude Turner, Anthony Joseph, and Dwight Richards, “An Empirical Study of a Wavelet-Neural Network Based Approach for Forensic Speaker Recognition with Cross Channel Data,” in C. Dagli, editor, Intelligent Engineering Systems Through Artificial Neural Networks: Computational Intelligence in Architecting Complex Engineering Systems -- Proceedings of the Artificial Neural Networks in Engineering (ANNIE) 20th Anniversary Conference, November 1-3, 2010, ASME Press, Vol. 20, pp. 445-452.
Abstract— This paper presents a neural network and wavelet based approach for forensic speaker recognition with cross channel data. We discuss our algorithm and provide a performance comparison between the proposed system and a cepstral feature extraction and Gaussian mixture model (GMM) based approach. Our results show that the proposed system performs as well as or better than the cepstral-GMM based model for semi-text-dependent speech and the same set of six speakers from the TIMIT and CTIMIT corpora.
S. Cha and C.C. Tappert, "A Genetic Algorithm for Constructing Compact Binary Decision Trees," J. Pattern Recognition Research (JPRR), Vol 4, No 1, 2009, pp 1-13.
Hayes, D. R., & Qureshi, S. A Framework for Computer Forensics Investigations Involving Microsoft Vista. LISAT Conference Proceedings, Farmingdale: IEEE. 2008
Abstract— The technical environment continues to change and impact the work of digital investigations. This research provides a framework within which computer forensics investigators can take advantage of new or different types of evidence from Microsoft’s Vista operating system (“Vista”). Moreover, this paper will also indicate the many challenges that investigators will encounter when faced with the Vista platform. The focus herein will be on changes associated with new security, encryption and file restoration features. These features vary according to the version of Vista and these differences will also be discussed. This research will also detail the integrity of data recovery procedures through detailed experiments used to identify how data could be manipulated by a perpetrator in Vista as compared to previous versions of Microsoft’s operating systems. Ultimately, this paper will indicate that enhancements in security and encryption associated with Encrypted File System (EFS) as well as BitLocker Drive Encryption are very problematic for investigators. Vista has serious implications for computer forensics investigations. Nevertheless, this research will guide the digital investigator through the labyrinth of new challenges, to effect a more thorough investigation of digital evidence.
Benjamin, D. Paul, "Using A Cognitive Architecture to Automate Cyberdefense Reasoning", with Partha Pal, Franklin Webber, Paul Rubel, Mike Atigetchi, Proceedings of the 2008 ECSIS Symposium onBio-inspired, Learning, and Intelligent Systems for Security (BLISS 2008), IEEE Computer Society, August 4-6, 2008, Edinburgh, Scotland.
Abstract— The CSISM project is designing and implementing an automated cyberdefense decision-making mechanism with expert-level ability. CSISM interprets alerts and observations and takes defensive actions to try to ensure the survivability of the computing capability of the network. The project goal is a difficult one: to produce expert-level response in realtime with uncertain and incomplete information. Our approach is to emulate human reasoning and learning abilities by using a cognitive architecture to embody the reasoning of human cyberdefense experts. This paper focuses on the cognitive reasoning component of CSISM
Benjamin, D. Paul, "Automating Cyber-Defense Management", with Partha Pal, Franklin Webber, Michael Atigetchi and Paul Rubel, Proceedings of the 2nd Workshop on Recent Advances in Intrusion-Tolerant Systems (WRAITS08), Glasgow, Scotland, 2008.
Abstract—Last year, we reported  our success in setting a new high-water mark for intrusion tolerance. That success can largely be attributed to our use of a “survivability architecture”, which refers to the organization of a set of concrete defense mechanisms for preventing intrusion, and for detecting and responding to intrusions that cannot be prevented. The system defense-enabled with the DPASA survivability architecture  showed a high level of resistance to sustained attacks by sophisticated adversaries, but needed expert operators to perform the role of an “intelligent control loop”—interpreting the events reported by the survivable system as well as deciding in some cases which defense mechanisms to actuate. We took the position that the survivability architecture must be extended to include part, if not all, of the functionality of the intelligent control loop. This paper is a work in progress report of our current research attempting to introduce a cognitive control loop into survivability architectures.
Anomaly and Specification Based Cognitive Approach for Mission-Level Detection and Response", by Paul Rubel, Partha Pal, Michael Atigetchi, Paul Benjamin and Franklin Webber, 11th International Symposium On Recent Advances In Intrusion Detection (RAID 2008), Boston, MA, September 15-17, 2008. Also published in Recent Advances in Intrusion Detection, Lecture Notes in Computer Science, Vol. 5230/2008, pp. 408-409.
Abstract— In 2005 a survivable system we built was subjected to redteam evaluation. Analyzing, interpreting, and responding to the defense mechanism reports took a room of developers. In May 2008 we took part in another red-team exercise. During this exercise an autonomous reasoning engine took the place of the room of developers. Our reasoning engine uses anomaly and specification-based approaches to autonomously decide if system and mission availability is in jeopardy, and take necessary corrective actions. This extended abstract presents a brief summary of the reasoning capability we developed: how it categorizes the data into an internal representation and how it uses deductive and coherence based reasoning to decide whether a response is warranted.
Anthony Joseph and Claude Turner, "A Method to Secure More Reliable Online Business Transactions,” Proceedings CD-ROM of the International Conference on Computing and e-Systems, TIGERA-2007, March 12-14, 2007.
Abstract— This article focuses on a methodology designed to strengthen network security at the interface and internally. The proposed method employs forensic testing to complement security testing, thereby using forensic computing to enhance network security. It involves the use of legally sound routine testing and proactive investigation of internal host ports and the network’s informational content to uncover and report forensic information on the network state and performance status as well as to detect, highlight, and grade the criticality of suspicious or potentially suspicious activities before they materialize into serious or costly attacks. Moreover, an unadulterated record of the network's condition and performance status as well as the related results of the data processing and documentation will be stored in a database for future reference, comparative analysis, and for evidentiary purposes in legal proceedings.
Benjamin, D. Paul, "A Cognitive Approach to Intrusion Detection", Proceedings of the IEEE Conference on Computational Intelligence for Security and Defense Applications 2007 (CISDA2007), Honolulu, Hawaii, April 2007
Abstract—The VMSoar project at Pace University is building a cognitive agent for cybersecurity. The project's objective is to create an intelligent agent that can model and understand the activities of users who are on the network, and that can communicate with network administrators in English to alert them to illegal or suspicious activities. VMSoar can understand users' activities because it is capable of performing these activities itself. It knows how to perform both legal and illegal activities, and uses this knowledge to explore simulations of the activity on a network. It can also probe information stored on a machine to assess the legality of past activity. Research in cybersecurity is difficult is due to the extremely large amount of data that must be analyzed to detect illegal activities. In addition, new exploits are developed frequently. Most current projects in this area are attempting to build some level of intelligence into their systems; however, those projects are focusing primarily on statistical data mining approaches. The VMSoar project is unique in its approach to building an intelligent security agent. The VMSoar agent is based on Soar, a mature cognitive architecture that is used in universities and corporations around the world.
S. Cha, S. Yoon, and C.C. Tappert, "Enhancing Binary Feature Vector Similarity Measures," J. Pattern Recognition Research (JPRR), Vol 1, No 1, 2006, pp 63-77.
S. Cha, S. Yoon, and C.C. Tappert, "Handwriting Copybook Style Identification for Questioned Document Examination," J. Forensic Document Examiners (AFDE), Vol 17, 2006, pp 1-16.
C.C. Tappert and S. Cha, Security-Related Research and Projects in Computing Promote Student Awareness of Security Issues, Information Systems Education Journal (ISEDJ), Vol 4, No 82, 2006.
Benjamin, D. Paul, "Semantic Encoding of Relational Databases in Wireless Networks", with Adrian Walker, Proceedings of the SPIE Defense Symposium on Data Mining, Intrusion Detection, Information Assurance and Data Networks Security, Orlando, Florida, March-April 2005.
Abstract— Semantic Encoding is a new, patented technology that greatly increases the speed of transmission of distributed databases over networks, especially over ad hoc wireless networks, while providing a novel method of data security. It reduces bandwidth consumption and storage requirements, while speeding up query processing, encryption and computation of digital signatures. We describe the application of Semantic Encoding in a wireless setting and provide an example of its operation in which a compression of 290:1 would be achieved.
Benjamin, D. Paul, "VMSoar: A Cognitive Agent for Network Security", with Ranjita Shankar-Iyer and Archana Perumal, Proceedings of the SPIE Defense Symposium on Data Mining, Intrusion Detection, Information Assurance and Data Networks Security, Orlando, Florida, March-April 2005.
Abstract— VMSoar is a cognitive network security agent designed for both network configuration and long-term security management. It performs automatic vulnerability assessments by exploring a configuration’s weaknesses and also performs network intrusion detection. VMSoar is built on the Soar cognitive architecture, and benefits from the general cognitive abilities of Soar, including learning from experience, the ability to solve a wide range of complex problems, and use of natural language to interact with humans. The approach used by VMSoar is very different from that taken by other vulnerability assessment or intrusion detection systems. VMSoar performs vulnerability assessments by using VMWare to create a virtual copy of the target machine then attacking the simulated machine with a wide assortment of exploits. VMSoar uses this same ability to perform intrusion detection. When trying to understand a sequence of network packets, VMSoar uses VMWare to make a virtual copy of the local portion of the network and then attempts to generate the observed packets on the simulated network by performing various exploits. This approach is initially slow, but VMSoar’s learning ability significantly speeds up both vulnerability assessment and intrusion detection. This paper describes the design and implementation of VMSoar, and initial experiments with Windows NT and XP.
S. Yoon, S. Choi, S. Cha, Y. Lee, and C.C. Tappert, On the Individuality of the Iris Biometric, Int. J. Graphics, Vision and Image Processing, Vol 5, 2005.
S.M. Merritt, A. Stix, J.E. Sullivan, F. Grossman, C.C. Tappert, and D.A. Sachs, "Developing a Professional Doctorate in Computing: A Fifth Year Assessment," ACM Inroads (SIGCSE Bulletin), Vol 36, No 4, 2004, pp 42-46.
Sung-Hyuk Cha, Charles C. Tappert, Michael Gibbons, and Yi-Min Chee, Automatic Detection of Handwriting Forgery using a Fractal Number Estimate of Wrinkliness, Int. J. Pattern Recognition and Artificial Intelligence, Vol 18, No 7, 2004. pp 1361-1371.
"Evolving Efficient Security Systems Under Budget Constraints Using Genetic Algorithms", Michael L. Gargano, P. Benjamin, W. Edelson, and P. Meisinger, Proc. 34th Southeastern International Conference on Combinatorics, Graph Theory and Computing, 2003.
Abstract—The EASI model (estimate of adversary sequence interruption model) is a dynamic, analytic method widely used by security professionals to evaluate a physical protection security system (pps). Our methods involve using genetic algorithms to evolve such systems when budget constraints or detector sequencing must be considered.
"Undergraduate Cybersecurity Projects", D. Paul Benjamin, Charles Border, Robert Montante, Paul Wagner, SIGCSE2003 Proceedings, Reno, Nevada, 2003.
C.C. Tappert, C.Y. Suen, and T. Wakahara, "The state-of-the-art in on-line handwriting recognition," IEEE Transactions Pattern Analysis Machine Intelligence, Vol 12, August 1990, pp 787-808.
Intellectual Contributions: Book Chapters
C.C. Tappert, M. Villani, and S. Cha, "Keystroke Biometric Identification and Authentication on Long-Text Input," pp 342-367, Chapter 16 in Behavioral Biometrics for Human Identification: Intelligent Applications, Edited by Liang Wang and Xin Geng, Medical Information Science Reference, 2010.
C.C. Tappert and S. Cha, "Handwriting Recognition Interfaces," Chapter 6, pp. 123-137, in Text Entry Systems, Scott MacKenzie and Kumiko Tanaka-Ishii (Eds.), Morgan Kaufmann, 2007.
C.C. Tappert, A.S. Ruocco, K.A. Langdorf, F.J. Mabry, K.J. Heineman, T.A. Brick, D.M. Cross, S.V. Pellissier, and R.C. Kaste, "Military applications of wearable computers and augmented reality," Chapter 20, pp. 625-647, in Fundamentals of Wearable Computers and Augmented Reality, W. Barfield and T. Caudell (Eds.), Lawrence Erlbaum, 2001.
T. Fujisaki, H.S.M. Beigi, C.C. Tappert, M. Ukelson and C.G. Wolf, "Online recognition of unconstrained handprinting: a stroke-based system and its evaluation," in From Pixels to Features III: Frontiers in Handwriting Recognition, S. Impedovo and J.C. Simon (Eds.), Elsevier Science Publishers, pp. 297-312, 1992.
C.C. Tappert, "Speed, accuracy, flexibility trade-offs in on-line character recognition," in Character and Handwriting Recognition, P.S.P. Wang (Ed.), World Scientific, 1991, also Int. J. Pattern Recognition and Artificial Intelligence, Vol. 5, pp. 79-95, June 1991.
T Fujisaki, T.E. Chefalas, J. Kim, C.C. Tappert, and C.G. Wolf, "Online Run-on character recognizer," in Character and Handwriting Recognition, P.S.P. Wang (Ed.), World Scientific, 1991, also Int. J. Pattern Recognition and Artificial Intelligence, Vol. 5, pp. 123-137, June 1991.
Intellectual Property: Patents and Copyrights
T.E. Chefalas and C.C. Tappert, "Silent Training by Error Correction for On-line Handwriting Recognition Systems," U.S. Patent 5,544,260, August 1996.
T.E. Chefalas and C.C. Tappert, " Methods and Apparatus for Evolving a Starter Set of Handwriting Prototypes into a User-specific Set," U.S. Patent 5,319,721, June 1994.
T. Fujisaki, J. Kim, G.J. Leibman, and C.C. Tappert, " On-line Handwriting Recognition Using a Prototype Confusability Dialog," U.S. Patent 5,315,667, May 1994.
T.E. Chefalas and C.C. Tappert, " Elastic Prototype Averaging in Online Handwriting Recognition," U.S. Patent 5,287,415, February 1994.
J. Kim, G.J. Leibman, and C.C. Tappert, " Method and Apparatus for Improving Prototypes of Similar Characters in On-line Handwriting Recognition," U.S. Patent 5,285,505, February 1994.
T.E. Chefalas, T. Fujisaki, J. Kim, and C.C. Tappert, " Robust Prototype Establishment in an On-line Handwriting Recognition System," U.S. Patent 5,121,441, June 1992.
H.A. Ellozy, H.H. Jeanty, and C.C. Tappert, " Handwriting Recognition Employing Pairwise Discriminant Measures," U.S. Patent 5,005,205, April 1991.
C.C. Tappert, "Recognition System for Run-on Handwritten Characters," U.S. Patent 4,731,857, March 1988.
A.S. Fox, E.C. Greanias, J. Kim, and C.C. Tappert, "System for Automatic Adjustment and Editing of Handwritten Text Image," U.S. Patent 4,727,588, February 1988.
(Many technical inventions not patented were published in the IBM Technical Disclosure Bulletin.)
Presentations (Conference Proceedings, Workshop Papers, Technical Reports, Talks and Seminars)
J.V. Monaco, N. Bakelman, S. Cha, and C.C. Tappert, Developing a Keystroke Biometric System for Continual Authentication of Computer Users, Proc. 2012 European Intelligence and Security Informatics Conf., Odense, Denmark, August 2012, pp 210-216.
J.C. Stewart, J.V. Monaco, S. Cha, and C.C. Tappert, "An Investigation of Keystroke and Stylometry Traits," Proc. Int. Joint Conf. Biometrics (IJCB 2011), Washington D.C., Oct 2011.
R.S. Zack, C.C. Tappert and S.-H. Cha, "Performance of a Long-Text-Input Keystroke Biometric Authentication System Using an Improved k-Nearest-Neighbor Classification Method," Proc. IEEE 4th Int Conf Biometrics: Theory, Apps, and Systems (BTAS 2010), Washington, D.C., Sep 2010.
S. Cha, Y. An, and C.C. Tappert, "ROC Curves for Multivariate Biometric Matching Models," Proc. Int. Conf. Artificial Intelligence and Pattern Recognition, Orlando, Florida, July 2010.
S. Choi, S. Cha, and C.C. Tappert, "Correlation Analysis of Binary Similarity and Distance Measures on Different Binary Database Types," Proc. Int Conf Artificial Intelligence and Pattern Recognition (AIPR 2009), Orlando, Florida, July 2009.
S. Choi, S. Cha, and C. Tappert, "A Survey of Binary Similarity and Distance Measures," Proc. 13th World Multiconference on Systemics, Cybernetics and Informatics (WMSCI 2009), Orlando, Florida, July 2009.
S. Cha and C. Tappert, "Constructing Binary Decision Trees Using Genetic Algorithm," Proc. 2008 Int. Conf. Genetic & Evolutionary Methods (GEM 2008), Las Vegas, Nevada, July 2008.
Yanus, R. and Shin, N. “Critical Success Factors for Managing an Information Security Awareness Program,” Proceedings of the 6th ISOneWorld Conference (April 11-13, 2007).
Abstract—While organizations utilize best practices of information security for their technologies, policies and procedures, information security is often compromised by lack of employee awareness. Successful firms understand that information security measures work best when security technology and process controls complement one another. An information security awareness program is made up of security awareness, training and education. It is important to develop a security policy that reflects business needs and inform users of their information security responsibilities. Finally, a process must be in place to monitor, review and update the program when necessary. This research explores factors critical for successfully managing an information security awareness program. It can serve as a framework for technology and security professionals to improve information security.
C. E. Abrams, S. Cha, and C. C. Tappert, "Analyzing Shape Context using the Hamiltonian Cycle," Proc. 7th IAPR Int. Workshop Graphics Recognition, Curitiba, Brazil, Sep 2007.
C.C. Tappert and J.R. Ward, "Pen-Centric Shorthand Handwriting Recognition Interfaces," Proc. 1st Int. Workshop on Pen-Based Learning Technologies, Catania, Italy, May 2007.
C.C. Tappert, M. Villani, M. Curtin, G. Ngo, J. Simone, H. St. Fort, and S. Cha, "Keystroke Biometric Recognition Studies on Long-Text Input over the Internet," Proc. 23rd International Biometric Conf., Montréal, Canada, July 2006.
C.E. Abrams, S. Cha, and C.C. Tappert, "Shape Matching with Ordered Boundary Points Using a Least-Cost Diagonal Method," Proc. Int. Conf. Image Processing, Computer Vision, & Pattern Recognition (IPCV 2006), Las Vegas, June 2006.
M. Curtin, C.C. Tappert, M. Villani, G. Ngo, J. Simone, H. St. Fort, and S. Cha, "Keystroke Biometric Recognition on Long-Text Input: A Feasibility Study," Proc. Int. Workshop Sci Comp/Comp Stat (IWSCCS 2006), Hong Kong, June 2006.
M. Villani, C.C. Tappert, G. Ngo, J. Simone, H. St. Fort, and S. Cha, "Keystroke Biometric Recognition Studies on Long-Text Input under Ideal and Application-Oriented Conditions," Proc. CVPR 2006 Workshop on Biometrics, New York, NY, June 2006.
C.C. Tappert and S. Cha, "Recent Security-Related Research and Projects in CSIS at Pace University," Proc. HTCIA 05 Northeast Regional Conf., Pace Univ., NYC, November 2005.
S. Yoon, S. Choi, S. Cha, Y. Lee, and C.C. Tappert, "On the Individuality of the Iris Biometric," Proc. ICIAR 05, Toronto, Canada, September 2005.
S. Yoon, S. Cha, and C.C. Tappert, "On Binary Similarity Measures for Handwritten Character Recognition," Proc. ICDAR 05, Seoul, Korea, August 2005.
S. Yoon, S. Choi, S. Cha, and C.C. Tappert, "Writer Profiling Using Handwriting Copybook Styles," Proc. ICDAR 05, Seoul, Korea, August 2005.
M. Gibbons, S. Yoon, S. Cha, and C.C. Tappert, "Biometric Identification Generalizability," Proc. Audio- and Video-based Biometric Person Authentication,Rye Brook, NY, July 2005.
S. Yoon, S. Choi, S. Cha, Y. Lee, and C.C. Tappert, "Combining Multiple Iris Biometric Verifiers," Proc. The 9th World Multi-Conference on Systemics, Cybernetics and Informatics,Orlando, FL, July 2005.
B. Ahmed, S. Cha, and C.C. Tappert, "Nationality Identification from Names Using N-Gram Based Cumulative Frequency Addition," Proc. The 9th World Multi-Conference on Systemics, Cybernetics and Informatics,Orlando, FL, July 2005.
G. Bartolacci, M. Curtin, M. Katzenberg, N. Nwana, S. Cha, and C.C. Tappert, "Applying Keystroke Biometrics for User Verification and Identification," Proc. MCSCE,MLMTA, Las Vegas, NV, June 2005.
M. Gibbons, S. Yoon, S. Cha, and C.C. Tappert, "Analyzing Open Biometric Identification Systems," Proc. MCSCE,MLMTA, Las Vegas, NV, June 2005.
A. Evans, J. Sikorski, P. Thomas, S.-H. Cha, C. Tappert, J. Zou, A. Gattani, and G. Nagy, Computer Assisted Visual Interactive Recognition (CAVIAR) Technology, Proc. 2005 Electro/Information Technology (EIT) Conference, EIT 2005, Lincoln, NE, May 2005.
S.-H. Cha, S. Yoon, and C.C. Tappert, "Computer Assisted Handwriting Style Identification in Questioned Document Examination," Proc. Investigative Image Processing III, paper 5685-25, Electronic Imaging 2005, San Jose, CA, January 2005.
C.C. Tappert and S.-H. Cha, "Security-Related Research and Projects in Computing Promote Student Awareness of Security Issues,"Proc. ISECON 2004, Newport, RI, November 2004.
W.B. Huber, S.-H. Cha, C.C. Tappert, and V.L. Hanson, "Use of Chatroom Abbreviations and Shorthand Symbols in Pen Computing," Proc. 9th Int Workshop on Frontiers in Handwriting Recognition, IWFHR 2004, Tokyo, Japan, October 2004.
S.-S. Choi, S. Yoon, S.-H. Cha, and C.C. Tappert, "Use of Histogram Distances in Iris Authentication," Proc. MCSCE 2004MLMTA, Las Vegas, NV, June 2004.
H.-C. Chen, S.-H. Cha, Y.-M. Chee, and C.C. Tappert, "The Detection of Forged Handwriting Using a Fractal Number Estimate of Wrinkliness," Proc. 11th Int. Graphonomics Soc. Conf. (IGS 2003), Scottsdale, AZ, November 2003, pp. 312-315.
S.-H. Cha, C.C. Tappert, and S.N. Srihari, "Optimizing binary feature vector similarity measure using genetic algorithm and handwritten character recognition," Proc. Int. Conf. Document Analysis and Recognition (ICDAR 2003), Edinburgh, Scotland, August 2003, pp. 662-665.
S.-H. Cha and C.C. Tappert, "Automatic Detection of Handwriting Forgery," Proc. 8th Int. Workshop Frontiers Handwriting Recognition (IWFHR-8), Niagara, Canada, August 2002, pp. 264-267.
S.M. Merritt, F. Grossman, C. Tappert, J. Bergin, H. Blum, R. Frank, D. Sachs, A. Stix, and S. Varden, "The Doctor of Professional Studies in Computing: An Innovative Professional Doctoral Program," Proc. 19th Annual Information Systems Educational Conference, ISECON 2001, Novenber 2001.
C.C. Tappert, A.S.Ruocco, K.A. Langdorf, F.J. Mabry, K.J. Heineman, T.A. Brick, D.M. Cross, S.V. Pellissier, and R.C. Kaste, "Wearable Computers: Military Application Areas and Cadet/Faculty Projects," Proc. Fifth Annual U.S. Army ARL/USMA Technical Symposium, pp. 219-237, October 1997.
T.E. Chefalas, J. Kim, and C.C. Tappert, "The IBM ThinkWrite handwriting recognizer," Basic and Applied Issues in Handwriting and Drawing Research: Proc. Seventh Biennial Conf. of Int. Graphonomics Society and Annual Symposium of Assoc. Forensic Document Examiners, London, Ontario, pp. 30-31, Aug 1995.
C.C. Tappert, "Online handwriting recognition with hidden Markov models," Proc. Fifth Handwriting Conf. of the Int. Graphonomics Society, pp. 204-206, Tempe, Arizona, October 1991.
T. Fujisaki, C.C. Tappert, M. Ukelson, and C.G. Wolf, "Online recognition of run-on handwriting," Proc. Int. Workshop on Frontiers in Handwriting Recognition, Chateau de Bonas, France, pp. 205-216, September 1991.
T. Fujisaki, T.E. Chefalas, J. Kim, and C.C. Tappert, "Online recognizer for run-on and printed characters," Proc. IEEE 10th Int. Conf. on Pattern Recognition, pp. 450-454, Atlantic City, NJ, June 1990.
C.C. Tappert, "Rationale for adaptive online handwriting recognition," Proc. Int. Workshop on Frontiers in Handwriting Recognition, pp. 13-22, Montreal, Canada, April 1990.
C.C. Tappert, "A survey of online handwriting recognition," Neural Networks for Computing Conf., Snowbird, Utah, April 1990.