The i in iSensor refers to intelligence. The mission of the iSensor Lab is to discover nuances that support the global and societal commonwealth, particularly concerning cybersecurity, privacy and ethics in cyberspace. iSensor Analytics focuses on sociotechnical systems research in the areas of interpersonal as well as collective trusted human computer interaction and information behavioral factors that impact the stability of society. Adopting social science theories grounded in psychology and communication, iSensor Analytics builds inference engines—based on psychological and physiological features—that detect non-explicit human intent and psychological motivation. Areas of research include:
- Detection of computer-mediated deception such as disinformation and synthetic “deepfake” technologies that influence and distort public opinion
- Cyber forensics investigation of evidence of fraud and insider threat that is created during cloud interaction
- “Hotspot” identification for cyber-bulling or hate speech that impacts freedom of speech
iSensor Analytics currently holds a patent US-17/162,468 on systems and methods for detecting deception in computer-mediated communication. This intelligence sensor system, or i-Sensor, which can comprehend human’s virtual dialogues in Computer Mediated Communications (CMC), focuses on processing those dialogues to understand trustworthiness detected among humans in a virtual collaborative group. iSensor Analytics also has a copyrighted invention (TechID 21-003); CV19 Self Defense mHealth intervention that helps mobile phone users with situational awareness during a pandemic.
Using online games to simulate threat situations helps to generate rich data that can offer insights into complex security problems. This predictive approach formulates a novel understanding of insider threats, providing contemporary ways of understanding anomalous behavior in virtual space, and thus contributing to cyber infrastructure security.
Experiments were conducted using online team-based game-playing. This study endeavored to re-create realistic situations in which human sensors have the opportunity to observe changes in the behavior of a focal individual. Transcripts of communications were examined to recognize how human sensors attribute meaning. Results of this study show that observed changes in behavior can identify a downward shift in the trustworthiness of a critical member. Human sensors triggered a two-stage recursive attribution mechanism to make sense of suspicious behavior. The contributions of this socio-technical study lie in its capability to tackle complex insider threat problems by adopting a social psychological theory on predicting human trustworthiness in a virtual collaborative environment. The two-stage recursive attribution mechanism contributes to the behavioral anomaly detection computational modeling of intelligence sensor in virtual worlds.
Future research: Continuing the effort of building education and research capacity in ubiquitous secure technology. iSensor Lab purposefully seeks to utilize existing resources, strengths, and the efforts of the University’s members, students, and research participants, to pursue sociotechnical research with rigor and relevance, and to develop a simulated virtual lab to study human interaction during crisis management in the virtual world. This initial development effort will include a set of crisis and emergency scenarios that guide virtual participants to collaborate and coordinate as virtual teams to respond in disaster situations. Interaction will be monitored and studied to understand the patterns of coordinated relationships that emerge during crisis. Virtual participants will include scientists, government agencies, intelligence community, members of emergency response teams in physical context, as well as geographically dispersed corporations and organizations.
These projects are researched and developed by Dr. Shuyuan Mary Ho Metcalfe.