WBAN Security Management in Healthcare Enterprise Environments

As healthcare data are pushed online, consumers have raised big concerns on the breach of their personal information. Law and regulations have placed businesses and public organizations under obligations to take actions to prevent such data breaches. Various vulnerabilities have been identified in healthcare enterprise environments, in which the Wireless Body Area Networks (WBAN) remains to be a major vulnerability, which can be easily taken advantage of by determined adversaries. Thus, vulnerabilities of WBAN systems and the effective countermeasure mechanisms to secure WBAN are urgently needed. In this research, first, the architecture of WBAN system has been explored, and the vulnerabilities within the system have been identified and analyzed. After that, issues on existing federal regulations related to WBAN are discussed. Finally, scenarios are described where vulnerabilities, threats, and countermeasures are analyzed

Game Based Learning for Safety and Security Education

Safety and security education are important part of technology related education, because of recent number of increase in safety and security related incidents. Game based learning is an emerging and rapidly advancing forms of computer-assisted instruction. Game based learning for safety and security education enables students to learn concepts and skills without the risk of physical injury and security breach. In this paper, a pedestal grinder safety game and physical security game have been developed using industrial standard modeling and game development software. The average score of the knowledge test of grinder safety game was 82%, which is higher than traditional lecture only instruction method. In addition, the survey of physical security game shows 84% average satisfaction ratio from high school students who played the game during the summer camp. The results of these studies indicated that game based learning method can enhance students' learning without potential harm to the students

Forensic Evidence Identification and Modeling for Attacks against a Simulated Online Business Information System

Forensic readiness of business information systems can support future forensics investigation or auditing on external/internal attacks, internal sabotage and espionage, and business fraud. To establish forensics readiness, it is essential for an organization to identify which fingerprints are relevant and where they can be located, to determine whether they are logged in a forensically sound way and whether all the needed fingerprints are available to reconstruct the events successfully. Also, a fingerprint identification and locating mechanism should be provided to guide potential forensics investigation in the future. Furthermore, mechanisms should be established to automate the security incident tracking and reconstruction processes. In this research, external and internal attacks are first modeled as augmented attack trees based on the vulnerabilities of business information systems. Then, modeled attacks are conducted against a honeynet that simulates an online business information system, and a forensic investigation follows each attack. Finally, an evidence tree, which is expected to provide the necessary contextual information to automate the attack tracking and reconstruction process in the future, is built for each attack based on fingerprints identified and located within the system

Data Loss Prevention Management and Control: Inside Activity Incident Monitoring, Identification, and Tracking in Healthcare Enterprise Environments

As healthcare data are pushed online, consumers have raised big concerns on the breach of their personal information. Law and regulations have placed businesses and public organizations under obligations to take actions to prevent data breach. Among various threats, insider threats have been identified to be a major threat on data loss. Thus, effective mechanisms to control insider threats on data loss are urgently needed. The objective of this research is to address data loss prevention challenges in healthcare enterprise environment. First, a novel approach is provided to model internal threat, specifically inside activities. With inside activities modeling, data loss paths and threat vectors are formally described and identified. Then, threat vectors and potential data loss paths have been investigated in a healthcare enterprise environment. Threat vectors have been enumerated and data loss statistics data for some threat vectors have been collected. After that, issues on data loss prevention and inside activity incident identification, tracking, and reconstruction are discussed. Finally, evidences of inside activities are modeled as evidence trees to provide guidance for inside activity identification and reconstruction

On the Development of a Digital Forensics Curriculum

Computer Crime and computer related incidents continue their prevalence and frequency, resulting in losses approaching billions of dollars. To fight against these crimes and frauds, it is urgent to develop digital forensics education programs to train a suitable workforce that can effectively investigate computer crimes and incidents. There is presently no standard to guide the design of digital forensics curriculum for an academic program. In this research, previous work on digital forensics curriculum design and existing education programs are thoroughly investigated. Both digital forensics educators and practitioners were surveyed and results were analyzed to determine the industry and law enforcement need for skills and knowledge for their digital forensic examiners. Based on the survey results and the topics that make up certificate programs in digital forensics, topics that are desired in digital forensics courses are identified. Finally, based on the research findings, six digital forensics courses and required topics are proposed to be offered in both undergraduate and graduate digital forensics programs

Evaluation of Game-Based Learning in Cybersecurity Education for High School Students

Game based learning is a new game play mechanism that the players explore various aspects of game play in a learning context designed by the instructor or the game designer. Nevertheless, general acceptance of game based learning as a new learning paradigm was deferred by a lack of well-controlled, large sample efficacy studies. To address the increasing need of cybersecurity workforce, this paper introduces a game based learning method for high school cybersecurity education. Purdue University Northwest launched GenCyber high school summer camps to about 200 high school students in Chicago metropolitan area. The survey conducted after the summer camp indicated that the game based learning for cybersecurity education was very effective in cybersecurity awareness training. Further analysis of survey data revealed that there is a gender difference in raising students' interests in cybersecurity and computer science education using game based learning method

Forensic Evidence Identification and Modeling for Attacks against a Simulated Online Business Information System

Forensic readiness can support future forensics investigation or auditing on external/internal attacks, internal sabotage and espionage, and business frauds. To establish forensics readiness, it is essential for an organization to identify what evidences are relevant and where they can be found, to determine whether they are logged in a forensic sound way and whether all the needed evidences are available to reconstruct the events successfully.  Our goal of this research is to ensure evidence availability. First, both external and internal attacks are molded as augmented attack trees/graphs based on the system vulnerabilities. Second, modeled attacks are conducted against a honeynet simulating an online business information system, and each honeypot's hard drive is forensic sound imaged for each individual attack. Third, an evidence tree/graph will be built after forensics examination on the disk images for each attack. The evidence trees/graphs are expected to be used for automatic crime scene reconstruction and automatic attack/fraud detection in the future