skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.


Title: Eureka!: Advancing Cybersecurity Learning through Inquiry-Based Laboratories
Cybersecurity is rapidly becoming one of the most important industries in the world, in regards to the national, financial, and environmental well-being of every nation. There are currently about half a million cyber attacks every minute, and the attacks will continue to increase in complexity and frequency as hackers adapt their strategies to the ever-changing cyber physical landscape. It is critical to train and educate the future workforce on the fundamental aspects of cyber and mobile security, and to improve their ability to identify, prevent, and respond to emerging threats. The purpose of this paper is to discuss the development of a collection of cybersecurity labs - called Eureka Experiences - designed to teach sophisticated concepts in an engaging, efficient, and affordable virtualization environment. This presentation will also address the future research and development of with these labs, and propose possible strategies for adapting them to a wide range of learners.  more » « less
Award ID(s):
1829553
PAR ID:
10177445
Author(s) / Creator(s):
Date Published:
Journal Name:
Society for Information Technology & Teacher Education International Conference
Volume:
2020
Issue:
1
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. Machine Learning (ML) analyzes, and processes data and discover patterns. In cybersecurity, it effectively analyzes big data from existing cybersecurity attacks and develop proactive strategies to detect current and future cybersecurity attacks. Both ML and cybersecurity are important subjects in computing curriculum, but using ML for cybersecurity is not commonly explored. This paper designs and presents a case study-based portable labware experience built on Google's CoLaboratory (CoLab) for a ML cybersecurity application to provide students with hands-on labs accessing from anywhere and anytime, reducing or eliminating tedious installations and configurations. This approach allows students to focus on learning essential concepts and gaining valuable experience through hands-on problem solving skills. Our preliminary results and student evaluations are reported for a case-based hands-on regression labware in cyber fraud prediction using credit card fraud as an example. 
    more » « less
  2. The imperative factors of cybersecurity within institutions have become prevalent due to the rise of cyber-attacks. Cybercriminals strategically choose their targets and develop several different techniques and tactics that are used to exploit vulnerabilities throughout an entire institution. With the thorough analysis practices being used in recent policy and regulation of cyber incident reports, it has been claimed that data breaches have increased at alarming rates rapidly. Thus, capturing the trends of cyber-attacks strategies, exploited vulnerabilities, and reoccurring patterns as insight to better cybersecurity. This paper seeks to discover the possible threats that influence the relationship between the human component and cybersecurity posture. Along with this, we use the Vocabulary for Event Recording and Incident Sharing (VERIS) database to analyze previous cyber incidents to advance risk management that will benefit the institutional level of cybersecurity. We elaborate on the rising concerns of external versus internal factors that potentially put institutions at risk for exploiting vulnerabilities and conducting an exploratory data analysis that articulates the understanding of detrimental monetary and data loss in recent cyber incidents. The human component of this research attributes to the perceptive of the most common cause within cyber incidents, human error. With these concerns on the rise, we found contributing factors with the use of a risk-based approach and thorough analysis of databases, which will be used to improve the practical consensus of cybersecurity. Our findings can be of use to all institutions in search of useful insight to better their risk-management planning skills and failing elements of their cybersecurity. 
    more » « less
  3. Machine Learning (ML) analyzes, and processes data and develop patterns. In the case of cybersecurity, it helps to better analyze previous cyber attacks and develop proactive strategy to detect and prevent the security threats. Both ML and cybersecurity are important subjects in computing curriculum, but ML for cybersecurity is not well presented there. We design and develop case-study based portable labware on Google CoLab for ML to cybersecurity so that students can access and practice these hands-on labs anywhere and anytime without time tedious installation and configuration which will help students more focus on learning of concepts and getting more experience for hands-on problem solving skills. 
    more » « less
  4. Machine Learning (ML) analyze, and process data and develop patterns. In the case of cybersecurity, it helps to better analyze previous cyber attacks and develop proactive strategy to detect, prevent the security threats. Both ML and cybersecurity are important subjects in computing curriculum but ML for security is not well presented there. We design and develop case-study based portable labware on Google CoLab for ML to cybersecurity so that students can access, share, collaborate, and practice these hands-on labs anywhere and anytime without time tedious installation and configuration which will help students more focus on learning of concepts and getting more experience for hands-on problem solving skills. 
    more » « less
  5. Securing cyber-physical systems (CPS) like the Smart Grid against cyber attacks is making it imperative for the system defenders to plan for investing in the cybersecurity resources of cyber-physical critical infrastructure. Given the constraint of limited resources that can be invested in the cyber layer of the cyber-physical smart grid, optimal allocation of these resources has become a priority for the defenders of the grid. This paper proposes a methodology for optimizing the allocation of resources for the cybersecurity infrastructure in a smart grid using attack-defense trees and game theory. The proposed methodology uses attack-defense trees (ADTs) for analyzing the cyber-attack paths (attacker strategies) within the grid and possible defense strategies to prevent those attacks. The attack-defense strategy space (ADSS) provides a comprehensive list of interactions between the attacker and the defender of the grid. The proposed methodology uses the ADSS from the ADT analysis for a game-theoretic formulation (GTF) of attacker-defender interaction. The GTF allows us to obtain strategies for the defender in order to optimize cybersecurity resource allocation in the smart grid. The implementation of the proposed methodology is validated using a synthetic smart grid model equipped with cyber and physical components depicting the feasibility of the methodology for real-world implementation. 
    more » « less