Aron Laszka is an Associate Professor in the College of Information Sciences and Technology at the Pennsylvania State University. Previously, he was an Assistant Professor at the University of Houston, a Research Assistant Professor at Vanderbilt University, and a Postdoctoral Scholar at the University of California, Berkeley.
His research interests revolve around artificial intelligence and cyber-physical systems, focusing on machine learning for decision making and optimization, with applications in smart and connected communities, critical infrastructure, and cybersecurity.
His research is funded by the National Science Foundation, the Department of Energy, the Department of Transportation, and other agencies.
As the Industrial Internet of Things (IIoT) becomes more ubiquitous in critical application domains, such as smart water-distribution and transportation systems, providing security …
We introduce a game-theoretic model to investigate the strategic interaction between a cyber insurance policyholder whose premium depends on her self-reported security level and an …
In recent years, state-of-the-art traffic-control devices have evolved from standalone hardware to networked smart devices. Smart traffic control enables operators to decrease …
Traffic networks are one of the most critical infrastructures for any community. The increasing integration of smart and connected sensors in traffic networks provides researchers …
In a networked system, any change in the underlying network structure, such as node and link removals due to an attack, could severely affect the overall system behavior. …
Adversaries may cause significant damage to smart infrastructure using malicious attacks. To detect and mitigate these attacks before they can cause physical damage, operators can …
The quantity of personal data that is collected, stored, and subsequently processed continues to grow rapidly. Given its sensitivity, ensuring privacy protections has become a …
Learning enabled components (LECs) trained using data-driven algorithms are increasingly being used in autonomous robots commonly found in factories, hospitals, and educational …
Transactive energy systems (TES) are emerging as a transformative solution for the problems that distribution system operators face due to an increase in the use of distributed …
Many organizations and companies have recently chosen to use so-called bug-bounty programs (also known as vulnerability reward programs), which allow outside security experts to evaluate the security of an organization’s products and services and to report security vulnerabilities in exchange for rewards. Bug-bounty programs provide unique benefits by allowing organizations to publicly signal their commitment to security and to harness the diverse expertise of thousands of security experts in an affordable way. Despite their rapidly growing popularity, bug-bounty programs are not well understood and can be mismanaged. As a result, bug bounty programs can waste substantial resources and they rarely live up to their potential to improve cybersecurity. This project will significantly improve the efficiency of bug-bounty programs by collecting and publishing comprehensive datasets on the bug-bounty ecosystem, by establishing a sound theory of bug-bounty programs, and by providing practical recommendations for organizations and regulators.