Sasha Romanosky, PhD
A passion for research

Publications | Presentations | Industry Projects 

Greetings!

I research topics on the economics of security and privacy, cyber crime, cyber insurance, and national security. I am a Senior Policy Researcher at the RAND Corporation, a faculty member of the Pardee RAND Graduate School, and an affiliated faculty in the Program on Economics & Privacy at the Antonin Scalia Law School, George Mason University. My research has appeared in journals such as the Journal of Policy Analysis and Management, the Journal of Empirical Legal Studies, the Journal of Cybersecurity, the Journal of National Security Law and Policy, the Berkeley Technology Law Journal, International Journal of Intelligence and CounterIntelligence, and ACM's Digital Threats: Research and Practice (DTRAP).

I earned a Ph.D. in Public Policy and Management from Carnegie Mellon University and a B.S. in Electrical Engineering from the University of Calgary, Canada. I was a Microsoft research fellow in the Information Law Institute at New York University School of Law, and a security professional for over 10 years in the financial and e-commerce industries. In addition, I am one of the original authors of the Common Vulnerability Scoring System (CVSS), an international standard for scoring computer vulnerabilities, and a co-creator of the Exploit Probability Scoring System (EPSS), an emerging standard for estimating the probability of a vulnerability being exploited in the wild.

It was my pleasure and honor to serve as a Cyber Policy Advisor in the Office of the Secretary of Defense for Policy (OSDP) at the Pentagon, where I oversaw the Defense Department's Vulnerability Equities Process (VEP), the Vulnerability Disclosure Program (VDP), and other cyber policy matters, for which I received the Defense Medal for Exceptional Public Service.


I can be reached at sasha.romanosky [at] gmail.com.


Academic Research

My research is motivated by the surge in social media, cloud computing, and mobile services that is fuelling the unprecedented collection, use and sale of personal consumer information. These opportunities for use of big data afford many benefits to firms, consumers, and government agencies. However individuals can be harmed when their personal information is lost, stolen, or improperly accessed.

In addition to commercial purposes, individual data are used for many kinds of public sector applications such as law enforcement and national security. These surveillance data, whether collected from drones, CCTVs, license plate readers, or other sources, represent an unprecedented opportunity to detect -- and prevent -- malicious activity.

The critical tension, therefore, is in balancing corporate interests, individual privacy rights, law enforcement, and national security. While there are legitimate reasons for limiting the collection, use, or sharing of personal information, excessive restrictions can be inefficient. For example, limiting the types of data that firms can collect may enhance consumer privacy, but may reduce a firm's ability to innovate. Restricted access to medical information may reduce medical fraud, but it may also inhibit important medical research or identify disease outbreaks. Limiting access to location or cloud-based data may hinder the government's ability to investigate serious crimes.

How is consumer data regulated today?
The management of personal consumer information is regulated by many disparate state and federal laws. On one hand, states may prohibit the selling, sharing or public disclosure of personal information. For example, some states specifically prevent the sale of driver tollbooth information, while other states prevent the collection or public notice of social security, zip code, and social media account information. On the other hand, state laws allow, or require, the disclosure of personal information. For example, most states require that companies notify individuals when their personal information has been lost or stolen, while others require consumer notice if a company collects your information with intent to sell it.

But what is the full landscape of state and federal information laws? How can firms continue to innovate despite increasing data restrictions? Do these laws work as intended, or do they introduce perverse outcomes? What consequences and benefits exist for protecting critical infrastructure, and how can these effects be empirically measured?

How do Information Policies work, and how do they reduce externalities?
Legislators often consider a number of alternative policy interventions to help reduce externalities caused by the unauthorized disclosure or collection of information, such as ex ante safety regulation (mandated standards), information disclosure, and ex post liability. Ex ante regulation is often a heavy-handed prevention mechanism that enforces a minimum standard of care. However, its effectiveness is hampered when the regulated inputs are only loosely correlated with the harmful outputs. Disclosure, on the other hand, can be a corrective mechanism that empowers individuals to avoid potential harms. However, cognitive biases may instead burden individuals, preventing them from acting. Finally, ex post liability allows victims to recover any losses through civil litigation, thereby forcing firms to internalize any harm.

But are these interventions effective? How do they drive firm and consumer behaviors, and how do they affect overall social costs?

These issues present many wonderful opportunities for rigorous empirical and inter-disciplinary research in security and privacy, information policy, applied microeconomics, and law & economics.



Publications (click to expand)


Presentations (click to expand)


Industry Projects (click to expand)

Publications | Presentations | Industry Projects