Visible to the public Privacy Risk in Cybersecurity Data Sharing

TitlePrivacy Risk in Cybersecurity Data Sharing
Publication TypeConference Paper
Year of Publication2016
AuthorsBhatia, Jaspreet, Breaux, Travis D., Friedberg, Liora, Hibshi, Hanan, Smullen, Daniel
Conference NameProceedings of the 2016 ACM on Workshop on Information Sharing and Collaborative Security
Conference LocationNew York, NY, USA
ISBN Number978-1-4503-4565-1
Keywordscybersecurity data sharing, data usage, Human Behavior, industrial control systems, Metrics, personal privacy, pubcrawl, Resiliency, risk perception, Scalability, threat vectors

As information systems become increasingly interdependent, there is an increased need to share cybersecurity data across government agencies and companies, and within and across industrial sectors. This sharing includes threat, vulnerability and incident reporting data, among other data. For cyberattacks that include sociotechnical vectors, such as phishing or watering hole attacks, this increased sharing could expose customer and employee personal data to increased privacy risk. In the US, privacy risk arises when the government voluntarily receives data from companies without meaningful consent from individuals, or without a lawful procedure that protects an individual's right to due process. In this paper, we describe a study to examine the trade-off between the need for potentially sensitive data, which we call incident data usage, and the perceived privacy risk of sharing that data with the government. The study is comprised of two parts: a data usage estimate built from a survey of 76 security professionals with mean eight years' experience; and a privacy risk estimate that measures privacy risk using an ordinal likelihood scale and nominal data types in factorial vignettes. The privacy risk estimate also factors in data purposes with different levels of societal benefit, including terrorism, imminent threat of death, economic harm, and loss of intellectual property. The results show which data types are high-usage, low-risk versus those that are low-usage, high-risk. We discuss the implications of these results and recommend future work to improve privacy when data must be shared despite the increased risk to privacy.

Citation Keybhatia_privacy_2016