TY - GEN
T1 - Quacky
T2 - 37th IEEE/ACM International Conference on Automated Software Engineering, ASE 2022
AU - Eiers, William
AU - Sankaran, Ganesh
AU - Li, Albert
AU - O'Mahony, Emily
AU - Prince, Benjamin
AU - Bultan, Tevfik
N1 - Publisher Copyright:
© 2022 Owner/Author.
PY - 2022/9/19
Y1 - 2022/9/19
N2 - Quacky is a tool for quantifying permissiveness of access control policies in the cloud. Given a policy, Quacky translates it into a SMT formula and uses a model counting constraint solver to quantify permissiveness. When given multiple policies, Quacky not only determines which policy is more permissive, but also quantifies the relative permissiveness between the policies. With Quacky, policy authors can automatically analyze complex policies, helping them ensure that there is no unintended access to private data. Quacky supports access control policies written in the Amazon Web Services (AWS) Identity and Access Management (IAM), Microsoft Azure, and Google Cloud Platform (GCP) policy languages. It has command-line and web interfaces. It is open-source and available at https://github.com/vlab-cs-ucsb/quacky. Video URL: https://youtu.be/YsiGOI-SCtg.
AB - Quacky is a tool for quantifying permissiveness of access control policies in the cloud. Given a policy, Quacky translates it into a SMT formula and uses a model counting constraint solver to quantify permissiveness. When given multiple policies, Quacky not only determines which policy is more permissive, but also quantifies the relative permissiveness between the policies. With Quacky, policy authors can automatically analyze complex policies, helping them ensure that there is no unintended access to private data. Quacky supports access control policies written in the Amazon Web Services (AWS) Identity and Access Management (IAM), Microsoft Azure, and Google Cloud Platform (GCP) policy languages. It has command-line and web interfaces. It is open-source and available at https://github.com/vlab-cs-ucsb/quacky. Video URL: https://youtu.be/YsiGOI-SCtg.
UR - http://www.scopus.com/inward/record.url?scp=85146918626&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85146918626&partnerID=8YFLogxK
U2 - 10.1145/3551349.3559530
DO - 10.1145/3551349.3559530
M3 - Conference contribution
AN - SCOPUS:85146918626
T3 - ACM International Conference Proceeding Series
BT - 37th IEEE/ACM International Conference on Automated Software Engineering, ASE 2022
A2 - Aehnelt, Mario
A2 - Kirste, Thomas
Y2 - 10 October 2022 through 14 October 2022
ER -