Callisto: a cryptographic approach to detecting serial perpetrators of sexual misconduct
Files
Accepted manuscript
Date
2018-01-01
Authors
Rajan, Anjana
Qin, Lucy
Archer, David W.
Boneh, Dan
Lepoint, Tancrede
Varia, Mayank
Version
Accepted manuscript
OA Version
Citation
Anjana Rajan, Lucy Qin, David W Archer, Dan Boneh, Tancrede Lepoint, Mayank Varia. 2018. "Callisto: A Cryptographic Approach to Detecting Serial Perpetrators of Sexual Misconduct." PROCEEDINGS OF THE 1ST ACM SIGCAS CONFERENCE ON COMPUTING AND SUSTAINABLE SOCIETIES (COMPASS 2018). 1st ACM SIGCAS Conference on Computing and Sustainable Societies (COMPASS). San Jose, CA, 2018-06-20 - 2018-06-22. https://doi.org/10.1145/3209811.3212699
Abstract
Sexual misconduct is prevalent in workplace and education settings
but stigma and risk of further damage deter many victims from
seeking justice. Callisto, a non-profit that has created an online sexual assault reporting platform for college campuses, is expanding its
work to combat sexual assault and harassment in other industries.
In this new product, users will be invited to an online "matching
escrow" that will detect repeat perpetrators and create pathways
to support for victims. Users submit encrypted data about their
perpetrator, and this data can only be decrypted by the Callisto
Options Counselor (a lawyer), when another user enters the identity of the same perpetrator. If the perpetrator identities match,
both users will be put in touch independently with the Options
Counselor, who will connect them to each other (if appropriate) and
help them determine their best path towards justice. The client relationships with the Options Counselors are structured so that any
client-counselor communications would be privileged. A combination of client-side encryption, encrypted communication channels,
oblivious pseudo-random functions, key federation, and Shamir
Secret Sharing keep data confidential in transit, at rest, and during
the matching process with the guarantee that only the lawyer ever
has access to user submitted data, and even then only when a match
is identified.
Description
License
© 2018 Copyright held by the owner/author(s). Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License