TY - GEN
T1 - Nemesis: Combating Abusive Information in Encrypted Messaging with Private Reporting
AU - Lian, Rui
AU - Ming, Yulong
AU - Cai, Chengjun
AU - Zheng, Yifeng
AU - Wang, Cong
AU - Jia, Xiaohua
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
PY - 2024/9
Y1 - 2024/9
N2 - Abusive messages spread rapidly within popular end-to-end encrypted messaging services (EEMSs) due to the inability to conduct content moderation on plaintext messages. This issue has turned EEMSs into breeding grounds for fake news, misinformation, and other viral abusive content. However, enabling the identification of abusive information without careful consideration can compromise the cherished confidentiality feature of EEMSs. To address this issue, we propose Nemesis, a privacy-friendly, user-reporting-based content moderation system for EEMSs. In Nemesis, users can privately report abusive messages, and the system traces the source if the report count exceeds a predefined threshold. Compared to existing systems, Nemesis offers three key advantages: 1) it supports flexible and adaptable thresholds to meet different content moderation needs, 2) it prevents dishonest reporters from disrupting the system, and 3) it better ensures the privacy of all users during the moderation process. Nemesis utilizes lightweight cryptographic techniques to achieve these goals, and evaluation results demonstrate its low overhead in securely identifying abusive messages and tracing their sources in EEMSs.
AB - Abusive messages spread rapidly within popular end-to-end encrypted messaging services (EEMSs) due to the inability to conduct content moderation on plaintext messages. This issue has turned EEMSs into breeding grounds for fake news, misinformation, and other viral abusive content. However, enabling the identification of abusive information without careful consideration can compromise the cherished confidentiality feature of EEMSs. To address this issue, we propose Nemesis, a privacy-friendly, user-reporting-based content moderation system for EEMSs. In Nemesis, users can privately report abusive messages, and the system traces the source if the report count exceeds a predefined threshold. Compared to existing systems, Nemesis offers three key advantages: 1) it supports flexible and adaptable thresholds to meet different content moderation needs, 2) it prevents dishonest reporters from disrupting the system, and 3) it better ensures the privacy of all users during the moderation process. Nemesis utilizes lightweight cryptographic techniques to achieve these goals, and evaluation results demonstrate its low overhead in securely identifying abusive messages and tracing their sources in EEMSs.
KW - Content moderation
KW - End-to-end encryption
KW - Threshold aggregation
UR - http://www.scopus.com/inward/record.url?scp=85204575377&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-70890-9_13
DO - 10.1007/978-3-031-70890-9_13
M3 - Conference article published in proceeding or book
AN - SCOPUS:85204575377
SN - 9783031708893
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 247
EP - 267
BT - Computer Security – ESORICS 2024 - 29th European Symposium on Research in Computer Security, Proceedings
A2 - Garcia-Alfaro, Joaquin
A2 - Kozik, Rafał
A2 - Choraś, Michał
A2 - Katsikas, Sokratis
PB - Springer Science and Business Media Deutschland GmbH
T2 - 29th European Symposium on Research in Computer Security, ESORICS 2024
Y2 - 16 September 2024 through 20 September 2024
ER -