Vaibhav Gusain, Douglas Leith, Improving Privacy Benefits of Redaction, ESANN, 2025, pp1 - 8,
Conference Paper,
PUBLISHED
URL
|
Sulthana Shams, Douglas Leith, Evaluating Impact of User-Cluster Targeted Attacks in Matrix Factorisation Recommenders, ACM Transactions on Recommender Systems, 3, (2), 2025, p1-34 ,
Journal Article,
PUBLISHED
DOI
|
Mohamed Suliman and Swanand Kadhe and Anisa Halimi and Douglas Leith and Nathalie Baracaldo and Ambrish Rawat, Data Forging Is Harder Than You Think, ICLR Workshop on Privacy Regulation and Protection in Machine Learning, 2024, pp1-8 ,
Conference Paper,
PUBLISHED
URL
|
Mohamed Suliman, Douglas Leith, Two Models are Better Than One: Federated Learning is Not Private for Google GBoard Next Word Prediction, ESORICS, 2024, pp105-122 ,
Conference Paper,
PUBLISHED
DOI
|
Vaibhav Gusain, Douglas Leith, Plausible Deniability of Redacted Text, ESORICS, 2024, pp1-8 ,
Conference Paper,
PUBLISHED
URL
|
Dilina Rajapakse, Douglas Leith, A Good State Estimator Can Yield A Simple Recommender: A Reinforcement Learning Perspective, CIKM, 2024, pp1-8 ,
Conference Paper,
PUBLISHED
URL
|
What Data Do the Google Dialer and Messages Apps on Android Send to Google? in, Springer Nature Switzerland, 2023, pp549-568 , [Leith, Douglas J.],
Book Chapter,
PUBLISHED
DOI
|
Liu, Haoyu, Leith, Douglas J., Patras, Paul, Android OS Privacy Under the Loupe -- A Tale from the East, WiSec', ACM, 2023, pp1 - 8,
Conference Paper,
PUBLISHED
DOI
|
Vaibhav Gusain and Douglas J. Leith, Towards Quantifying The Privacy Of Redacted Text, ECIR, 2023, pp1 - 8,
Conference Paper,
PUBLISHED
DOI
URL
|
Mohamed Suliman, Douglas Leith, Anisa Halimi, Re-evaluating the Privacy Benefit of Federated Learning, ECML-PKDD, 2023, pp1 - 8,
Conference Paper,
PUBLISHED
URL
|
|