82 citations · 179 across the 5 of their papers we have counts for
6 papers
SplitOut: Out-of-the-Box Training-Hijacking Detection in Split Learning via Outlier Detection
Ege Erdogan, Unat Teksen, Mehmet Salih Celiktenyildiz +2
Split learning enables efficient and privacy-aware training of a deep neural network by splitting a neural network so that the clients (data holders) compute the first layers and o…
SplitGuard: Detecting and Mitigating Training-Hijacking Attacks in Split Learning
Ege Erdogan, Alptekin Kupcu, A. Ercument Cicek
Distributed deep learning frameworks such as split learning provide great benefits with regards to the computational cost of training deep neural networks and the privacy-aware uti…
UnSplit: Data-Oblivious Model Inversion, Model Stealing, and Label Inference Attacks Against Split Learning
Ege Erdogan, Alptekin Kupcu, A. Ercument Cicek
Training deep neural networks often forces users to work in a distributed or outsourced setting, accompanied with privacy concerns. Split learning aims to address this concern by d…
Genome Reconstruction Attacks Against Genomic Data-Sharing Beacons
Kerem Ayoz, Erman Ayday, A. Ercument Cicek
Sharing genome data in a privacy-preserving way stands as a major bottleneck in front of the scientific progress promised by the big data era in genomics. A community-driven protoc…
Apollo: A Sequencing-Technology-Independent, Scalable, and Accurate Assembly Polishing Algorithm
Can Firtina, Jeremie S. Kim, Mohammed Alser +4
Long reads produced by third-generation sequencing technologies are used to construct an assembly (i.e., the subject's genome), which is further used in downstream genome analysis.…
Privacy-Related Consequences of Turkish Citizen Database Leak
Erin Avllazagaj, Erman Ayday, A. Ercument Cicek
Personal data is collected and stored more than ever by the governments and companies in the digital age. Even though the data is only released after anonymization, deanonymization…