Dataset Groups Activity Stream Defensive ML: Defending Architectural Side-channels with Adversarial Obfuscation The dataset used in the paper is a memory contention side-channel attack and an application power side-channel attack. BibTex: @dataset{Hyoungwook_Nam_and_Raghavendra_Pradyumna_Pothukuchi_and_Bo_Li_and_Nam_Sung_Kim_and_Josep_Torrellas_2024, abstract = {The dataset used in the paper is a memory contention side-channel attack and an application power side-channel attack.}, author = {Hyoungwook Nam and Raghavendra Pradyumna Pothukuchi and Bo Li and Nam Sung Kim and Josep Torrellas}, doi = {10.57702/wkju01ki}, institution = {No Organization}, keyword = {'application power', 'machine learning', 'memory contention', 'side-channel attacks'}, month = {dec}, publisher = {TIB}, title = {Defensive ML: Defending Architectural Side-channels with Adversarial Obfuscation}, url = {https://service.tib.eu/ldmservice/dataset/defensive-ml--defending-architectural-side-channels-with-adversarial-obfuscation}, year = {2024} }
