Web: http://arxiv.org/abs/2211.12044

Nov. 23, 2022, 2:20 a.m. | Lu Pang, Tao Sun, Haibin Ling, Chao Chen

cs.CR updates on arXiv.org arxiv.org

Due to the increasing computational demand of Deep Neural Networks (DNNs),
companies and organizations have begun to outsource the training process.
However, the externally trained DNNs can potentially be backdoor attacked. It
is crucial to defend against such attacks, i.e., to postprocess a suspicious
model so that its backdoor behavior is mitigated while its normal prediction
power on clean inputs remain uncompromised. To remove the abnormal backdoor
behavior, existing methods mostly rely on additional labeled clean samples.
However, such requirement …

backdoor data

Operational Technology Cyber Security Consultant

@ PA Consulting | Edinburgh, United Kingdom

Cyber Security Analyst I

@ Humanity | Cincinnati, OH, United States

IT Security Analyst Specialist

@ Humanity | Phoenix, AZ, United States

IT Security Analyst Senior

@ Humanity | Phoenix, AZ, United States

Managed Network Detection & Response Analyst (REMOTE)

@ Arista Networks | Vancouver, BC, Canada

Director, Next Generation Firewall Customer Success

@ Palo Alto Networks | Raleigh, NC, United States

Cyber Security engineer

@ LACROIX | Rennes, France

Cyber Security Engineer(台北)

@ SGS | Taipei, Taiwan

Duales Studium Elektrotechnik mit Schwerpunkt Cyber Security (w/m/div.) - anteilig remote

@ Bosch Group | Rülzheim, Germany

Cloud Security Controls Expert

@ PA Consulting | London, United Kingdom

Cybersecurity Audit Manager

@ ServiceNow | Santa Clara, CALIFORNIA, United States

Security Solution Administrator - Platform Operation (REF1249B)

@ Deutsche Telekom IT Solutions | Pécs, Budapest, Szeged, Debrecen, Hungary