Feb. 13, 2023, 2:18 a.m. | Rosario Cammarota, Matthias Schunter, Anand Rajan, Fabian Boemer, Ágnes Kiss, Amos Treiber, Christian Weinert, Thomas Schneider, Emmanuel Stapf,

cs.CR updates on arXiv.org arxiv.org

In this work, we provide an industry research view for approaching the
design, deployment, and operation of trustworthy Artificial Intelligence (AI)
inference systems. Such systems provide customers with timely, informed, and
customized inferences to aid their decision, while at the same time utilizing
appropriate security protection mechanisms for AI models. Additionally, such
systems should also use Privacy-Enhancing Technologies (PETs) to protect
customers' data at any time. To approach the subject, we start by introducing
current trends in AI inference systems. …

aid ai models artificial artificial intelligence customers data decision deployment design industry industry research intelligence privacy protect protection research security systems technologies trustworthy ai work

Information Security Engineers

@ D. E. Shaw Research | New York City

Technology Security Analyst

@ Halton Region | Oakville, Ontario, Canada

Senior Cyber Security Analyst

@ Valley Water | San Jose, CA

Technical Support Specialist (Cyber Security)

@ Sigma Software | Warsaw, Poland

OT Security Specialist

@ Adani Group | AHMEDABAD, GUJARAT, India

FS-EGRC-Manager-Cloud Security

@ EY | Bengaluru, KA, IN, 560048