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Dell is expanding its managed services offers to include Machine Learning Operations (the “Service”). The urgency for leveraging data to achieve competitive advantage is driving demand for data science capabilities. In the digital era, businesses must move quickly and drive projects to production. Artificial Intelligence (AI) and Machine Learning (ML) are rapidly gaining momentum to help achieve these objectives. However, rising costs system complexity, operational inefficiencies, and the decentralization of the public cloud create massive roadblocks to success. Maintaining the confidentiality, integrity, and availability of the Service is paramount and a core priority for Dell. Importantly, the overall security of this Service is a shared responsibility between Dell and the customer.
The Service provides a complete, fully tested, validated, and centralized platform for ML workloads, managing the infrastructure, platform, and model life cycle for business. Improved operational efficiencies enable data teams to get models to production and focus more on innovation.
This document describes the security measures used by Dell, designed to secure remote management of the Service. Furthermore, this document defines the shared responsibilities between Dell and the customer as it relates to the Service.
At Dell, cybersecurity is of great importance to us. Our approach to addressing cyber threats and risks is based on an adversary’s perspective. We use the MITRE ATT@CK™ framework, a knowledge base, and model for observed cyber adversary behavior. This framework reflects the various phases of an adversary’s attack life cycle and the platforms they are known to target. Through this approach, we identify what an adversary can do, and define how to protect against the attack vectors in the most effective way to secure the Service.
Layered security is a supplementary approach we use to ensure a security system will leverage the protection in multiple layers, to slow, block, or delay a threat until it can be neutralized.