GPU & AI Security: A Familiar Landscape

In the age of AI, security remains paramount. While the underlying principles haven't drastically changed since the early 2000s, a solid grasp of application development fundamentals – whether through Microsoft, Apple, or Google courses – will equip you with the knowledge needed to navigate AI security effectively.

Nobody is a code crunching, defense minded, legal expert superhero. Oftentimes managers and office staff are required to set boundaries in a database and directory, and cybersecurity experts take care of the rest.

The tools of the trade are largely the same. AI may offer advantages to both security professionals and threat actors, but in practice, these advancements often balance each other out.

The traditional pillars of cybersecurity still stand strong. Role-based access control (RBAC) defines organizational boundaries and primarily defends against internal threats. Compliance standards like SOC2 and ISO 25000 consistently emphasize RBAC as a core requirement.

With RBAC, companies grant data access based on an individual's legal standing. Employees, contractors, non-employees, insiders, customers under NDA, the general public, and even competitors each have a defined role. These roles dictate access privileges within cloud accounts, and users can hold multiple roles simultaneously. This framework streamlines access revocation, for example, when an employee leaves the company. Furthermore, it ensures compliance with regulations across industries like healthcare, patent law, defense, and finance.

Evidence-based security complements RBAC, focusing on technology and cryptography. Systems authenticated and authorized through RBAC leverage evidence-based security to execute their privileges, ensuring that software code applies the correct legal procedures to the appropriate data. The most notable are code signing, and TLS certificates. They ensure that the issuer reviewed the software used.

At the heart of evidence-based security are three cryptographic standards: hashing, and public and private key encryption. Private key encryption excels at scale within closed corporate networks, encrypting internet traffic to restrict access to authorized individuals. Public key encryption enables the signing of documents and files with a private key, allowing anyone to verify the signature using a publicly available key. While computationally intensive, public key encryption serves as a crucial negotiation protocol. Larger datasets and files are then encrypted using a private key established through public key standards. Hashing assigns a unique numerical fingerprint to documents based on their content. Any alteration to the document changes the hash, ensuring that the signed content, training data, or model remains unaltered.

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