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Home » Security Bloggers Network » Security BSides London 2021 – Gabriel Currie’s ‘Ready For (Nearly) Anything: Preparing Your Organisation For A Cyber Incident’

Security BSides London 2021 – Gabriel Currie’s ‘Ready For (Nearly) Anything: Preparing Your Organisation For A Cyber Incident’

by Marc Handelman on January 20, 2022

Our thanks to Security BSides London for publishing their tremendous videos from the Security BSides London 2021 Conference on the organization’s YouTube channel. Enjoy!

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*** This is a Security Bloggers Network syndicated blog from Infosecurity.US authored by Marc Handelman. Read the original post at: https://www.youtube-nocookie.com/embed/5hkvNOrHhIg

January 20, 2022January 20, 2022 Marc Handelman cybersecurity education, defensive security, education, Information Security, Infosec Education, Offensive Security, security, Security BSides London

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Security in AI

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How would you best describe your organization's current stage of securing the use of generative AI in your applications?(Required)

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Average - We have some policies or tools in place.

Advanced - We have some enhanced security protocols specifically tailored for generative AI in our applications.

Very advanced - We have comprehensive, mature, and proactive security solutions for generative AI in our applications.

Have you implemented, or are you planning to implement, zero trust security for the AI your organization uses or develops?(Required)

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Do not use zero trust at all

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What are the three biggest challenges your organization faces when integrating generative AI into applications or workflows? (Select up to three)(Required)

Integration capabilities of current systems

Data security or privacy

Potential impacts on performance or scalability of the applications

Security of prompts or responses

Cost to implement

Lack of expertise or experience

Compliance with standards and regulations

Potential impacts on performance or scalability of the AI

Intellectual property protection

Access security

How does your organization secure proprietary information used in AI training, tuning, or retrieval-augmented generation (RAG)? (Select all that apply)(Required)

Encryption at rest

Encryption in transit

Data access control, monitoring

Data anonymization

Data/information isolation

Data masking/tokenization

Data governance policies

Zero trust / continuous authentication and authorization

No specific measures in place

Which of the following kinds of tools are you currently using to secure your organization’s use of generative AI? (select all that apply)(Required)

Native cloud service tools (AWS Guardrails, e.g.)

Third-party tools

Custom in-house tools

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How valuable do you think it would it be to have a solution that classifies and quantifies risks associated with generative AI tools?(Required)

Extremely valuable

Very valuable

Somewhat valuable

Not valuable

What are, or do you think would be, the most important reasons for implementing generative AI security measures? (Select up to three)(Required)

Regulatory compliance

Protecting intellectual property

Mitigating potential data breaches

Maintaining customer trust

Competitive advantage

Improved risk management

Increased operational efficiency

Don’t know

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