Security and Governance Framework for GenAI

Security and Governance Framework for GenAI | Protect GenAI

Unleash the power of Generative AI safely! Discover how Generative AI Security Frameworks, Governance Frameworks, and Guardrails can protect your GenAI projects. Learn proven approaches and access resources (slides) to ensure responsible and secure GenAI development and deployment.

Generative AI, with its immense potential, requires robust security frameworks to mitigate risks. Here's a quick breakdown of key elements:

Generative AI Security Framework: This framework outlines best practices for securing generative AI systems throughout their lifecycle, from data collection to deployment. It addresses concerns like model manipulation, bias, and adversarial attacks. A good example is Google's Secure AI Framework SAIF which focuses on building secure-by-default generative AI.

Governance Framework: This framework establishes policies and procedures for the responsible development and use of generative AI. It ensures compliance with regulations and ethical considerations. Think of it as the rulebook for generative AI projects.

Guardrails: These are specific controls within the governance framework that limit or prevent risky behaviors. Imagine guardrails on a bridge - they provide boundaries to keep generative AI use on track. They might include things like data access restrictions or bias detection algorithms.

Security Framework - For Gen AI

Identify attack Surface & Define Action Plan For Security

Establish AI Governance across enterprise. Have action plan to secure data, infrastructure and Model. See more details by clicking on slides

Governace for GenAI LLM and Chatbots | governance Framework for GenAI

Trustyworthy and reliable LLM and GenAI

We recognize the immense potential of LLMs to revolutionize various aspects of our lives. However, we also acknowledge the critical need to ensure their development and deployment are guided by ethical principles and safeguard human values. Above are guiding principles and framework for AI. It is further extended for GenAI. Click to see detail slides for personalziation, automation and creative scenario to specific governance items

Guardrails for GenAI LLM and Chatbots

Safety for LLM and GenAI

Guardrails are essentially guidelines and controls that steer the LLM's outputs in the desired direction.

Here are some ways to keep your LLM on track:

Input Validation: Set criteria for what kind of information the LLM can process, preventing nonsensical or malicious inputs.
Output Filtering: Review and potentially edit the LLM's outputs before they are used, catching any biases or factual errors.
Real-time Monitoring: Continuously track how the LLM is being used and intervene if it generates harmful content.
Human oversight: Ensure humans are always involved in the LLM interaction

build Data Products using GenAI

Data Products build Right From Start

Dataknobs capablities - KREATE, KONTROLS and KNOBS.
KREATE focus on creatibvity and generation
KONTROLS provide guardrails, lineage, compliance, privacy and security.
KNOBS enable experimentation and diagnosis

Governence Security and Compliance

Gen AI Attack Surface

How Dataknobs identify GenAI attack surface

Data Poison : Malacious actor can temper with training data to corrupt AI and Gen AI models.

Prompt Injection : Attackers craft special instruction disguisd as regular prompts.

Data Source Attack: Attacker can attack and hack data sources.

Attack on Model: Attacker can analyze input , output pair to train a surrogate model.

What to Secure - GenAI

How Dataknobs protects

Secure e2e infra

Secure the prompts, validate input.

Secure APIs to ensure attacker does not get to your data

Apply Modration in prompts

Secure your model - regularly check for data poison, model behavior change

Action Plan for Gen AI Security

Build Action Plan with us for GenAI safety

Establish AI governance

Validate Infra Security

Validate Data Security

Validate Model Security

Check Prompt, Input, LLM Usage Security

Develop data products with KREATE, KONTROLS and KNOBS

Innovate with responsibility

KREATE - Create What matters - data,content, User interface, AI Assistant & Application

KONTROLS - Focus on guardrails, safety, security, governance, lineage. Add right controls in creation process

KNOBS - Enable Diagnostic and Experimentation in creation and appying controls.

Why Kontrols matters

Control GenAI and AI output

GenAI create new trajectories of data. It may produce unwanted output.

Apply controls to check facts and avoid producing incorrect answers.

Apply controls to produce output that is natural.

Produce responses as per law and governace policies.

Why Knobs matter

Knobs are levers using which you manage output

See Drivetrain appproach for building data product, AI product. It has 4 steps and levers are key to success. Knobs are abstract mechanism on input that you can control.