Policy Security Training

Employee Information Security, Sensitive Data Handling, and Responsible AI Awareness Training

1. Purpose and Importance of Information Security

Objective
Protecting company data, customer information, intellectual property, and AI-related datasets.

Why It Matters
Security breaches can lead to:

• Financial losses

• Legal and regulatory issues

• Reputational damage

• Loss of customer trust

Employee Responsibility

• Every employee plays a critical role in information security.

• Must follow established security protocols and best practices.

2. Core Information Security Policies

Data Handling

• Properly classify and handle company data according to the Data Classification Policy.

• Sensitive data — including PII, PHI, payment card data, intellectual property, and proprietary AI datasets — must be handled only on approved, scoped systems.

• Do not download or store sensitive data on personal devices, personal cloud accounts, or non-approved systems.

• Use only company-approved encrypted channels for transmitting sensitive information.

• Follow retention and secure disposal policies for data.

Device Security

• Secure all devices with encryption and regular system updates.

Network Security

• Never connect to unsecured networks.

• Always use VPN when accessing company resources remotely.

Access Control

• Use MFA where required.

• Access only the data necessary to perform your role.

Incident Reporting

• Report immediately to the security team:

  • Suspected security incidents

  • Unusual activities

  • Potential data breaches

3. Phishing and Social Engineering Awareness

Recognizing Phishing Attacks
Common signs include:

• Unexpected requests for sensitive information

• Suspicious links or attachments

• Urgent or threatening language

• Poor grammar and spelling

Types of Phishing Attacks

• Email Phishing: Fraudulent emails from seemingly trusted sources

• Spear Phishing: Targeted attacks using personal/company details

• Smishing: SMS-based phishing

• Vishing: Voice-based phishing (phone calls)

Social Engineering Tactics

• Be vigilant of manipulation attempts to obtain information

• Verify identities through official channels

4. Safe Email Practices

Sender Verification

• Always verify sender email addresses

• Be cautious of similar-looking domains

Link Safety

• Hover over links to preview URLs

• Type URLs directly instead of clicking when unsure

Attachment Handling

• Never open attachments from unknown senders

• Scan attachments with antivirus software

Information Sharing

• Never share sensitive data via email without approved secure channels

5. Mobile and Remote Work Security

Device Protection

• Enable device locks (PIN, biometric)

• Encrypt sensitive data

• Keep devices physically secure

Remote Access

• Always use VPN for company resources

• Avoid public Wi-Fi unless using company-approved security controls

• Use company-approved hotspots

6. Safe Internet Practices

Web Safety

• Only visit trusted websites

• Verify website security (HTTPS)

• Avoid downloading unauthorized software

System Maintenance

• Keep all software updated

• Run regular security scans

• Install security patches promptly

7. Sensitive Data Handling

Scope
Sensitive data includes PII, PHI, payment card data, intellectual property, confidential business data, and AI-related datasets.

Rules

• Store and process only on authorized, scoped systems.

• Do not copy or move data to personal storage, unapproved cloud platforms, or unsecured media.

• When transmitting sensitive data, use company-approved encrypted methods.

• Share sensitive data only with authorized personnel who have a business need to know.

• Follow data minimization principles — use only the data necessary for the task.

8. Responsible AI Usage

Purpose
Ensure AI usage aligns with security, ethics, and compliance requirements.

Guidelines

• Authorized Systems Only: Handle AI training datasets, prompts, or outputs containing sensitive data only on approved, scoped systems.

• No Unauthorized Uploads: Never input proprietary or customer-related data into public AI tools without written approval.

• Bias & Fairness: Follow responsible AI guidelines to prevent discrimination in AI outputs.

• Privacy Compliance: Adhere to GDPR, CCPA, HIPAA, PCI DSS, and other applicable laws when working with AI datasets.

• Model Security: Protect AI models and related datasets against theft, misuse, or unauthorized sharing.

• Data Minimization: Use only the minimum amount of data needed for AI training or inference.

9. Incident Response and Reporting

Response Protocol

• Stop work immediately if a breach is suspected

• Disconnect from network if necessary

• Report to IT/security team immediately

• Document incident details

Reporting Guidelines

• Report all security concerns promptly

• No penalties for false alarms — better to over-report than miss a real threat