As thoroughly as possible, describe the security components of your approved information system. For discussion of server-side components, it is okay to make reasonable educated assumptions based on what you know about the typical configuration of the server-side of a client / server system.
2. Discuss any security concerns or vulnerabilities that your approved information system has.
3. At the bottom of your post, list all of the references you used to find this information.
The server-side comprises the API Gateway, Load Balancers, Application Servers, Database, and the AI Model infrastructure.
A. Perimeter Security
Firewalls and Web Application Firewalls (WAF): WAFs are deployed at the edge to inspect HTTP/HTTPS traffic for known attack patterns like SQL injection, cross-site scripting (XSS), and denial-of-service (DoS) attempts before traffic reaches the core application servers.
Intrusion Detection/Prevention Systems (IDPS): Continuously monitor network traffic and system activity for malicious behavior or policy violations, alerting security teams or automatically blocking suspicious traffic.
DDoS Protection: Cloud-native services are utilized to absorb high-volume traffic spikes intended to overwhelm and crash the service.
B. Identity and Access Management (IAM)
Strong Authentication: Supports Multi-Factor Authentication (MFA) for all internal users and often for external users.
Role-Based Access Control (RBAC): Access to internal systems, databases, and model infrastructure is strictly controlled based on the principle of least privilege. For instance, a developer may access code repositories but not production databases containing user data.
API Key Management: A dedicated system manages the creation, rotation, and revocation of API keys for developers and internal services.
C. Data Security
Encryption at Rest and In Transit:
At Rest: Databases, file storage, and backup media containing training data, user queries, and internal logs are encrypted using algorithms like AES-256.
In Transit: Handled by TLS/SSL, as noted above.
For an AI system like a language model, the architecture is fundamentally divided into client-side (the user interface) and server-side (the AI model and processing infrastructure).
The client-side refers to the user's browser or mobile application used to submit queries.
Secure Communication (TLS/SSL): All data transfer between the client and the server is encrypted using Transport Layer Security (TLS), ensuring confidentiality and integrity. This prevents man-in-the-middle attacks from intercepting or tampering with user queries and model responses.
Input Validation: The client application performs basic checks on user input to filter out common web vulnerabilities before the data reaches the server. This includes limits on query length and checking for malformed data.
Client Authentication Token Management: The client securely stores and manages temporary authentication tokens (e.g., JWTs) used to prove the user's identity to the server for each request.