Insufficient Security Measures
Malicious entities can take advantage of weaknesses in AI algorithms to alter results, potentially resulting in tangible real-life impacts. Additionally, it’s vital to prioritize safeguarding privacy and handling data responsibly, particularly given AI’s significant data needs. Balancing the extraction of valuable insights with privacy maintenance is a delicate task
ENTITY
1 - Human
INTENT
1 - Intentional
TIMING
2 - Post-deployment
Risk ID
mit474
Domain lineage
2. Privacy & Security
2.2 > AI system security vulnerabilities and attacks
Mitigation strategy
1. Embed Privacy by Design (PbD) principles into the entire AI system lifecycle, emphasizing data minimization, robust encryption, and role-based access controls for all data, to proactively ensure adherence to privacy regulations and uphold user data integrity. 2. Implement a multi-layered defense strategy against adversarial manipulation, including the use of adversarial training during model development to enhance model robustness and the deployment of input validation and anomaly detection at the inference stage to neutralize malicious inputs. 3. Utilize Explainable AI (XAI) frameworks and post-hoc explainability techniques to ensure model transparency, enabling the auditing of algorithmic decisions and the timely detection of unintended consequences, biases, or unauthorized model alterations post-deployment.
ADDITIONAL EVIDENCE
guaranteeing adherence to privacy regulations and upholding user data privacy constitutes a vital component of AI security management. Incorporating privacy-by-design principles and employing anonymization techniques can aid in safeguarding sensitive personal information