- Machine learning technologies are widely used in industries with strict privacy requirements such as healthcare, digital banking, wearables, social media, insurance, and etc. These AI engines are trained with private information and are regularly collecting personally identifiable data. When machine learning algorithms are trained with private data, the resulting engine might leak information about that data through its behaviour (i.e., a black-box inference attack) or its architecture (i.e., a white-box attack).
- Our AI-Security scientists could review your AI systems architecture and identify any architectural or procedural privacy issues during training, testing, deploying, or using your machine learning agents. Our experts conduct a comprehensive privacy risk assessment of your AI engines by running a range of Our AI Cybersecurity Review service, provides data collectors, solution developers, service deployers and consumers with an independent view of current security and privacy issues in AI-based systems deployed in transportation systems.
To identify any data leakage issues. We will provide you with a privacy risk assessment report that includes list of identified risks and offers practical actions to address those risks to become compliant.
PCI-DSS Requirement 6.1 mandates companies to establish a process to identify vulnerabilities in their internal and external applications. PCI-DSS Requirement 6.2 requires companies to ensure that all software and system components are protected from known vulnerabilities. PCI-DSS Requirement 11.3.1 requires at least annual external penetration testing of companies systems. PCI-DSS Requirement 11.3.3. mandates to address vulnerabilities detected during tests and to conduct additional testing until all vulnerabilities are corrected.
Our AI Vulnerability Assessment and Testing Services would help you meeting all PCI-DSS requirements. Our AI-Security experts identify all vulnerabilities in your AI ecosystem and closely work with you to address identified risks. Our AI Security Review Service would assure your company compliance with the best AI security standards and guidelines through out the year.
As the most widely used information security standard in the world, ISO27001 requires companies to show that they have taken the necessary measures to limit potential incidents. Making sure that your AI-based systems are robust against cyberattacks and required controls are in place to contain potential incidents is becoming a key element of ISO27001 compliance reports. With the help of our experts and using our AI Vulnerability Assessment and Testing Services you can make sure that your AI services are meeting ISO27001 requirements in a simplified and optimized manner.
Many countries are proposing guidelines and standards for responsible and reliable use of AI. These guidelines are the foundation for the future legislative requirements. Compliance with these standard guidelines would not only guarantee your AI systems alignment with future legislative requirements but improves your company brand and reputation.
We deliver a systematic and strategic approach to assess your business compliance with the following standard guidelines:
- Canada’s Responsible Use of Artificial Intelligence guidelines recommend companies to ensure the effective and ethical use of AI. By implementing our Trustworthy AI Framework you can be assured that your business meets Canada’s Responsible Use of Artificial Intelligence guideline requirements.
- EU Ethics Guideline for Trustworthy AI put forward a set of 7 key requirements for AI systems. By implementing our Trustworthy AI Framework you can be assured that your business meets all 7 requirements of the EU Ethics Guideline for Trustworthy AI.