Adversarial Machine Learning: Approaches & defences
Most of us interact with Artificial Intelligence (AI) or Machine Learning (ML) on a daily basis without even knowing; from Google translate, to facial recognition software on our mobile phones and digital assistance in financial services or call centres. It is a growing market with ever increasing possibilities across all sectors, due to the vast amounts of ‘big data’ that most organisations now generate and accumulate.
However, while many look forward to achieving goals with AI it is important to step back and reflect.
Our Adversarial Machine Learning whitepaper explores the potential impact of advances in this area of study such as the defences or mitigations that can be put in place to minimise the risk and the issues around auditing AI systems and the data channels that they utilise.
Published date:  24 October 2017