With the growing reliance on ML, organizations must proactively identify vulnerabilities and determine if ML solutions align with their business goals. To help you navigate this evolving landscape, our ethical hacker, Samraa Al Zubi, has prepared a comprehensive whitepaper that dives deep into the security aspects of machine learning.
In this whitepaper, Samraa explores some of the most common attack types targeting ML systems, shedding light on potential risks that businesses may face. The document also provides insights into identifying proper use cases for ML solutions and evaluating whether these technologies are suitable for your organisation.
Moreover, the whitepaper discusses the emerging regulations set to govern AI and ML use, offering valuable guidance on compliance. It also includes a detailed assessment of security tools and defences, highlighting the most effective strategies to protect your ML systems against malicious actors.
Artificial Intelligence holds immense potential to address critical challenges across various industries. However, as we unlock this potential, we must prepare to defend machine learning systems from becoming liabilities. By implementing robust security measures, we can ensure that ML enhances, rather than jeopardises, our digital landscape.
