New technologies such as Artificial Intelligence and its subset, Machine Learning, Computer Vision, IoT, Cloud Technologies, Smart Robotics and Mobility are fostering innovation in the connected and autonomous vehicles industry.

Also, there are potential issues arising from the poor quality and/or inadequate quantity of data on which to base predictions, as well as the predictive capability of the algorithms used to infer probabilistic outcomes. Algorithmic transparency might be a serious issue in particular in regulated industries, especially when implicating people, and it is not easy to address this problem as just because someone has access to the ML code, it does not always equal being able to explain how the software works, mainly because there are ML algorithms that do not behave in a wholly predictable manner.

From ransomware, to spyware and banking trojans, the types of malware threats are many. Yet the one threat that seems to be posing the greatest challenge to organizations and their cybersecurity solutions is the unknown malware. This is because the means that have most typically been used to counter cyber threats to date remain insufficient when it comes to unknowns: Signature-based: traditional antivirus solutions usually lean on such technique. With this technique, key data from given files is signed, and so for next times files are matched with the same signature, those will be classified as malicious. The key data is usually strings, or other byte sequences of code piece.