| Title | A Feasibility Study on Machine Learning Techniques for APT Detection and Protection in VANETs |
| Publication Type | Conference Paper |
| Year of Publication | 2019 |
| Authors | De Abreu, Sergio |
| Conference Name | 2019 IEEE 12th International Conference on Global Security, Safety and Sustainability (ICGS3) |
| Keywords | advanced persistent threat, APT, APT attack, APT detection, computer network security, Human Behavior, learning (artificial intelligence), machine learning, Metrics, pubcrawl, resilience, Resiliency, road vehicles, Scalability, VANET protection, vehicular ad hoc networks |
| Abstract | It is estimated that by 2030, 1 in 4 vehicles on the road will be driverless with adoption rates increasing this figure substantially over the next few decades. |
| DOI | 10.1109/ICGS3.2019.8688031 |
| Citation Key | de_abreu_feasibility_2019 |
A Feasibility Study on Machine Learning Techniques for APT Detection and Protection in VANETs