Impact of False Data Injection Attacks on Deep Learning Enabled Predictive Analytics

Role of Artificial Intelligence in the Internet of Things (IoT) cybersecurity

“…Once an attacker has access to some or all of the devices on an IoT network via an MITM attack, one example of an attack they could carry out next is a False Data Injection (FDI) attack. FDI attacks are when an attacker alters measurements from IoT sensors by a small amount so as to avoid suspicion and then outputs the faulty data [21]. FDI attacks can be perpetrated in a number of ways, but in practice doing so via MITM attacks is the most practical.…”

“…FDI attacks are often leveraged against sensors that send data to an algorithm that attempts to make predictions based on the data it has received or otherwise uses data to make conclusions. These algorithms, sometimes referred to as predictive maintenance systems, are commonly used in monitoring the state of a mechanical machine and predicting when it will need to be maintained or tuned [21]. These predictive maintenance algorithms and similar would also be a staple feature of smart cities, FDI attacks against which could be disastrous.…”

“…An example of an FDI attack on a predictive maintenance system is sensors on an airplane engine that predict when the engine will need critical maintenance. When attackers are able to access even a small portion of the sensors, they are able to create a small amount of noise that goes undetected by faulty data detection mechanisms but is just enough to skew the algorithm's predictions [21]. In testing, it would even be enough to delay critical maintenance to the system, potentially causing catastrophic failure while in use, which could cause a costly unplanned delay or loss of life.…”

Machine Learning for Authentication and Authorization in IoT: Taxonomy, Challenges and Future Research Direction

“… False Data Injection: If the node has been captured, the intruder can insert erroneous information into the IoT application that can generate false results and cause IoT application to fail. DDoS attacks may use this critical approach too [ 47 ]. Service Interruption: Such threats are often classified in current literature as unauthorized disruption activities or DDoS attacks.…”

“…False Data Injection: If the node has been captured, the intruder can insert erroneous information into the IoT application that can generate false results and cause IoT application to fail. DDoS attacks may use this critical approach too [ 47 ].…”