Massive Development in Digital Risk Protection Market as Researchers Create a novel System that can Fend-Off Against 'False Data Injection' Strikes
Posted On December 30, 2021
In 2010, the Stuxnet virus was utilized to damage nuclear centrifuges in Iran. Similar to that incident, ransomware and cyberattacks worldwide continues to increase. Systems operators are primarily worried about sophisticated attacks like 'false data injection' strikes. Hackers feed the wrong data to the operating system in these attacks, falsely believing that everything is fine. If computer models and data analytics relying on artificial intelligence that assures the seamless running of today's electric grids, power plants and manufacturing facilities get into the wrong hands. In that case, they could be turned against themselves.
A research team has put forward a robust response against these threats. They have developed an innovative self-cognizant and healing technology applicable in industrial control systems against internal and external attacks. The system is for a computer model that runs on cyber-physical systems. The system would be a significant contribution to Digital Risk Protection Market. Even if attackers are armed with a perfect duplicate of a system's model and attempt to bring falsified data, the system can fend off against it. The system can detect and reject the falsified data on its own with no need for human intervention.
The innovation is being referred to as cover cognizance. The team explained it as having a bunch of bees hovering around an object. Once the object moves a little, the whole network of bees will move with it like a butterfly effect. Similarly, if someone touches the data a little, the whole system will respond to the instruction and correct the modified data in no time.
Generally, these systems are directly dependent upon the knowledge of the model. If an attacker is well familiar with the model, the defence can be easily invaded. Any system that relies on a controller looking at data and making a decision is vulnerable to these types of attacks right now. If one can access the data, then probably the information on it can also be changed. So, whoever is trying to harm the system will base their actions on fake data.
The idea proposed is impressive and relevant for about every cyber-physical domain, like advanced transportation or manufacturing. The team hopes that the present research will help the world develop further and solve prevalent real-world problems.