As technology becomes more prevalent, its application to safety and security in critical systems continues to increase. This leads to an increased dependence on sensors to provide an accurate view of the environment surrounding an application. These sensors can also be exploited by a malicious individual to attack a system and compromise its safety or security. These attacks change the reported value of a sensor so that it doesn't re ect the real situation. The systems in a car can be used as an example of this. Cars can have numerous sensors that measure a variety of things, including the car's distance from an object, if the tires are locking up, or if the gas is low. The use of these sensors makes cars safer and more convenient to use. Using IEMI, an attacker could compromise some of these systems by changing the reported value so that an object appears further away than it actually is or that the tires aren't locking up when they are, possibly causing the car to crash. By doing this, a malicious individual could compromise the safety or security of a car. This work attempts to understand what would be required for a malicious individual to conduct such an attack, thereby allowing for the identification of systems that are vulnerable to such attacks. This understanding would also provide the basis for designing defenses against these attacks, thereby increasing the safety of society at large.