Using a Cluster for Securing Embedded Systems

Securing Embedded Systems

Securing Embedded Systems: From Analyses of Modern Automotive Systems to Enabling Dynamic Analysis

Chaotic Memory Randomization for Securing Embedded Systems

Embedded systems permeate through nearly all aspects of modern society. From cars to refrigerators to nuclear refineries, securing these systems has never been more important. Intrusions, such as the Stuxnet malware which broke the centrifuges in Iran’s Natanz refinery, can be catastrophic to not only the infected systems, but even to the wellbeing of the surrounding population. Modern day prot...

SECURING INTERPRETABILITY OF FUZZY MODELS FOR MODELING NONLINEAR MIMO SYSTEMS USING A HYBRID OF EVOLUTIONARY ALGORITHMS

In this study, a Multi-Objective Genetic Algorithm (MOGA) is utilized to extract interpretable and compact fuzzy rule bases for modeling nonlinear Multi-input Multi-output (MIMO) systems. In the process of non- linear system identi cation, structure selection, parameter estimation, model performance and model validation are important objectives. Furthermore, se- curing low-level and high-level ...

On Securing Networked Real-Time Embedded Systems

There has been an exponential growth of applications that rely on diverse types of embedded real-time end systems and devices, such as smart phones, play stations, home appliances, consumer and industrial electronics, smart sensors and actuators. These applications require diverse types of Quality-of-Service (QoS) including timeliness, dependability, security and privacy, from the end systems/d...

Securing Embedded Software using Software Dynamic Translation