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The use and deployment of Industrial Control Systems (ICS) have become standard across many industries, though the security of these important systems have not kept pace with their current Internet focused deployment technologies. This technology gap has exposed an exploitable vector for would be attackers as ICS protocols do not have security mechanisms in place to handle Internet connectivity. This...
This paper presents an overview of the privacy issues that are expected to emerge as a result of the Internet of Things (IoT). IoT expands digital world to include different things in our physical world. This ambitious aspiration is becoming true with the utilization of already existing technologies that enable things to be identified and to communicate with each other. Unfortunately, the ubiquitous...
As the use of mobile devices continues to increase, so does the need for sophisticated malware detection algorithms. The preliminary research presented in this paper focuses on examining permission requests made by Android apps as a means for detecting malware. By using a machine learning algorithm, we are able to differentiate between benign and malicious apps. The model presented achieved a classification...
Until recently, industrial control systems (ICSs) used “air-gap” security measures, where every node of the ICS network was isolated from other networks, including the Internet, by a physical disconnect. Attaching ICS networks to the Internet benefits companies and engineers who use them. However, as these systems were designed for use in the air-gapped security environment, protocols used by ICSs...
One of the biggest efforts of securing cyberspace is the ability to secure the critical infrastructure power grid. This meshed network of geographically distributed control systems has recently been interlaced with network capable devices. This article manipulates power system state parameters to identify stealthy cyber-events based on the feature identification method principal component analysis...
Research efforts to develop malicious application detection algorithms have been a priority ever since the discovery of the first "viruses". Various methods are used to search and identify these malicious applications. One such method, n-gram analysis, can be implemented to extract features from binary files. These features are then be used by machine learning algorithms to classify them...
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