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 contain little to no security features and are vulnerable to various attacks. This paper proposes an approach to detect the intrusions into network attached ICSs by measuring and verifying data that is transmitted through the network but is not inherently the data used by the transmission protocol -network telemetry. Using simulated PLC units, the developed IDS was able to achieve 94.3% accuracy when differentiating between machines of an attacker and engineer on the same network, and 99.5% accuracy when differentiating between attacker and engineer on the Internet. Stanislav Ponomarev is a Ph.D. candidate of engineering at Louisiana Tech University with concentration in cyber security. His research topics of interest include image enhancement, hard drive forensics, malicious application detection, network intrusion detection, and windows executable memory attacks.Travis Atkison received the B.

a b s t r a c tObtaining accurate temperature distributions in living tissue related to hyperthermia skin cancer treatment without using an intruding sensor is a challenge. Here, we report a mathematical model that can accurately determine the temperature distribution in the tumor region and surrounding normal tissue. The model is based on a modified Pennes' equation for the bioheat transfer in a 3-D triple-layered skin structure embedded with a vascular countercurrent network and a tumor appearing in the subcutaneous region. The vascular network is designed based on the constructal theory of multi-scale tree-shaped heat exchangers. The tumor is injected with gold nanoshells in order to be heated quickly. The proposed model is implemented numerically using a stable finite difference scheme. The method is demonstrated and tested by an example.

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Modern networking architecture is designed with high scalability in mind. Different protocols can be encapsulated to support different systems. Machine identifiers (IP and MAC addresses) in network packets can be modified easily. This modification prevents servers from determining whether the connecting machines are allowed to communicate. Cryptographic functions have been used in protocols such as Secure Shell (SSH) to establish network node authenticity, but they can be circumvented by social engineering and brute force attacks. This research effort created a new classifier that processes network telemetry to determine authenticity of SSH clients in a control system's network. The developed classifier, within the control system's network, was able to differentiate with a 100% accuracy SSH connections from machines that were transmitting identical MAC and IP addresses, and had the same RSA key for authentication.

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