Network-on-Chips (NoCs) have been widely used as a scalable communication solution in the design of multiprocessor system-on-chips (MPSoCs). NoCs manage communications between on-chip Intellectual Property (IP) cores and allow processing cores to achieve higher performance by outsourcing their communication tasks. NoC paradigm is based on the idea of resource sharing where hardware resources, including buffers, communication links, routers, etc., are shared between all IPs of the MPSoC. In fact, the data being routed by each NoC router might not be related to the router's local core. Such a utilization-centric design approach can raise security issues in MPSoCs-based designs, e.g., integrity and confidentiality of the data being routed in an NoC might be compromised by unauthorized accesses/modifications of intermediate routers. Many papers in the literature have discovered and addressed security holes of NoCs, aiming at improving the security of the NoC paradigm. However, to the best of our knowledge, there is no solid survey study on the security vulnerabilities and countermeasures for NoCs. This paper will review security threats and countermeasures proposed so far for wired NoCs, wireless NoCs, and 3D NoCs. The paper aims at giving the readers an insight into the attacks and weaknesses/strengths of countermeasures.

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Abstract-In this demonstration we present a platform that encompasses all of the components required to realistically evaluate the performance of Dynamic Adaptive Streaming over HTTP (DASH) over a real-time NS-3 simulated network. Our platform consists of a network-attached storage server with DASH video clips and a simulated LTE network which utilises the NS-3 LTE module provided by the LENA project. We stream to clients running an open-source player with a choice of adaptation algorithms. By providing a user interface that offers user parametrisation to modify both client and LTE settings, we can view the evaluated results of real-time interactions between the network and the clients. Of special interest is that our platform streams actual video clips to real video clients in real-time over a simulated LTE network, allowing reproducible experiments and easy modification of LTE and client parameters.The demonstration showcases how changes in LTE network settings (fading model, scheduler, client distance from eNB, etc.), as well as video-related decisions at the clients (streaming algorithm, quality selection, clip selection, etc.), can impact on the delivery and achievable quality.