Abstract-In this paper, we describe our novel use of network intrusion detection systems (NIDS) for protecting automated distribution systems (ADS) against certain types of cyber attacks in a new way. The novelty consists of using the hybrid control environment rules and model as the baseline for what is normal and what is an anomaly, tailoring the security policies to the physical operation of the system. NIDS sensors in our architecture continuously analyze traffic in the communication medium that comes from embedded controllers, checking if the data and commands exchanged conform to the expected structure of the controllers interactions, and evolution of the system's physical state. Considering its importance in future ADSs, we chose the fault location, isolation and service restoration (FLISR) process as our distribution automation case study for the NIDS deployment. To test our scheme, we emulated the FLISR process using real programmable logic controllers (PLCs) that interact with a simulated physical infrastructure. We used this testbed to examine the capability of our NIDS approach in several attack scenarios. The experimental analysis reveals that our approach is capable of detecting various attacks scenarios including the attacks initiated within the trusted perimeter of the automation network by attackers that have complete knowledge about the communication information exchanged.

In this paper, we propose a novel use of network intrusion detection systems (NIDSs) tailored to detect attacks against networks that support hybrid controllers that implement power grid protection schemes. In our approach, we implement specification-based intrusion detection signatures based on the execution of the hybrid automata that specify the communication rules and physical limits that the system should obey. To validate our idea, we developed an experimental framework consisting of a simulation of the physical system and an emulation of the master controller, which serves as the digital relay that implements the protection mechanism. Our Hybrid Control NIDS (HC-NIDS) continuously monitors and analyzes the network traffic exchanged within the physical system. It identifies traffic that deviates from the expected communication pattern or physical limitations, which could place the system in an unsafe mode of operation. Our experimental analysis demonstrates that our approach is able to detect a diverse range of attack scenarios aimed at compromising the physical process by leveraging information about the physical part of the power system

In recent work we have introduced and evaluated a fair and dynamic joint Call Admission Control (CAC) and Multiple Access Control (MAC) framework, for Geostationary Orbit (GEO) Satellite Systems, named Fair Predictive Resource Reservation Access (FPRRA). The framework was based on accurate videoconference and data traffic prediction, made decisions after taking into account the provider's revenue, and was shown to be highly efficient. In this paper we enhance FPRRA by talking into account the users' satisfaction for making scheduling decisions and we focus on its evaluation in the absence of accurate MPEG-4 and H.264 video traffic modeling. In addition, we discuss the efficiency of our proposed scheme in comparison to other efficient schemes from the literature

The trustworthiness and security of cyber-physical systems (CPSs), such as the power grid, are of paramount importance to ensure their safe operation, performance, and economic efficiency. The aim of many cyber-physical security techniques, such as network intrusion detection systems (NIDSs) for CPSs, is to ensure continuous reliable operation even in exposed network environments. But the validation of such methods goes well beyond standard network analysis, since meaningful tests must also integrate realistic understanding of the physical systems behavior and response to the network activity. Our goal in this paper is to showcase an example of a testbed environment that can support such validation. In it, real network traffic, emulating and industrial control network, interacts with simulated physical models in real-time, extending and leveraging "hardware-in-the-loop" and "cyber-in-the-loop" capabilities. The testbed is a bridge between theory and practice and offers a number of features, including network communications, data management, as well as the virtualization of cyber-physical state analytics performed by the NIDS. The traffic is captured by real network taps and is forwarded to a real data management environment, receiving also the data reports from the simulated industrial control environment. To illustrate the capabilities of our testbed we show how the data are cross-checked by a "physics aware" NIDS, identifying network traffic that does not comply with its cyber-physical security rules

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