Engineering topics

Ozel, Omur

Publications and source records attributed to Ozel, Omur.

4 records

DOE OSTI2018

Uniform redundancy allocation maximizes the robustness of flow networks against cascading failures

We study the robustness of flow networks against cascading failures under a partial load redistribution model. In particular, we consider a flow network of N lines with initial loads L 1 ,...,L N and free spaces (i.e., redundant space) S 1 ,...,S N that are independent and identically distributed with joint distribution P LS (x,y) = P[L ≤ x, S ≤ y]. The capacity C i is the maximum load allowed on line i and is given by C i = L i + S i . Furthermore, when a line fails due to overloading, it is removed from the system and (1 – ε) fraction of the load it was carrying is redistributed equally among all remaining lines in the system. The rest (i.e., ε fraction) of the load is assumed to be lost or absorbed, e.g., due to advanced circuitry disconnecting overloaded power lines or an interconnected network or material absorbing a fraction of the flow from overloaded lines. We analyze the robustness of this flow network against random attacks that remove a p fraction of the lines. Our contributions include (i) deriving the final fraction of alive lines n ∞ (p,ε) for all p,εϵ(0,1) and confirming the results via extensive simulations; (ii) showing that partial redistribution might lead to (depending on the parameter 0 < ε ≤ 1) the order of transition at the critical attack size p* changing from first to second-order; and (iii) proving analytically that flow networks achieve maximum robustness [quantified by the area ∫$^{1}_{0}$ n ∞ (p,ε)dp] when all lines have the same free space regardless of their initial load. The optimality of equal free-space allocation is also confirmed on real-world data from the UK National Power Grid.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2017

A Bernoulli Gaussian Watermark for Detecting Integrity Attacks in Control Systems

We examine the merit of Bernoulli packet drops in actively detecting integrity attacks on control systems. The aim is to detect an adversary who delivers fake sensor measurements to a system operator in order to conceal their effect on the plant. Physical watermarks, or noisy additive Gaussian inputs, have been previously used to detect several classes of integrity attacks in control systems. In this paper, we consider the analysis and design of Gaussian physical watermarks in the presence of packet drops at the control input. On one hand, this enables analysis in a more general network setting. On the other hand, we observe that in certain cases, Bernoulli packet drops can improve detection performance relative to a purely Gaussian watermark. This motivates the joint design of a Bernoulli-Gaussian watermark which incorporates both an additive Gaussian input and a Bernoulli drop process. We characterize the effect of such a watermark on system performance as well as attack detectability in two separate design scenarios. Here, we consider a correlation detector for attack recognition. We then propose efficiently solvable optimization problems to intelligently select parameters of the Gaussian input and the Bernoulli drop process while addressing security and performance trade-offs. Finally, we provide numerical results which illustrate that a watermark with packet drops can indeed outperform a Gaussian watermark.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2017

Physical Watermarking for Securing Cyber-Physical Systems via Packet Drop Injections

Physical watermarking is a well known solution for detecting integrity attacks on Cyber-Physical Systems (CPSs) such as the smart grid. Here, a random control input is injected into the system in order to authenticate physical dynamics and sensors which may have been corrupted by adversaries. Packet drops may naturally occur in a CPS due to network imperfections. To our knowledge, previous work has not considered the role of packet drops in detecting integrity attacks. In this paper, we investigate the merit of injecting Bernoulli packet drops into the control inputs sent to actuators as a new physical watermarking scheme. With the classical linear quadratic objective function and an independent and identically distributed packet drop injection sequence, we study the effect of packet drops on meeting security and control objectives. Our results indicate that the packet drops could act as a potential physical watermark for attack detection in CPSs.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2017

Active Detection for Exposing Intelligent Attacks in Control Systems

In this paper, we consider approaches for detecting integrity attacks carried out by intelligent and resourceful adversaries in control systems. Passive detection techniques are often incorporated to identify malicious behavior. Here, the defender utilizes finely-tuned algorithms to process information and make a binary decision, whether the system is healthy or under attack. We demonstrate that passive detection can be ineffective against adversaries with model knowledge and access to a set of input/output channels. We then propose active detection as a tool to detect attacks. In active detection, the defender leverages degrees of freedom he has in the system to detect the adversary. Specifically, the defender will introduce a physical secret kept hidden from the adversary, which can be utilized to authenticate the dynamics. In this regard, we carefully review two approaches for active detection: physical watermarking at the control input, and a moving target approach for generating system dynamics. We examine practical considerations for implementing these technologies and discuss future research directions.

25 ENERGY STORAGE↗