Electrical and Electronic Engineering - Research Publications

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    On Privacy of Quantized Sensor Measurements through Additive Noise
    Murguia, C ; Shames, I ; Farokhi, F ; Nesic, D ( 2018-09-10)
    We study the problem of maximizing privacy of quantized sensor measurements by adding random variables. In particular, we consider the setting where information about the state of a process is obtained using noisy sensor measurements. This information is quantized and sent to a remote station through an unsecured communication network. It is desired to keep the state of the process private; however, because the network is not secure, adversaries might have access to sensor information, which could be used to estimate the process state. To avoid an accurate state estimation, we add random numbers to the quantized sensor measurements and send the sum to the remote station instead. The distribution of these random variables is designed to minimize the mutual information between the sum and the quantized sensor measurements for a desired level of distortion -- how different the sum and the quantized sensor measurements are allowed to be. Simulations are presented to illustrate our results.
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    Information-Theoretic Privacy through Chaos Synchronization and Optimal Additive Noise
    Murguia, C ; Shames, I ; Farokhi, F ; Nesic, D ( 2019-06-03)
    We study the problem of maximizing privacy of data sets by adding random vectors generated via synchronized chaotic oscillators. In particular, we consider the setup where information about data sets, queries, is sent through public (unsecured) communication channels to a remote station. To hide private features (specific entries) within the data set, we corrupt the response to queries by adding random vectors. We send the distorted query (the sum of the requested query and the random vector) through the public channel. The distribution of the additive random vector is designed to minimize the mutual information (our privacy metric) between private entries of the data set and the distorted query. We cast the synthesis of this distribution as a convex program in the probabilities of the additive random vector. Once we have the optimal distribution, we propose an algorithm to generate pseudorandom realizations from this distribution using trajectories of a chaotic oscillator. At the other end of the channel, we have a second chaotic oscillator, which we use to generate realizations from the same distribution. Note that if we obtain the same realizations on both sides of the channel, we can simply subtract the realization from the distorted query to recover the requested query. To generate equal realizations, we need the two chaotic oscillators to be synchronized, i.e., we need them to generate exactly the same trajectories on both sides of the channel synchronously in time. We force the two chaotic oscillators into exponential synchronization using a driving signal. Exponential synchronization implies that trajectories of the oscillators converge to each other exponentially fast for all admissible initial conditions and are perfectly synchronized in the limit only. Thus, in finite time, there is always a “small” difference between their trajectories. To implement our algorithm, we assume (as it is often done in related work) that systems have been operating for sufficiently long time so that this small difference is negligible and oscillators are practically synchronized. We quantify the worst-case distortion induced by assuming perfect synchronization, and show that this distortion vanishes exponentially fast. Simulations are presented to illustrate our results.
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    On Privacy of Quantized Sensor Measurements through Additive Noise
    Murguia, C ; Shames, I ; Farokhi, F ; Nesic, D (IEEE, 2018-01-01)
    We study the problem of maximizing privacy of quantized sensor measurements by adding random variables. In particular, we consider the setting where information about the state of a process is obtained using noisy sensor measurements. This information is quantized and sent to a remote station through an unsecured communication network. It is desired to keep the state of the process private; however, because the network is not secure, adversaries might have access to sensor information, which could be used to estimate the process state. To avoid an accurate state estimation, we add random numbers to the quantized sensor measurements and send the sum to the remote station instead. The distribution of these random variables is designed to minimize the mutual information between the sum and the quantized sensor measurements for a desired level of distortion - how different the sum and the quantized sensor measurements are allowed to be. Simulations are presented to illustrate our results.
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    Optimal contract design for effort-averse sensors
    Farokhi, F ; Shames, I ; Cantoni, M (Taylor & Francis, 2018-06-28)
    A central planner wishes to engage a collection of sensors to measure a quantity. Each sensor seeks to trade-off the effort it invests to obtain and report a measurement, against contracted reward. Assuming that measurement quality improves as a sensor increases the effort it invests, the problem of reward contract design is investigated. To this end, a game is formulated between the central planner and the sensors. Using this game, it is established that the central planner can enhance the quality of the estimate by rewarding each sensor based on the distance between the average of the received measurements and the measurement provided by the sensor. Optimal contracts are designed from the perspective of the budget required to achieve a specified level of error performance.
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    Secure Control of Nonlinear Systems Using Semi-Homomorphic Encryption
    Lin, Y ; Farokhi, F ; Shames, I ; Nesic, D (IEEE, 2018-01-01)
    A secure nonlinear networked control system (NCS) design using semi-homomorphic encryption, namely, Paillier encryption is studied. Under certain assumptions, control signal computation using encrypted signal directly is allowed by semi-homomorphic encryption. Thus, the security of the NCSs is further enhanced by concealing information on the controller side. However, additional technical difficulties in the design and analysis of NCSs are induced compared to standard NCSs. In this paper, the stabilization of a nonlinear discrete time NCS is considered. More specifically, sufficient conditions on the encryption parameters that guarantee stability of the NCS are provided, and a trade-off between the encryption parameters and the ultimate bound of the state is shown.
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    Security analysis of cyber-physical systems using H-2 norm
    Shames, I ; Farokhi, F ; Summers, TH (INST ENGINEERING TECHNOLOGY-IET, 2017-07-14)
    In this paper, we study the effect of attacks on networked systems and propose a new security index to analyze the impact of such attacks using H2 norms of attacks to target and monitoring outputs. In addition, we pose, and subsequently solve, optimisation problems for selecting inputs or outputs that point to attacks with maximum impact and least detectability. To demonstrate the applicability of the analysis methods proposed in this paper IEEE 9-bus and 50-generator 145- bus systems are considered as test cases.
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    Secure and Private Cloud-Based Control Using Semi-Homomorphic Encryption
    Farokhi, F ; Shames, I ; Batterham, N (Elsevier, 2016)
    Networked control systems with encrypted sensors measurements is considered. Semi-homomorphic encryption is used so that the controller can perform the required computation on the encrypted data. Specifically, in this paper, the Paillier encryption technique is utilized that allows summation of decrypted data to be performed by multiplication of the encrypted data. Conditions on the parameters of the encryption technique are provided that guarantee the stability of the closed-loop system and ensure certain bounds on the closed-loop performance.
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    Compressive Sensing in Fault Detection
    Farokhi, F ; Shames, I (IEEE, 2018-08-09)
    Randomly generated tests are used to identify faulty sensors in large-scale discrete-time linear time-invariant dynamical systems with high probability. It is proved that the number of the required tests for successfully identifying the location of the faulty sensors (with high probability) scales logarithmically with the number of the sensors and quadratically with the maximum number of faulty sensors. It is also proved that the problem of decoding the identity of the faulty sensors based on the random tests can be cast as a linear programming problem and therefore can be solved reliably and efficiently even for large-scale systems. A numerical example based on automated irrigation networks is utilized to demonstrate the results.
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    Promoting Truthful Behavior in Participatory-Sensing Mechanisms
    Farokhi, F ; Shames, I ; Cantoni, M (IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2015-10-01)