Papers by Venkata Sriram Siddhardh Nadendla
Design of Binary Quantizers for Distributed Detection Under Secrecy Constraints
IEEE Transactions on Signal Processing, 2016
ABSTRACT In this paper, we consider the problem of designing binary quantizers at the sensors for... more ABSTRACT In this paper, we consider the problem of designing binary quantizers at the sensors for a distributed detection network in the presence of an eavesdropper. We propose to design these quantizers under a secrecy constraint imposed on the eavesdropper. The performance metric chosen in this paper is the KL Divergence at both the fusion center (FC) and the eavesdropper (Eve). First, we consider the problem of secure distributed detection in the presence of identical sensors and channels. We prove that the optimal quantizer can be implemented as a likelihood ratio test, whose threshold depends on the specified secrecy constraint on the Eve. We present an algorithm to find the optimal threshold in the case of Additive White Gaussian Noise (AWGN) observation models at the sensors. In the numerical results, we discuss the tradeoff between the distributed detection performance and the secrecy constraint on the eavesdropper. We show how the system behavior varies as a function of the secrecy constraint imposed on Eve. Finally, we also investigate the problem of designing the quantizers for a distributed detection network with non-identical sensors and channels. We decompose the problem into $N$ sequential problems using dynamic programming, where each individual problem has the same structure as the scenario with identical sensors and channels. Optimum binary quantizers are obtained. Numerical results are presented for illustration.
IEEE Communications Magazine, 2015
The distributed inference framework comprises of a group of spatially distributed nodes which acq... more The distributed inference framework comprises of a group of spatially distributed nodes which acquire observations about a phenomenon of interest. Due to bandwidth and energy constraints, the nodes often quantize their observations into a finite-bit local message before sending it to the fusion center (FC). Based on the local summary statistics transmitted by nodes, the FC makes a global decision about the presence of the phenomenon of interest. The distributed and broadcast nature of such systems makes them quite vulnerable to different types of attacks. This paper addresses the problem of secure communication in the presence of eavesdroppers. In particular, we focus on efficient mitigation schemes to mitigate the impact of eavesdropping. We present an overview of the distributed inference schemes under secrecy constraints and describe the currently available approaches in the context of distributed detection and estimation followed by a discussion on avenues for future research.
The problem of Byzantine (malicious sensors) threats in a distributed detection framework for inf... more The problem of Byzantine (malicious sensors) threats in a distributed detection framework for inference networks is addressed. Impact of Byzantines is mitigated by suitably adding Stochastic Resonance (SR) noise. Previously, Independent Malicious Byzantine Attack (IMBA), where each Byzantine decides to attack the network independently relying on its own observation was considered. In this paper, we present further results for Cooperative Malicious Byzantine Attack (CMBA), where Byzantines collaborate to make the decision and use this information for the attack. In order to analyze the network performance, we consider KL-Divergence (KLD)
Minimax games for cooperative spectrum sensing in a centralized cognitive radio network in the presence of interferers
2011 - MILCOM 2011 Military Communications Conference, 2011
ABSTRACT In this paper, we consider the problem of interferers for cooperative spectrum sensing i... more ABSTRACT In this paper, we consider the problem of interferers for cooperative spectrum sensing in a centralized cognitive radio network comprising N cognitive radios (CRs) and one fusion center (FC) in the presence of a fixed interferer. The design metric chosen is the error probability. We prove the existence of a saddle-point in the minimax game between the interferer and the CR network. An optimal solution is found that maximizes the objective with respect to the interferer's parameters and minimizes the same with respect to the CR network's parameters. We show that the probability of error is a quasi-convex function with respect to the network's parameters and a monotone function with respect to the interferer's parameters. We also present numerical results that corroborate our theoretical results.
Secure distributed detection in the presence of eavesdroppers
2010 Conference Record of the Forty Fourth Asilomar Conference on Signals, Systems and Computers, 2010
ABSTRACT We investigate the structure of quantizer rules at the local sensors in distributed dete... more ABSTRACT We investigate the structure of quantizer rules at the local sensors in distributed detection networks, in the presence of eavesdroppers (Eve), under asymptotic regime (number of sensors tending to infinity) for binary hypotheses. These local quantizers are designed in such a way that the confidentiality of sensor data is preserved while achieving optimal detection performance at the fusion center (FC). In the case of Eve with noisier channels, for a general channel model, we show that these optimal quantizer rules at the local sensors are always on the boundaries of the achievable region of sensor's ROC. If there is a constraint on the Eve's performance, based on our numerical results, we conjecture that the structure of an optimal quantizer is LRT-based. The above argument is corroborated with a numerical example using BSC channels for the Eve and ideal channels for the FC. In the case of Eve with better channels, we prove that the quantizer rules that can provide confidentiality along with optimal detection performance, cannot send any useful information to the fusion center (FC). We propose a jamming scheme for the FC against Eve and evaluate the optimal distribution for the Gaussian jamming signal that requires minimum energy to make both FC and Eve's channel similar in distributed detection performance.
On jamming models against collaborative spectrum sensing in a simple cognitive radio network
2010 Conference Record of the Forty Fourth Asilomar Conference on Signals, Systems and Computers, 2010
ABSTRACT We design the optimal jamming attack strategy for a cognitive radio network in the prese... more ABSTRACT We design the optimal jamming attack strategy for a cognitive radio network in the presence of path-loss decaying signal models. We consider a cognitive radio network with K participating cognitive radios and one fusion center in the presence of one primary user and one jammer in the operating region. We assume that the network is not aware of the presence of the jammer and hence employs the optimal decision rules designed for a benign environment. Jammer, on the other hand, tries to take advantage of this ignorance and carries the best possible attack so that it can maximally deteriorate the global performance (error-probability) of the network under a total power-constraint. We consider a two-fold attack - one on the CR (sensor) reception and other on the fusion center reception. We present numerical results depicting near-field and far-field effects over different path-loss exponents to find the optimal jamming attack for a relatively simple example where the network has only one sensor (K = 1). This example serves as an illustration of the basic concepts and will be followed by a more in-depth study.
An auction-based mechanism for dynamic spectrum allocation in participatory cognitive radio networks
2012 50th Annual Allerton Conference on Communication, Control, and Computing (Allerton), 2012
ABSTRACT The problem of dynamic spectrum allocation for participatory cognitive radio (CR) networ... more ABSTRACT The problem of dynamic spectrum allocation for participatory cognitive radio (CR) networks is modeled using an auction-based mechanism, where the fusion center (FC) acts as an auctioneer and allocates spectrum to CRs without complete knowledge regarding spectrum availability. We also consider the cost of collisions with the primary user (PU) and assign this cost to the FC, making it completely responsible for its allocation decision. With the help of CRs participating in the network, the FC makes a global inference on the availability of the spectrum followed by spectrum allocation. The goal of this paper is to investigate the design of an optimal auction-based framework for participatory CR networks, and to find the conditions under which a CR actively participates in the optimal auction (or, collaborative spectrum sensing). We also identify a scenario in the optimal auction design where the FC pays to the participating CRs, in order to improve the sensing performance, while simultaneously maximizing its revenue.
2011 IEEE Wireless Communications and Networking Conference, 2011
The problem of binary hypothesis testing in a wireless sensor network is considered where observa... more The problem of binary hypothesis testing in a wireless sensor network is considered where observation of the sensors are quantized using identical binary quantizers and encrypted before transmission using a simple probabilistic cipher. The authorized or ally fusion center (AFC) is aware of the encryption process and the encryption parameters, whereas the unauthorized or third party fusion centers (TPFC) are unaware of the encryption parameters. The optimal threshold is evaluated for fixed values of the encryption parameters and numerical results are presented on the error probabilities of the two fusion centers. It is shown that by appropriate selection of the encryption parameters it is possible to degrade the performance of the TPFC significantly compared to that of AFC.
IEEE Transactions on Signal Processing, 2000
The problem of distributed inference with M-ary quantized data at the sensors is investigated in ... more The problem of distributed inference with M-ary quantized data at the sensors is investigated in the presence of Byzantine attacks. We assume that the attacker does not have knowledge about either the true state of the phenomenon of interest, or the quantization thresholds used at the sensors. Therefore, the Byzantine nodes attack the inference network by modifying modifying the symbol corresponding to the quantized data to one of the other M symbols in the quantization alphabetset and transmitting the false symbol to the fusion center (FC). In this paper, we find the optimal Byzantine attack that blinds any distributed inference network. As the quantization alphabet size increases, a tremendous improvement in the security performance of the distributed inference network is observed.
In this paper, we consider the problem of dynamic spectrum allocation in cognitive radio (CR) net... more In this paper, we consider the problem of dynamic spectrum allocation in cognitive radio (CR) networks and propose a new sealed-bid auction framework to address the spectrum allocation problem when the spectrum is not available with certainty.
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Papers by Venkata Sriram Siddhardh Nadendla