Search

Privacy-preserving data release mechanisms aiming to minimize the privacy leakage under utility constraints of nonspecific tasks are studied through the lens of information theory. While the private feature to be protected is typically determined and known by the users who release their data, the specific task where the release data is utilized is usually unknown. To address the lack of information of the specific task, utility constraints laid on a set of multiple possible tasks are considered. The mechanism protects the privacy of a given feature of the to-be-released data while satisfying utility constraints of all possible tasks in the set. First, the single-letter characterization of the privacy-utility tradeoff region is derived. Characterization of the minimum privacy under log-loss utility constraints turns out to be a non-convex optimization problem involving mutual information in the objective function and the constraints. Second, focusing on the case where the raw data consists of multiple independent components, we show that the above optimization problem can be decomposed into multiple parallel privacy funnel (PF) problems [1] with different weightings. We explicitly derive the optimal solution to each PF problem when the private feature is a deterministic function of a data component. The solution is characterized by the leakage-free threshold, and the minimum leakage is zero while the utility constraint is below the threshold. Once the utility requirement is above the threshold, the privacy leakage increases linearly. Finally, we show that the optimal weighting of each privacy funnel problem can be found by solving a linear program (LP). Numerical results are shown to illustrate the robustness of our approach.

Physical layer secrecy has attracted much attention in recent years due to its ability to ensure communication secrecy with the use of channel coding and signal processing techniques (and without the explicit use of secret keys) in the physical layer. It serves as a promising technique for highly dynamic or ad hoc systems such as device-to-device and machine-type communication systems. However, the achievable secrecy performance depends highly on the level of CSI at the transmitter, the receiver, and the eavesdropper. In this article, we discuss how different levels of CSI resulting from conventional and unconventional ways of performing training and channel feedback may affect the confidentiality in terms of the information-theoretic (perfect) secrecy rate. The conventional approach refers to the emission of pilot signals from the transmitter and explicit channel feedback from the receiver. This approach is backward compatible with existing systems and allows the receiver to obtain accurate knowledge of the CSI, but may suffer from CSI leakage toward the eavesdropper. Unconventional approaches capitalize on reverse training to prevent CSI leakage and are shown to achieve significant improvements over conventional schemes in certain cases. For example, in a system with four transmit antennas and a single antenna at both the receiver and the eavesdropper, a secrecy rate gain of approximately 0.8 b/channel use at transmit SNR of 16 dB is observed over the full CSI case by providing CSI only to the transmitter (but not the receiver and the eavesdropper).

We consider the block Rayleigh fading multiple-input multiple-output (MIMO) wiretap channel with no prior channel state information (CSI) available at any of the terminals. The channel gains remain constant within a coherence interval of $T$ symbols, and then change to another independent realization in the next coherence interval. The transmitter, the legitimate receiver, and the eavesdropper have $n_{t}$ , $n_{r}$ , and $n_{e} $ antennas, respectively. We determine the exact secure degrees of freedom (s.d.o.f.) of this system when $T\geq 2\min(n_{t},n_{r} )$ . We show that, in this case, the s.d.o.f. is exactly equal to $(\min(n_{t},n_{r})-n_{e})^{+}(T-\min(n_{t},n_{r} ))/T$ . The first term in this expression can be interpreted as the eavesdropper with $n_{e}$ antennas taking away $n_{e} $ antennas from both the transmitter and the legitimate receiver. The second term can be interpreted as a fraction of the s.d.o.f. being lost due to the lack of CSI at the legitimate receiver. In particular, the fraction loss, $\min(n_{t},n_{r} ) /T$ , can be interpreted as the fraction of channel uses dedicated to training the legitimate receiver for it to learn its own CSI. We prove that this s.d.o.f. can be achieved by employing a constant norm channel input, which can be viewed as a generalization of discrete signalling to multiple dimensions.

Introduction This study investigated whether heavy metal levels were higher in people from Taiwan as compared to those from Western countries. Methods We measured the level of heavy metals (lead, mercury, arsenic and cadmium) in the blood of 40 apparently healthy adults. Since mercury does not respond to ethylenediaminetetraacetic acid (EDTA) infusion, only urine lead, arsenic and cadmium levels were determined by applying the body burden concept after calcium disodium EDTA infusion. These three heavy metals were extracted from daily urine samples for three consecutive days. Results The mean blood lead, mercury and cadmium levels of the Taiwanese individuals (24.46 ± 9.69 µg/L, 9.64 ± 6.98 µg/L and 0.73 ± 0.27 µg/L, respectively) were greater than those of the Americans. The Taiwanese also had greater blood mercury and cadmium levels than the Germans. The first-day urine lead, arsenic and cadmium levels were 77.9%, 33.1% and 62.4%, respectively, of the total lead, arsenic and cadmium excretion during the three days. This indicates that the first-day urine lead and cadmium excretion represented most (> 60%) of the lead and cadmium excretion in those three days. Conclusion This study demonstrated that the Taiwanese population has higher blood mercury and cadmium levels than Western populations. To study the urine lead and cadmium body burden of patients, detection of first-day, rather than three-day, urine lead and cadmium levels can be done, as the former yields results that are fairly representative, and is more time- and cost-effective.

This work considers the joint design of training and data transmission in physical-layer secret communication systems, and examines the role of artificial noise (AN) in both of these phases. In particular, AN in the training phase is used to prevent the eavesdropper from obtaining accurate channel state information (CSI) whereas AN in the data transmission phase can be used to mask the transmission of the confidential message. By considering AN-assisted training and secrecy beamforming schemes, we first derive bounds on the achievable secrecy rate and obtain a closed-form approximation that is asymptotically tight at high SNR. Then, by maximizing the approximate achievable secrecy rate, the optimal power allocation between signal and AN in both training and data transmission phases is obtained for both conventional and AN-assisted training based schemes. We show that the use of AN is necessary to achieve a high secrecy rate at high SNR, and its use in the training phase can be more efficient than that in the data transmission phase when the coherence time is large. However, at low SNR, the use of AN provides no advantage since CSI is difficult to obtain in this case. Numerical results are presented to verify our theoretical claims., 38 pages, 5 figures, submitted to IEEE Transactions on Information Theory (submitted November 2015)

We consider the problem of multicasting information from a source to a destination over a multihop network of intermediate relays. However, some of the relays are untrustworthy and may be subject to eavesdropping. The source wishes to enlist their help while keeping the message secret against the eavesdropper. By employing random linear network coding at the relays, the problem is modeled as a noncoherent wiretap channel and is examined in terms of its secrecy capacity. The input distribution is optimized using an efficient projection-based gradient decent algorithm. The untrusted relay recruitment problem is also examined based on the derived secrecy capacity. An interesting scenario is analyzed where each potentially insecure relay may be randomly eavesdropped with a certain probability. Our asymptotic analysis reveals that, with enough untrusted relays, there exists a threshold on the eavesdropping probability below which all untrusted relays should be recruited.

Discriminatory channel estimation (DCE) is a secrecy-enhancing training and channel estimation technique previously proposed in the literature to enhance the effective channel quality difference between the main and the eavesdropper channels (i.e., the channels experienced by the legitimate receiver and the eavesdropper, respectively) in the channel estimation phase. In the past, this was achieved by developing techniques to first provide the transmitter with preliminary estimates of the main channel and by then emitting training signals that embed AN in the null space of the estimated main channel to disrupt the channel estimation at the eavesdropper. Extending upon previous works on DCE, this work proposes a general AN design that does not rely on the availability of the null space of the estimated main channel and, thus, does not require the transmitter to have more antennas than the receiver. In particular, the AN covariance matrix, the pilot signal power, and the linear estimator are jointly determined to minimize the channel estimation error at the receiver subject to a constraint below on the channel estimation error at the eavesdropper. The design is obtained by adopting an alternating optimization approach where the AN and pilot signals at the transmitter and the estimator at the receiver are optimized in turn until no further decrease in channel estimation error is observed. The effectiveness of the proposed scheme is demonstrated through computer simulations.