Meteor: Improved Secure 3-Party Neural Network Inference with Reducing Online Communication Costs

Secure neural network inference has been a promising solution to private Deep-Learning-as-a-Service, which enables the service provider and user to execute neural network inference without revealing their private inputs. However, the expensive overhead of current schemes is still an obstacle when applied in real applications. In this work, we present \textsc{Meteor}, an online communication-efficient and fast secure 3-party computation neural network inference system aginst semi-honest adversary in honest-majority. The main contributions of \textsc{Meteor} are two-fold: \romannumeral1) We propose a new and improved 3-party secret sharing scheme stemming from the \textit{linearity} of replicated secret sharing, and design efficient protocols for the basic cryptographic primitives, including linear operations, multiplication, most significant bit extraction, and multiplexer. \romannumeral2) Furthermore, we build efficient and secure blocks for the widely used neural network operators such as Matrix Multiplication, ReLU, and Maxpool, along with exploiting several specific optimizations for better efficiency. Our total communication with the setup phase is a little larger than SecureNN (PoPETs\u2719) and \textsc{Falcon} (PoPETs\u2721), two state-of-the-art solutions, but the gap is not significant when the online phase must be optimized as a priority. Using \textsc{Meteor}, we perform extensive evaluations on various neural networks. Compared to SecureNN and \textsc{Falcon}, we reduce the online communication costs by up to $25.6\times$ and $1.5\times$, and improve the running-time by at most $9.8\times$ (resp. $8.1\times$) and $1.5\times$ (resp. $2.1\times$) in LAN (resp. WAN) for the online inference

FLOD: Oblivious Defender for Private Byzantine-Robust Federated Learning with Dishonest-Majority

\textit{Privacy} and \textit{Byzantine-robustness} are two major concerns of federated learning (FL), but mitigating both threats simultaneously is highly challenging: privacy-preserving strategies prohibit access to individual model updates to avoid leakage, while Byzantine-robust methods require access for comprehensive mathematical analysis. Besides, most Byzantine-robust methods only work in the \textit{honest-majority} setting. We present $\mathsf{FLOD}$, a novel oblivious defender for private Byzantine-robust FL in dishonest-majority setting. Basically, we propose a novel Hamming distance-based aggregation method to resist $>1/2$ Byzantine attacks using a small \textit{root-dataset} and \textit{server-model} for bootstrapping trust. Furthermore, we employ two non-colluding servers and use additive homomorphic encryption ($\mathsf{AHE}$) and secure two-party computation (2PC) primitives to construct efficient privacy-preserving building blocks for secure aggregation, in which we propose two novel in-depth variants of Beaver Multiplication triples (MT) to reduce the overhead of Bit to Arithmetic ($\mathsf{Bit2A}$) conversion and vector weighted sum aggregation ($\mathsf{VSWA}$) significantly. Experiments on real-world and synthetic datasets demonstrate our effectiveness and efficiency: (\romannumeral1) $\mathsf{FLOD}$ defeats known Byzantine attacks with a negligible effect on accuracy and convergence, (\romannumeral2) achieves a reduction of $\approx 2\times$ for offline (resp. online) overhead of $\mathsf{Bit2A}$ and $\mathsf{VSWA}$ compared to $\mathsf{ABY}$-$\mathsf{AHE}$ (resp. $\mathsf{ABY}$-$\mathsf{MT}$) based methods (NDSS\u2715), (\romannumeral3) and reduces total online communication and run-time by $167$-$1416\times$ and $3.1$-$7.4\times$ compared to $\mathsf{FLGUARD}$ (Crypto Eprint 2021/025)

Real-Time Neural Signals of Disorder and Order Perception

Order and disorder are prevalent in everyday life, yet little is known about the neural real-time processing that occurs during the perception of disorder relative to order. In the present study, from a cognitive perspective, by adopting the ERP method, we aimed to examine the elicited real-time neural signals of disorder and order perception when participants processed physical environmental and basic visual disorder and order pictures in an irrelevant red or green rectangle detection task, and we attempted to test the hypothesis of cognitive disfluency in disorder perception. Generally, we observed that at each measured time interval, the ERPs elicited by order stimuli were more positive (less negative) in amplitude than those elicited by disorder stimuli at the frontal electrodes (represented by F7/F8, FT7/FT8, Fz, and FCz), whereas at the posterior electrodes (represented by P7/P8, PO7/PO8, Pz, and POz), the opposite was true. These data reveal for the first time the neural underpinnings of disorder and order perception, extending our understanding of the nature of disorder and order. This study also contributes to the cognitive fluency literature and indirectly expands the research on disorder and order stimuli in cognitive fluency

Experimental Determination of Effective Minority Carrier Lifetime in HgCdTe Photovoltaic Detectors Using Optical and Electrical Methods

This paper presents experiment measurements of minority carrier lifetime using three different methods including modified open-circuit voltage decay (PIOCVD) method, small parallel resistance (SPR) method, and pulse recovery technique (PRT) on pn junction photodiode of the HgCdTe photodetector array. The measurements are done at the temperature of operation near 77 K. A saturation constant background light and a small resistance paralleled with the photodiode are used to minimize the influence of the effect of junction capacitance and resistance on the minority carrier lifetime extraction in the PIOCVD and SPR measurements, respectively. The minority carrier lifetime obtained using the two methods is distributed from 18 to 407 ns and from 0.7 to 110 ns for the different Cd compositions. The minority carrier lifetime extracted from the traditional PRT measurement is found in the range of 4 to 20 ns for x=0.231–0.4186. From the results, it can be concluded that the minority carrier lifetime becomes longer with the increase of Cd composition and the pixels dimensional area

“You Should Have Seen the Look on Your Face…”: Self-awareness of Facial Expressions

The awareness of facial expressions allows one to better understand, predict, and regulate his/her states to adapt to different social situations. The present research investigated individuals’ awareness of their own facial expressions and the influence of the duration and intensity of expressions in two self-reference modalities, a real-time condition and a video-review condition. The participants were instructed to respond as soon as they became aware of any facial movements. The results revealed that awareness rates were 57.79% in the real-time condition and 75.92% in the video-review condition. The awareness rate was influenced by the intensity and (or) the duration. The intensity thresholds for individuals to become aware of their own facial expressions were calculated using logistic regression models. The results of Generalized Estimating Equations (GEE) revealed that video-review awareness was a significant predictor of real-time awareness. These findings extend understandings of human facial expression self-awareness in two modalities

Household air pollution and epigenetic aging in Xuanwei, China

BACKGROUND: Household air pollution (HAP) from indoor combustion of solid fuel is a global health burden linked to lung cancer. In Xuanwei, China, lung cancer rate for nonsmoking women is among the highest in the world and largely attributed to high levels of polycyclic aromatic hydrocarbons (PAHs) that are produced from combustion of smoky (bituminous) coal used for cooking and heating. Epigenetic age acceleration (EAA), a DNA methylation-based biomarker of aging, has been shown to be highly correlated with biological processes underlying the susceptibility of age-related diseases. We aim to assess the association between HAP exposure and EAA. METHODS: We analyzed data from 106 never-smoking women from Xuanwei, China. Information on fuel type was collected using a questionnaire, and validated exposure models were used to predict levels of 43 HAP constituents. Exposure clusters were identified using hierarchical clustering. EAA was derived for five epigenetic clocks defined as the residuals resulting from regressing each clock on chronological age. We used generalized estimating equations to test associations between exposure clusters derived from predicted levels of HAP exposure, ambient 5-methylchrysene (5-MC), a PAH previously found to be associated with risk of lung cancer, and EAA, while accounting for repeated-measurements and confounders. RESULTS: We observed an increase in GrimAge EAA for clusters with 31 and 33 PAHs reflecting current (β = 0.77 y per standard deviation (SD) increase, 95 % CI:0.36,1.19) and childhood (β = 0.92 y per SD, 95 % CI:0.40,1.45) exposure, respectively. 5-MC (ng/m 3-year) was found to be associated with GrimAge EAA for current (β = 0.15 y, 95 % CI:0.05,0.25) and childhood (β = 0.30 y, 95 % CI:0.13,0.47) exposure. CONCLUSIONS: Our findings suggest that exposure to PAHs from indoor smoky coal combustion, particularly 5-MC, is associated with GrimAge EAA, a biomarker of mortality

Overall and cause-specific mortality rates among men and women with high exposure to indoor air pollution from the use of smoky and smokeless coal: a cohort study in Xuanwei, China

OBJECTIVES: Never-smoking women in Xuanwei (XW), China, have some of the highest lung cancer rates in the country. This has been attributed to the combustion of smoky coal used for indoor cooking and heating. The aim of this study was to evaluate the spectrum of cause-specific mortality in this unique population, including among those who use smokeless coal, considered 'cleaner' coal in XW, as this has not been well-characterised. DESIGN: Cohort study. SETTING: XW, a rural region of China where residents routinely burn coal for indoor cooking and heating. PARTICIPANTS: Age-adjusted, cause-specific mortality rates between 1976 and 2011 were calculated and compared among lifetime smoky and smokeless coal users in a cohort of 42 420 men and women from XW. Mortality rates for XW women were compared with those for a cohort of predominately never-smoking women in Shanghai. RESULTS: Mortality in smoky coal users was driven by cancer (41%), with lung cancer accounting for 88% of cancer deaths. In contrast, cardiovascular disease (CVD) accounted for 32% of deaths among smokeless coal users, with 7% of deaths from cancer. Total cancer mortality was four times higher among smoky coal users relative to smokeless coal users, particularly for lung cancer (standardised rate ratio (SRR)=17.6). Smokeless coal users had higher mortality rates of CVD (SRR=2.9) and pneumonia (SRR=2.5) compared with smoky coal users. These patterns were similar in men and women, even though XW women rarely smoked cigarettes. Women in XW, regardless of coal type used, had over a threefold higher rate of overall mortality, and most cause-specific outcomes were elevated compared with women in Shanghai. CONCLUSIONS: Cause-specific mortality burden differs in XW based on the lifetime use of different coal types. These observations provide evidence that eliminating all coal use for indoor cooking and heating is an important next step in improving public health particularly in developing countries