Abstract. The general trend in semiconductor industry to separate design from fabrication leads to potential threats from untrusted integrated circuit foundries. In particular, malicious hardware components can be covertly inserted at the foundry to implement hidden backdoors for unauthorized exposure of secret information. This paper proposes a new class of hardware Trojans which intentionally induce physical side-channels to convey secret information. We demonstrate power side-channels engineered to leak information below the effective noise power level of the device. Two concepts of very small implementations of Trojan side-channels (TSC) are introduced and evaluated with respect to their feasibility on Xilinx FPGAs. Their lightweight implementations indicate a high resistance to detection by conventional test and inspection methods. Furthermore, the proposed TSCs come with a physical encryption property, so that even a successful detection of the artificially introduced side-channel will not allow unhindered access to the secret information.

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The unique and unpredictable nature of silicon enables the use of physical unclonable functions (PUFs) for chip identification and authentication. Since the function of PUFs depends on minute uncontrollable process variations, a low supply voltage can benefit PUFs by providing high sensitivity to variations and low power consumption as well. Motivated by this, we explore the feasibility of sub-threshold arbiter PUFs in 45nm CMOS technology. By modeling process variations and interconnect imbalance effects at the post-layout design level, we optimize the PUF supply voltage for the minimum power-delay product and investigate the trade-offs on PUF uniqueness and reliability. Moreover, we demonstrate that such a design optimization does not compromise the security of PUFs regarding modeling attacks and side-channel analysis attacks. Our final 64-stage subthreshold PUF design only needs 418 gates and consumes 0.047pJ energy per cycle, which is very promising for low-power wireless sensing and security applications.

This is the first of two companion papers on improved intensity measures of strong seismic ground motions for use in probabilistic seismic demand analysis. It describes the formulation and the development of new intensity measures. The second paper illustrates the application of the developed intensity measures in probabilistic seismic demand analysis. The development of the intensity measures was based on investigations of the seismic responses of three reinforced concrete frame buildings (4, 10, and 16-storey high) designed for Vancouver. The buildings were subjected to a selected set of seismic motions scaled to different intensity levels. Maximum interstorey drifts obtained from nonlinear dynamic analyses were used as response parameters. Based on the results from the analyses, two intensity measures are proposed: one for short- and intermediate-period buildings, and another one for long-period buildings. The proposed intensity measures are superior compared to that represented by the spectral acceleration at the fundamental building period (Sa(T1)), which is currently the most widely used intensity measure in probabilistic seismic demand analysis.

Long non-coding RNA (lncRNA) AC026166.2-001 was found to be down-regulated in laryngeal squamous cell carcinoma (LSCC) tissues and metastatic neck lymph nodes. Decreased AC026166.2-001 was associated with poorer prognosis and may act as a novel biomarker for LSCC patients. In this study, AC026166.2–001 was overexpressed by a lentivirus vector and down-regulated by a small interfering RNA (siRNA). The results of real-time cell analysis (RTCA) and a plate colony formation assay showed that AC026166.2–001 inhibited LSCC cell proliferation and the clone-forming capacity. Cell cycle distribution and related protein changes were measured by flow cytometry. AC026166.2–001 arrested the cell cycle at the G1 phase and induced apoptosis. In addition, AC026166.2–001 decreased cell migration as measured by wound healing assays and transwell migration assays. Moreover, luciferase reporter assay and Western blotting results suggested that AC026166.2–001 acts as a sponge of miR-24-3p and regulates the expression of p27 and cyclin D1. The in vivo results showed that AC026166.2–001 significantly suppressed the growth of LSCC xenografts and promoted apoptosis. We validated the molecular mechanisms underlying AC026166.2–001 in LSCC. This is the first report of AC026166.2–001 acting as a tumor suppressor in LSCC by regulating the miR-24-3p/p27 axis.

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BackgroundLZTS2 (leucine zipper tumor suppressor 2), a candidate tumor suppressor gene, suppresses cell growth and plays a vital role in the carcinogenesis and development of tumors. No studies to date have described methylation of the LZTS2 promoter in human cancers, including LSCC (laryngeal squamous cell carcinoma). Therefore, the aim of this study was to explore the relationship between LZTS2 promoter methylation and risk of LSCC.MethodsIn our study, LZTS2 promoter methylation levels in LSCC tumor and adjacent normal tissues from 96 patients were measured using quantitative methylation-specific polymerase chain reaction (qMSP) assays.ResultsThe qMSP analyses revealed that LZTS2 promoter methylation levels in the LSCC tumor samples were significantly higher than those in paired adjacent healthy tissue samples. Furthermore, LZTS2 methylation levels were elevated in smokers, advanced T classified, and clinically staged patients, as well as in patients with lymph node metastases. In addition, Kaplan-Meier survival curves results showed that overall survival of LSCC patients with hypomethylated LZTS2 promoters was significantly higher than that in patients with hyper-methylated LZTS2 promoters (log-rank test P = 0.028). Meanwhile, the area under the receiver operating characteristic curve was 0.920. The diagnostic threshold value for LZTS2 methylation was 11.63% (94.7% sensitivity and 80.4% specificity).ConclusionsLZTS2 promoter hypermethylation is associated with risk, progression, and prognosis of LSCC in a cohort of 96 human subjects; LZTS2 promoter hypermethylation is a candidate diagnostic and prognostic biomarker for LSCC.

Abstract:With the widespread availability of cell-phone recording devices, source cell-phone identification has become a hot topic in multimedia forensics. At present, the research on the source cell-phone identification in clean conditions has achieved good results, but that in noisy environments is not ideal. This paper proposes a novel source cell-phone identification system suitable for both clean and noisy environments using spectral distribution features of constant Q transform (CQT) domain and multi-scene training method. Based on the analysis, it is found that the identification difficulty lies in different models of cell-phones of the same brand, and their tiny differences are mainly in the middle and low frequency bands. Therefore, this paper extracts spectral distribution features from the CQT domain, which has a higher frequency resolution in the mid-low frequency. To evaluate the effectiveness of the proposed feature, four classification techniques of Support Vector Machine (SVM), Random Forest (RF), Convolutional Neural Network (CNN) and Recurrent Neuron Network-Long Short-Term Memory Neural Network (RNN-BLSTM) are used to identify the source recording device. Experimental results show that the features proposed in this paper have superior performance. Compared with Mel frequency cepstral coefficient (MFCC) and linear frequency cepstral coefficient (LFCC), it enhances the accuracy of cell-phones within the same brand, whether the speech to be tested comprises clean speech files or noisy speech files. In addition, the CNN classification effect is outstanding. In terms of models, the model is established by the multi-scene training method, which improves the distinguishing ability of the model in the noisy environment than single-scenario training method. The average accuracy rate in CNN for clean speech files on the CKC speech database (CKC-SD) and TIMIT Recaptured Database (TIMIT-RD) databases increased from 95.47% and 97.89% to 97.08% and 99.29%, respectively. For noisy speech files with seen noisy types and unseen noisy types, the performance was greatly improved, and most of the recognition rates exceeded 90%. Therefore, the source identification system in this paper is robust to noise.