Android HIV: A Study of Repackaging Malware for Evading Machine-Learning Detection

Machine learning based solutions have been successfully employed for automatic detection of malware in Android applications. However, machine learning models are known to lack robustness against inputs crafted by an adversary. So far, the adversarial examples can only deceive Android malware detectors that rely on syntactic features, and the perturbations can only be implemented by simply modifying Android manifest. While recent Android malware detectors rely more on semantic features from Dalvik bytecode rather than manifest, existing attacking/defending methods are no longer effective. In this paper, we introduce a new highly-effective attack that generates adversarial examples of Android malware and evades being detected by the current models. To this end, we propose a method of applying optimal perturbations onto Android APK using a substitute model. Based on the transferability concept, the perturbations that successfully deceive the substitute model are likely to deceive the original models as well. We develop an automated tool to generate the adversarial examples without human intervention to apply the attacks. In contrast to existing works, the adversarial examples crafted by our method can also deceive recent machine learning based detectors that rely on semantic features such as control-flow-graph. The perturbations can also be implemented directly onto APK's Dalvik bytecode rather than Android manifest to evade from recent detectors. We evaluated the proposed manipulation methods for adversarial examples by using the same datasets that Drebin and MaMadroid (5879 malware samples) used. Our results show that, the malware detection rates decreased from 96% to 1% in MaMaDroid, and from 97% to 1% in Drebin, with just a small distortion generated by our adversarial examples manipulation method.Comment: 15 pages, 11 figure

Elevated circulating level of P2X7 receptor is related to severity of coronary artery stenosis and prognosis of acute myocardial infarction

Background: Acute myocardial infarction (AMI) is a severely life-threatening cardiovascular disease. Previous research has identified an association between the P2X7 receptor (P2X7R) and the development of atherosclerosis. However, the correlation of its expression with the clinical prognosis of patients with AMI remains unclear. The present study aimed to investigate the potential role of P2X7R in Chinese patients with AMI. Methods: Seventy-nine patients with AMI and 48 controls were consecutively enrolled in this prospective observational study. Circulating P2X7R mRNA expression levels and other clinical variables were determined upon admission to the hospital. Patients were followed up for 360 days, and the end-point was considered as the occurrence of major adverse cardiovascular events (MACE). Results: Circulating P2X7R mRNA expression level in peripheral blood mononuclear cells of patients with AMI were significantly higher than those in controls and had promising diagnostic ability of AMI with an area under the curve of 0.928. Furthermore, P2X7R was demonstrated to be correlated positively with the severity of coronary artery stenosis. Additionally, this is the first study to indicate that higher P2X7R mRNA expression is associated with a higher rate of MACE within 360 days after AMI. Conclusions: The present study showed that the circulating level of P2X7R was elevated in AMI patients and was closely associated with the severity of coronary artery stenosis and prognosis of AMI

Towards the discovery of new physics with lepton-universality ratios of b→sℓℓ decays

Tests of lepton-universality as rate ratios in $b\to s \ell\ell$ transitions can be predicted very accurately in the Standard Model. The deficits with respect to expectations reported by the LHCb experiment in muon-to-electron ratios of the $B\to K^{(*)}\ell\ell$ decay rates thus point to genuine manifestations of lepton non-universal new physics. In this paper, we analyse these measurements in the context of effective field theory. First, we discuss the interplay of the different operators in $R_K$ and $R_{K^*}$ and provide predictions for $R_{K^*}$ in the Standard Model and in new-physics scenarios that can explain $R_K$. We also provide approximate numerical formulas for these observables in bins of interest as functions of the relevant Wilson coefficients. Secondly, we perform frequentist fits to $R_{K}$ and $R_{K^*}$. The SM disagrees with these measurements at $3.7\sigma$ significance. We find excellent fits in scenarios with combinations of $\mathcal O_{9(10)}^\ell=\bar s\gamma^\mu b_L~\ell\gamma_\mu(\gamma_5) \ell$ operators, with pulls relative to the Standard Model in the region of $4\sigma$. An important conclusion of our analysis is that a lepton-specific contribution to $\mathcal O_{10}$ is essential to understand the data. Under the hypothesis that new-physics couples selectively to the muons, we also present fits to other $b\to s\mu\mu$ data with a conservative error assessment, and comment on more general scenarios. Finally, we discuss new lepton universality ratios that, if new physics is the origin of the observed discrepancy, should contribute to the statistically significant discovery of new physics in the near future.Comment: Matches published versio

KCAT: A Knowledge-Constraint Typing Annotation Tool

Fine-grained Entity Typing is a tough task which suffers from noise samples extracted from distant supervision. Thousands of manually annotated samples can achieve greater performance than millions of samples generated by the previous distant supervision method. Whereas, it's hard for human beings to differentiate and memorize thousands of types, thus making large-scale human labeling hardly possible. In this paper, we introduce a Knowledge-Constraint Typing Annotation Tool (KCAT), which is efficient for fine-grained entity typing annotation. KCAT reduces the size of candidate types to an acceptable range for human beings through entity linking and provides a Multi-step Typing scheme to revise the entity linking result. Moreover, KCAT provides an efficient Annotator Client to accelerate the annotation process and a comprehensive Manager Module to analyse crowdsourcing annotations. Experiment shows that KCAT can significantly improve annotation efficiency, the time consumption increases slowly as the size of type set expands.Comment: 6 pages, acl2019 demo pape

Galactic Disk Bulk Motions as Revealed by the LSS-GAC DR2

We report a detailed investigation of the bulk motions of the nearby Galactic stellar disk, based on three samples selected from the LSS-GAC DR2: a global sample containing 0.57 million FGK dwarfs out to $\sim$ 2 kpc, a local subset of the global sample consisting $\sim$ 5,400 stars within 150 pc, and an anti-center sample containing $\sim$ 4,400 AFGK dwarfs and red clump stars within windows of a few degree wide centered on the Galactic anti-center. The global sample is used to construct a three-dimensional map of bulk motions of the Galactic disk from the solar vicinity out to $\sim$ 2 kpc with a spatial resolution of $\sim$ 250 pc. Typical values of the radial and vertical components of bulk motion range from $-$15 km s$^{-1}$ to 15 km s$^{-1}$, while the lag behind the circular speed dominates the azimuthal component by up to $\sim$ 15 km s$^{-1}$. The map reveals spatially coherent, kpc-scale stellar flows in the disk, with typical velocities of a few tens km s$^{-1}$. Bending- and breathing-mode perturbations are clearly visible, and vary smoothly across the disk plane. Our data also reveal higher-order perturbations, such as breaks and ripples, in the profiles of vertical motion versus height. From the local sample, we find that stars of different populations exhibit very different patterns of bulk motion. Finally, the anti-center sample reveals a number of peaks in stellar number density in the line-of-sight velocity versus distance distribution, with the nearer ones apparently related to the known moving groups. The "velocity bifurcation" reported by Liu et al. (2012) at Galactocentric radii 10--11 kpc is confirmed. However, just beyond this distance, our data also reveal a new triple-peaked structure.Comment: 27 pages, 17 figures, Accepted for publication in a special issue of Research in Astronomy and Astrophysics on LAMOST science