Boosting the precision of virtual call integrity protection with partial pointer analysis for C++

© 2017 Association for Computing Machinery. We present, Vip, an approach to boosting the precision of Virtual call Integrity Protection for large-scale real-world C++ programs (e.g., Chrome) by using pointer analysis for the first time. Vip introduces two new techniques: (1) a sound and scalable partial pointer analysis for discovering statically the sets of legitimate targets at virtual callsites from separately compiled C++ modules and (2) a lightweight instrumentation technique for performing (virtual call) integrity checks at runtime. Vip raises the bar against vtable hijacking attacks by providing stronger security guarantees than the CHA-based approach with comparable performance overhead. Vip is implemented in LLVM-3.8.0 and evaluated using SPEC programs and Chrome. Statically, Vip protects virtual calls more effectively than CHA by significantly reducing the sets of legitimate targets permitted at 20.3% of the virtual callsites per program, on average. Dynamically, Vip incurs an average (maximum) instrumentation overhead of 0.7% (3.3%), making it practically deployable as part of a compiler tool chain

Hard X-ray and UV Observations of the 2005 January 15 Two-ribbon Flare

In this paper, we present comprehensive analysis of a two-ribbon flare observed in UV 1600{\AA} by Transition Region and Coronal Explorer and in HXRs by Reuven Ramaty High Energy Solar Spectroscopic Imager. HXR (25-100 keV) imaging observations show two kernels of size (FWHM) 15?? moving along the two UV ribbons. We find the following results. (1) UV brightening is substantially enhanced wherever and whenever the compact HXR kernel is passing, and during the HXR transit across a certain region, the UV count light curve in that region is temporally correlated with the HXR total flux light curve. After the passage of the HXR kernel, the UV light curve exhibits smooth monotonical decay. (2)We measure the apparent motion speed of the HXR sources and UV ribbon fronts, and decompose the motion into parallel and perpendicular motions with respect to the magnetic polarity inversion line (PIL). It is found that HXR kernels and UV fronts exhibit similar apparent motion patterns and speeds. The parallel motion dominates during the rise of the HXR emission, and the perpendicular motion starts and dominates at the HXR peak, the apparent motion speed being 10-40 km s-1. (3) We also find that UV emission is characterized by a rapid rise correlated with HXRs, followed by a long decay on timescales of 15-30 minutes. The above analysis provides evidence that UV brightening is primarily caused by beam heating, which also produces thick-target HXR emission. The thermal origin of UV emission cannot be excluded, but would produce weaker heating by one order of magnitude. The extended UV ribbons in this event are most likely a result of sequential reconnection along the PIL, which produces individual flux tubes (post-flare loops), subsequent non-thermal energy release and heating in these flux tubes, and then the very long cooling time of the transition region at the feet of these flux tubes.Comment: 8 figure

Static detection of control-flow-related vulnerabilities using graph embedding

© 2019 IEEE. Static vulnerability detection has shown its effectiveness in detecting well-defined low-level memory errors. However, high-level control-flow related (CFR) vulnerabilities, such as insufficient control flow management (CWE-691), business logic errors (CWE-840), and program behavioral problems (CWE-438), which are often caused by a wide variety of bad programming practices, posing a great challenge for existing general static analysis solutions. This paper presents a new deep-learning-based graph embedding approach to accurate detection of CFR vulnerabilities. Our approach makes a new attempt by applying a recent graph convolutional network to embed code fragments in a compact and low-dimensional representation that preserves high-level control-flow information of a vulnerable program. We have conducted our experiments using 8,368 real-world vulnerable programs by comparing our approach with several traditional static vulnerability detectors and state-of-the-art machine-learning-based approaches. The experimental results show the effectiveness of our approach in terms of both accuracy and recall. Our research has shed light on the promising direction of combining program analysis with deep learning techniques to address the general static analysis challenges

Atmospheric reactive nitrogen concentrations at ten sites with contrasting land use in an arid region of central Asia

Atmospheric concentrations of reactive nitrogen (N<sub>r</sub>) species from 2009 to 2011 are reported for ten sites in Xinjiang, China, an arid region of central Asia. Concentrations of NH<sub>3</sub>, NO<sub>2</sub>, particulate ammonium and nitrate (<i>p</i>NH<sub>4</sub><sup>+</sup> and <i>p</i>NO<sub>3</sub><sup>−</sup>) showed large spatial and seasonal variation and averaged 7.71, 9.68, 1.81 and 1.13 μg N m<sup>−3</sup>, and PM<sub>10</sub> concentrations averaged 249.2 μg m<sup>−3</sup> across all sites. Lower NH<sub>3</sub> concentrations and higher NO<sub>2</sub>, <i>p</i>NH<sub>4</sub><sup>+</sup> and <i>p</i>NO<sub>3</sub><sup>−</sup> concentrations were found in winter, reflecting serious air pollution due to domestic heating in winter and other anthropogenic sources such as increased emissions from motor traffic and industry. The increasing order of total concentrations of N<sub>r</sub> species was alpine grassland; desert, desert-oasis ecotone; desert in an oasis; farmland; suburban and urban ecosystems. Lower ratios of secondary particles (NH<sub>4</sub><sup>+</sup> and NO<sub>3</sub><sup>−</sup>) were found in the desert and desert-oasis ecotone, while urban and suburban areas had higher ratios, which implied that anthropogenic activities have greatly influenced local air quality and must be controlled

BiOX (X = Cl, Br, I) photocatalysts prepared using NaBiO 3 as the Bi source: Characterization and catalytic performance

The Bismuth oxyhalides, crystalline BiOX (X = Cl, Br, I) were prepared via a facile method, using NaBiO 3 and HX aqueous solutions as the raw materials for the first time. The systematic microstructure and optical property characterizations of the BiOX photocatalysts demonstrated the reliability of this new and facile preparation approach. The photocatalytic activity on the degradation of typical phenolic endocrine disrupting chemicals over BiOX and P25 were evaluated under Xenon-light irradiation and the initial photocatalytic mechanism was discussed based on the band edge potential analysis. © 2009.postprin

A modified protocol for the detection of three different mRNAs with a new-generation in situ hybridization chain reaction on frozen sections

A new multiple fluorescence in situ hybridization method based on hybridization chain reaction was recently reported, enabling simultaneous mapping of multiple target mRNAs within intact zebrafish and mouse embryos. With this approach, DNA probes complementary to target mRNAs trigger chain reactions in which metastable fluorophore-labeled DNA hairpins self-assemble into fluorescent amplification polymers. The formation of the specific polymers enhances greatly the sensitivity of multiple fluorescence in situ hybridization. In this study we describe the optimal parameters (hybridization chain reaction time and temperature, hairpin and salt concentration) for multiple fluorescence in situ hybridization via amplification of hybridization chain reaction for frozen tissue sections. The combined use of fluorescence in situ hybridization and immunofluorescence, together with other control experiments (sense probe, neutralization and competition, RNase treatment, and anti-sense probe without initiator) confirmed the high specificity of the fluorescence in situ hybridization used in this study. Two sets of three different mRNAs for oxytocin, vasopressin and somatostatin or oxytocin, vasopressin and thyrotropin releasing hormone were successfully visualized via this new method. We believe that this modified protocol for multiple fluorescence in situ hybridization via hybridization chain reaction would allow researchers to visualize multiple target nucleic acids in the future

Muscle strength and gait speed rather than lean mass are better indicators for poor cognitive function in older men

We aimed to examine muscle strength, function and mass in relation to cognition in older men. This cross-sectional data-set included 292 men aged ≥60 yr. Handgrip strength (kg) was measured by dynamometry, gait speed by 4-metre walk (m/s) and appendicular lean mass (kg) by dual-energy x-ray absorptiometry. Cognition was assessed across four domains: psychomotor function, attention, visual learning and working memory. Composite scores for overall cognition were calculated. Bivariate analyses indicated that handgrip strength and gait speed were positively associated with cognitive function. After accounting for confounders, positive associations between individual muscle (or physical) measures and cognitive performance were sustained for handgrip strength and psychomotor function, gait speed and psychomotor function, gait speed and attention, handgrip strength and overall cognition, and gait speed and overall cognition. In multivariable models, handgrip strength and gait speed independently predicted psychomotor function and overall cognition. No associations were detected between lean mass and cognition after adjusting for confounders. Thus, low muscle strength and slower gait speed, rather than low lean mass, were associated with poor cognition in older men

Acoustic phonon recycling for photocarrier generation in graphene-WS_{2} heterostructures

Electron-phonon scattering is the key process limiting the efficiency of modern nanoelectronic and optoelectronic devices, in which most of the incident energy is converted to lattice heat and finally dissipates into the environment. Here, we report an acoustic phonon recycling process in graphene-WS_{2} heterostructures, which couples the heat generated in graphene back into the carrier distribution in WS_{2}. This recycling process is experimentally recorded by spectrally resolved transient absorption microscopy under a wide range of pumping energies from 1.77 to 0.48 eV and is also theoretically described using an interfacial thermal transport model. The acoustic phonon recycling process has a relatively slow characteristic time (>100 ps), which is beneficial for carrier extraction and distinct from the commonly found ultrafast hot carrier transfer (~1 ps) in graphene-WS_{2} heterostructures. The combination of phonon recycling and carrier transfer makes graphene-based heterostructures highly attractive for broadband high-efficiency electronic and optoelectronic applications

DeepWukong: Statically Detecting Software Vulnerabilities Using Deep Graph Neural Network

Static bug detection has shown its effectiveness in detecting well-defined memory errors, e.g., memory leaks, buffer overflows, and null dereference. However, modern software systems have a wide variety of vulnerabilities. These vulnerabilities are extremely complicated with sophisticated programming logic, and these bugs are often caused by different bad programming practices, challenging existing bug detection solutions. It is hard and labor-intensive to develop precise and efficient static analysis solutions for different types of vulnerabilities, particularly for those that may not have a clear specification as the traditional well-defined vulnerabilities. This article presents DeepWukong, a new deep-learning-based embedding approach to static detection of software vulnerabilities for C/C++ programs. Our approach makes a new attempt by leveraging advanced recent graph neural networks to embed code fragments in a compact and low-dimensional representation, producing a new code representation that preserves high-level programming logic (in the form of control-and data-flows) together with the natural language information of a program. Our evaluation studies the top 10 most common C/C++ vulnerabilities during the past 3 years. We have conducted our experiments using 105,428 real-world programs by comparing our approach with four well-known traditional static vulnerability detectors and three state-of-the-art deep-learning-based approaches. The experimental results demonstrate the effectiveness of our research and have shed light on the promising direction of combining program analysis with deep learning techniques to address the general static code analysis challenges

The native cistrome and sequence motif families of the maize ear

Elucidating the transcriptional regulatory networks that underlie growth and development requires robust ways to define the complete set of transcription factor (TF) binding sites. Although TF-binding sites are known to be generally located within accessible chromatin regions (ACRs), pinpointing these DNA regulatory elements globally remains challenging. Current approaches primarily identify binding sites for a single TF (e.g. ChIP-seq), or globally detect ACRs but lack the resolution to consistently define TF-binding sites (e.g. DNAse-seq, ATAC-seq). To address this challenge, we developed MNase-defined cistrome-Occupancy Analysis (MOA-seq), a high-resolution (< 30 bp), high-throughput, and genome-wide strategy to globally identify putative TF-binding sites within ACRs. We used MOA-seq on developing maize ears as a proof of concept, able to define a cistrome of 145,000 MOA footprints (MFs). While a substantial majority (76%) of the known ATAC-seq ACRs intersected with the MFs, only a minority of MFs overlapped with the ATAC peaks, indicating that the majority of MFs were novel and not detected by ATAC-seq. MFs were associated with promoters and significantly enriched for TF-binding and long-range chromatin interaction sites, including for the well-characterized FASCIATED EAR4, KNOTTED1, and TEOSINTE BRANCHED1. Importantly, the MOA-seq strategy improved the spatial resolution of TF-binding prediction and allowed us to identify 215 motif families collectively distributed over more than 100,000 non-overlapping, putatively-occupied binding sites across the genome. Our study presents a simple, efficient, and high-resolution approach to identify putative TF footprints and binding motifs genome-wide, to ultimately define a native cistrome atlas