Searcharxiv⌕ Search

arXiv subjects

Chun Yang

Publications and source records attributed to Chun Yang.

52 records · Page 3Linked to original sources
arXiv2020

Saturation Memory Access: Mitigating Memory Spatial Errors without Terminating Programs

Memory spatial errors, i.e., buffer overflow vulnerabilities, have been a well-known issue in computer security for a long time and remain one of the root causes of exploitable vulnerabilities. Most of the existing mitigation tools adopt a fail-stop strategy to protect programs from intrusions, which means the victim program will be terminated upon detecting a memory safety violation. Unfortunately, the fail-stop strategy harms the availability of software. In this paper, we propose Saturation Memory Access (SMA), a memory spatial error mitigation mechanism that prevents out-of-bounds access without terminating a program. SMA is based on a key observation that developers generally do not rely on out-of-bounds accesses to implement program logic. SMA modifies dynamic memory allocators and adds paddings to objects to form an enlarged object boundary. By dynamically correcting all the out-of-bounds accesses to operate on the enlarged protecting boundaries, SMA can tolerate out-of-bounds accesses. For the sake of compatibility, we chose tagged pointers to record the boundary metadata of a memory object in the pointer itself, and correct the address upon detecting out-of-bounds access. We have implemented the prototype of SMA on LLVM 10.0. Our results show that our compiler enables the programs to execute successfully through buffer overflow attacks. Experiments on MiBench show that our prototype incurs an overhead of 78\%. Further optimizations would require ISA supports.

cs.CR↗
arXiv2020

DangKiller: Eliminating Dangling Pointers Efficiently via Implicit Identifier

Use-After-Free vulnerabilities, allowing the attacker to access unintended memory via dangling pointers, are more threatening. However, most detection schemes can only detect dangling pointers and invalid them, but not provide a tolerance mechanism to repair the errors at runtime. Also, these techniques obtain and manage the metadata inefficiently with complex structures and too much scan (sweep). The goal of this paper is to use compiler instrumentation to eliminate dangling pointers automatically and efficiently. In this paper, we observe that most techniques lack accurate efficient pointer graph metadata maintaining methods, so they need to scan the log to reduce the redundancy and sweep the whole address space to find dangling pointers. Also, they lack a direct, efficiently obtaining metadata approach. The key insight of this paper is that a unique identifier can be used as a key to a hash or direct-map algorithm. Thus, this paper maintains the same implicit identifier with each memory object and its corresponding referent. Associating the unique ID with metadata for memory objects, obtaining and managing the pointer graph metadata can be efficiently. Therefore, with the delayed free technique adopted into C/C++, we present the DangKiller as a novel and lightweight dangling pointer elimination solution. We first demonstrate the MinFat Pointer, which can calculate unique implicit ID for each object and pointer quickly, and use hash algorithm to obtain metadata. Secondly, we propose the Log Cache and Log Compression mechanism based on the ID to decrease the redundancy of dangling pointer candidates. Coupled with the Address Tagging architecture on an ARM64 system, our experiments show that the DangKiller can eliminate use-after-free vulnerabilities at only 11% and 3% runtime overheads for the SPEC CPU2006 and 2017 benchmarks respectively, except for unique cases.

cs.CR↗
arXiv2019

The spectral function of Mott-insulating Hubbard ladders: From fractionalized excitations to coherent quasi-particles

We study the spectral function of two-leg Hubbard ladders with the time-dependent density matrix renormalization group method (tDMRG). The high-resolution spectrum displays features of spin-charge separation and a scattering continuum of excitations with coherent bands of bound states `leaking' from it. As the inter-leg hopping is increased, the continuum in the bonding channel moves to higher energies and spinon and holon branches merge into a single coherent quasi-particle band. Simultaneously, the spectrum undergoes a crossover from a regime with two minima at incommensurate values of $k_x$ (a Mott insulator), to one with a single minimum at $k_x=π$ (a band insulator). We identify the presence of a continuum of scattering states consisting of a triplon and a polaron. We analyze the processes leading to quasiparticle formation by studying the time evolution of charge and spin degrees of freedom in real space after the hole is created. At short times, incoherent holons and spinons are emitted but after a characteristic time $τ$ charge and spin form polarons that propagate coherently.

cond-mat.str-el↗
arXiv2018

Security Event Recognition for Visual Surveillance

With rapidly increasing deployment of surveillance cameras, the reliable methods for automatically analyzing the surveillance video and recognizing special events are demanded by different practical applications. This paper proposes a novel effective framework for security event analysis in surveillance videos. First, convolutional neural network (CNN) framework is used to detect objects of interest in the given videos. Second, the owners of the objects are recognized and monitored in real-time as well. If anyone moves any object, this person will be verified whether he/she is its owner. If not, this event will be further analyzed and distinguished between two different scenes: moving the object away or stealing it. To validate the proposed approach, a new video dataset consisting of various scenarios is constructed for more complex tasks. For comparison purpose, the experiments are also carried out on the benchmark databases related to the task on abandoned luggage detection. The experimental results show that the proposed approach outperforms the state-of-the-art methods and effective in recognizing complex security events.

cs.CV↗
arXiv2018

Triple condensate halo from water droplets impacting on cold surfaces

Understanding the dynamics in the deposition of water droplets onto solid surfaces is of importance from both fundamental and practical viewpoints. While the deposition of a water droplet onto a heated surface is extensively studied, the characteristics of depositing a droplet onto a cold surface and the phenomena leading to such behavior remain elusive. Here we report the formation of a triple condensate halo observed during the deposition of a water droplet onto a cold surface, due to the interplay between droplet impact dynamics and vapor diffusion. Two subsequent condensation stages occur during the droplet spreading and cooling processes, engendering this unique condensate halo with three distinctive bands. We further proposed a scaling model to interpret the size of each band, and the model is validated by the experiments of droplets with different impact velocity and varying substrate temperature. Our experimental and theoretical investigation of the droplet impact dynamics and the associated condensation unravels the mass and heat transfer among droplet, vapor and substrate, offer a new sight for designing of heat exchange devices.

physics.flu-dyn↗
arXiv2017

Unique shape changes during freezing of a nanofluid droplet

Understanding the dynamics during freezing of nanofluid droplets is of importance from a fundamental and practical viewpoint. While the freezing of a water droplet has been extensively studied, little information is available about the characteristics of freezing a nanofluid droplet. Here, we report unique shape changes observed during the freezing process of a nanofluid droplet. Instead of forming a pointy tip on the frozen deionized water droplet, we found that the top of a frozen nanofluid droplet exhibits a flat plateau shape and such plateau becomes larger with increasing nanoparticle concentration. We ascribe this characteristic shape change to an outward Marangoni flow which moves liquid from the droplet interior to its vertexes, thus engendering the volume redistribution and shape changes. Moreover, we also observed a particle ring pattern formed during freezing of a nanofluid droplet, which is similar to the well-known coffee stain phenomenon occurring during evaporation of a water droplet with dispersed particles. We believe our reported phenomena are not only of fundamental interest but have potential applications in the freezing of nanofluids for energy storage and developing nanofluid based new microfabrication methods.

physics.flu-dyn↗
arXiv2017

AdaDNNs: Adaptive Ensemble of Deep Neural Networks for Scene Text Recognition

Recognizing text in the wild is a really challenging task because of complex backgrounds, various illuminations and diverse distortions, even with deep neural networks (convolutional neural networks and recurrent neural networks). In the end-to-end training procedure for scene text recognition, the outputs of deep neural networks at different iterations are always demonstrated with diversity and complementarity for the target object (text). Here, a simple but effective deep learning method, an adaptive ensemble of deep neural networks (AdaDNNs), is proposed to simply select and adaptively combine classifier components at different iterations from the whole learning system. Furthermore, the ensemble is formulated as a Bayesian framework for classifier weighting and combination. A variety of experiments on several typical acknowledged benchmarks, i.e., ICDAR Robust Reading Competition (Challenge 1, 2 and 4) datasets, verify the surprised improvement from the baseline DNNs, and the effectiveness of AdaDNNs compared with the recent state-of-the-art methods.

cs.CV↗
arXiv2017

Unveiling the internal entanglement structure of the Kondo singlet

We disentangle all the individual degrees of freedom in the quantum impurity problem to deconstruct the Kondo singlet, both in real and energy space, by studying the contribution of each individual free electron eigenstate. This is a problem of two spins coupled to a bath, where the bath is formed by the remaining conduction electrons. Being a mixed state, we resort to the "concurrence" to quantify entanglement. We identify "projected natural orbitals" that allow us to individualize a single-particle electronic wave function that is responsible of more than $90\%$ of the impurity screening. In the weak coupling regime, the impurity is entangled to an electron at the Fermi level, while in the strong coupling regime, the impurity counterintuitively entangles mostly with the high energy electrons and disentangles completely from the low-energy states carving a "hole" around the Fermi level. This enables one to use concurrence as a pseudo order parameter to compute the characteristic "size" of the Kondo cloud, beyond which electrons are are weakly correlated to the impurity and are dominated by the physics of the boundary.

cond-mat.str-el↗
arXiv2015

Spectral function of the 2D Hubbard model: a density matrix renormalization group plus cluster perturbation theory study

We study the spectral function of the 2D Hubbard model using cluster perturbation theory, and the density matrix renormalization group as a cluster solver. We reconstruct the two-dimensional dispersion at, and away from half-filling using 2xL ladders, with L up to 80 sites, yielding results with unprecedented resolution in excellent agreement with quantum Monte Carlo. The main features of the spectrum can be described with a mean-field dispersion, while kinks and pseudogap traced back to scattering between spin and charge degrees of freedom.

cond-mat.str-el↗
arXiv2015

Electroosmosis in conducting nanofluidic channels

Theoretical modeling of electroosmosis through conducting (ideally polarizable) nanochannels is reported. Based on the theory of induced charge electrokinetics, a novel nanofluidic system which possesses both adjustable ion selective characteristics and flexible flow control is proposed. Such nanofluidic devices operate only with very low gate control voltage applied on the conductive walls of nanochannels, and thus even can be energized by normal batteries. We believe that it is possible to use such metal-electrolyte configurations to overcome the difficulties met with conventional metal-isolator-electrolyte systems for nanofluidic applications.

physics.flu-dyn↗
arXiv2015

Electroosmotic mobilities of non-Newtonian fluids

Numerical analyses of transient electro-osmosis of a typical non-Newtonian liquid induced by DC and AC electric fields in a rectangular microchannel are conducted in the framework of continuum fluid mechanics. The famous power-law constitutive model is used to express the fluid dynamic viscosity in terms of the velocity gradient. Transient start-up characteristics of electro-osmotic power-law liquid flow in rectangular microchannels are simulated by using finite element method. Under a DC electric field, it is found out and the fluid is more inert to the external electric field and the steady-state velocity profile becomes more plug-like with decrease of the flow behavior index of the power-law liquids. The numerical calculations also confirm the validity of the generalized Smoluchowski slip velocity which can serve as the counterpart for the classic Smoluchowski slip velocity when dealing with electrokinetic flow of non-Newtonian power-law fluids. Under AC electric fields, the fluid is more obviously accelerated during oscillations and the amplitude of the oscillating velocity is closer to the magnitude of the generalized Smoluchowski velocity as the fluid behavior index increases. These dynamic predictions are of practical significance for the design of microfluidic devices that manipulate non-Newtonian fluids such as biofluids, polymer solutions and colloidal suspensions.

physics.flu-dyn↗
arXiv2015

Numerical analysis of dynamic electro-osmotic flows of non-Newtonian fluids in rectangular microchannels

Numerical analyses of transient electro-osmosis of a typical non-Newtonian liquid induced by DC and AC electric fields in a rectangular microchannel are conducted in the framework of continuum fluid mechanics. The famous power-law constitutive model is used to express the fluid dynamic viscosity in terms of the velocity gradient. Transient start-up characteristics of electro-osmotic power-law liquid flow in rectangular microchannels are simulated by using finite element method. Under a DC electric field, it is found out and the fluid is more inert to the external electric field and the steady-state velocity profile becomes more plug-like with decrease of the flow behavior index of the power-law liquids. The numerical calculations also confirm the validity of the generalized Smoluchowski slip velocity which can serve as the counterpart for the classic Smoluchowski slip velocity when dealing with electrokinetic flow of non-Newtonian power-law fluids. Under AC electric fields, the fluid is more obviously accelerated during oscillations and the amplitude of the oscillating velocity is closer to the magnitude of the generalized Smoluchowski velocity as the fluid behavior index increases. These dynamic predictions are of practical significance for the design of microfluidic devices that manipulate non-Newtonian fluids such as biofluids, polymer solutions and colloidal suspensions.

physics.flu-dyn↗
arXiv2014

Learning to Diversify via Weighted Kernels for Classifier Ensemble

Classifier ensemble generally should combine diverse component classifiers. However, it is difficult to give a definitive connection between diversity measure and ensemble accuracy. Given a list of available component classifiers, how to adaptively and diversely ensemble classifiers becomes a big challenge in the literature. In this paper, we argue that diversity, not direct diversity on samples but adaptive diversity with data, is highly correlated to ensemble accuracy, and we propose a novel technology for classifier ensemble, learning to diversify, which learns to adaptively combine classifiers by considering both accuracy and diversity. Specifically, our approach, Learning TO Diversify via Weighted Kernels (L2DWK), performs classifier combination by optimizing a direct but simple criterion: maximizing ensemble accuracy and adaptive diversity simultaneously by minimizing a convex loss function. Given a measure formulation, the diversity is calculated with weighted kernels (i.e., the diversity is measured on the component classifiers' outputs which are kernelled and weighted), and the kernel weights are automatically learned. We minimize this loss function by estimating the kernel weights in conjunction with the classifier weights, and propose a self-training algorithm for conducting this convex optimization procedure iteratively. Extensive experiments on a variety of 32 UCI classification benchmark datasets show that the proposed approach consistently outperforms state-of-the-art ensembles such as Bagging, AdaBoost, Random Forests, Gasen, Regularized Selective Ensemble, and Ensemble Pruning via Semi-Definite Programming.

cs.LG↗
arXiv2010

Fine Splitting in Charmonium Spectrum with Channel Coupling Effect

We study the fine splitting in charmonium spectrum in quark model with the channel coupling effect, including $DD$, $DD^*$, $D^*D^*$ and $D_sD_s$, $D_sD_s^*$, $D_s^*D_s^*$ channels. The interaction for channel coupling is constructed from the current-current Lagrangian related to the color confinement and the one-gluon exchange potentials. By adopting the massive gluon propagator from the lattice calculation in the nonperturbative region, the coupling interaction is further simplified to the four-fermion interaction. The numerical calculation still prefers the assignment $1^{++}$ of X(3872).

hep-ph↗
arXiv2010

AC electrokinetic phenomena over semiconductive surfaces: effective electric boundary conditions and their applications

Electrokinetic boundary conditions are derived for AC electrokinetic (ACEK) phenomena over leaky dielectric (i.e., semiconducting) surfaces. Such boundary conditions correlate the electric potentials across the semiconductor-electrolyte interface (consisting of the electric double layer (EDL) inside the electrolyte solutions and the space charge layer (SCL) inside the semiconductors) under AC electric fields with arbitrary wave forms. The present electrokinetic boundary conditions allow for evaluation of induced zeta potential contributed by both bond charges (due to electric polarization) and free charges (due to electric conduction) from the leaky dielectric materials. Subsequently, we demonstrate the applications of these boundary conditions in analyzing the ACEK phenomena around a semiconducting cylinder. It is concluded that the flow circulations exist around the semiconducting cylinder and are shown to be stronger under an AC field with lower frequency and around a cylinder with higher conductivity.

physics.flu-dyn↗