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Large language models (LLMs) have demonstrated impressive results on natural language tasks, and security researchers are beginning to employ them in both offensive and defensive systems. In cyber-security, there have been multiple research efforts that utilize LLMs focusing on the pre-breach stage of attacks like phishing and malware generation. However, so far there lacks a comprehensive study regarding whether LLM-based systems can be leveraged to simulate the post-breach stage of attacks that are typically human-operated, or "hands-on-keyboard" attacks, under various attack techniques and environments. As LLMs inevitably advance, they may be able to automate both the pre- and post-breach attack stages. This shift may transform organizational attacks from rare, expert-led events to frequent, automated operations requiring no expertise and executed at automation speed and scale. This risks fundamentally changing global computer security and correspondingly causing substantial economic impacts, and a goal of this work is to better understand these risks now so we can better prepare for these inevitable ever-more-capable LLMs on the horizon. On the immediate impact side, this research serves three purposes. First, an automated LLM-based, post-breach exploitation framework can help analysts quickly test and continually improve their organization's network security posture against previously unseen attacks. Second, an LLM-based penetration test system can extend the effectiveness of red teams with a limited number of human analysts. Finally, this research can help defensive systems and teams learn to detect novel attack behaviors preemptively before their use in the wild....

We have investigated both inter-band and intra-band second order nonlinear optical conductivity based on the velocity correlation formalism and the spectral expansion technique. We propose a scenario in which the second order intra-band process is nonzero while the inter-band process is zero. This occurs for a band structure with momentum asymmetry in the Brillouin zone. Very low-energy photons are blocked by the Pauli exclusion principle from participating in the inter-band process; however, they are permitted to participate in the intra-band process, with the band smeared by some impurity scattering. We establish a connection between the inter-band nonlinear optical conductivity in the velocity gauge and the shift vector in the length gauge for a two-band model. Using a quasiclassical kinetic approach, we demonstrate the importance of intra-band transitions in high harmonic generations for the single tilted Dirac cone model and hexagonal warping model. We confirm that the Kramers-Kronig relations break down for the limit case of ($\omega$, $-\omega$) in the nonlinear optical conductivity. Finally, we calculate the superconducting transition temperature of NbN and the dielectric function of AlN, and the resistance of the NbN/AlN junction. The natural non-linearity of the Josephson junction brings a Josephson plasma with frequency in the Terahertz region., Comment: 11 pages, 10 figures

The geometric response of quantum Hall liquids is an important aspect to understand their topological characteristics in addition to the electromagnetic response. According to the Wen-Zee theory, the topological spin is coupled to the curvature of the space in which the electrons reside. The presence of conical geometry provides a local isolated geometric singularity, making it suitable for exploring the geometric response. In the context of two-dimensional electrons in a perpendicular magnetic field, each Landau orbit occupies the same area. The cone geometry naturally provides a structure in which the distances between two adjacent orbits gradually change and can be easily adjusted by altering the tip angle. The presence of a cone tip introduces a geometric singularity that affects the electron density and interacts with the motion of electrons, which has been extensively studied. Furthermore, this type of geometry can automatically create a smooth interface or crossover between the crystalline charge-density-wave state and the liquid-like fractional quantum Hall state. In this work, the properties of this interface are studied from multiple perspectives, shedding light on the behavior of quantum Hall liquids in such geometric configurations.

Training a machine learning model with data following a meaningful order, i.e., from easy to hard, has been proven to be effective in accelerating the training process and achieving better model performance. The key enabling technique is curriculum learning (CL), which has seen great success and has been deployed in areas like image and text classification. Yet, how CL affects the privacy of machine learning is unclear. Given that CL changes the way a model memorizes the training data, its influence on data privacy needs to be thoroughly evaluated. To fill this knowledge gap, we perform the first study and leverage membership inference attack (MIA) and attribute inference attack (AIA) as two vectors to quantify the privacy leakage caused by CL. Our evaluation of nine real-world datasets with attack methods (NN-based, metric-based, label-only MIA, and NN-based AIA) revealed new insights about CL. First, MIA becomes slightly more effective when CL is applied, but the impact is much more prominent to a subset of training samples ranked as difficult. Second, a model trained under CL is less vulnerable under AIA, compared to MIA. Third, the existing defense techniques like DP-SGD, MemGuard, and MixupMMD are still effective under CL, though DP-SGD has a significant impact on target model accuracy. Finally, based on our insights into CL, we propose a new MIA, termed Diff-Cali, which exploits the difficulty scores for result calibration and is demonstrated to be effective against all CL methods and the normal training method. With this study, we hope to draw the community's attention to the unintended privacy risks of emerging machine-learning techniques and develop new attack benchmarks and defense solutions.

Domain Name System (DNS) is a critical component of the Internet. DNS resolvers, which act as the cache between DNS clients and DNS nameservers, are the central piece of the DNS infrastructure, essential to the scalability of DNS. However, finding the resolver vulnerabilities is non-trivial, and this problem is not well addressed by the existing tools. To list a few reasons, first, most of the known resolver vulnerabilities are non-crash bugs that cannot be directly detected by the existing oracles (or sanitizers). Second, there lacks rigorous specifications to be used as references to classify a test case as a resolver bug. Third, DNS resolvers are stateful, and stateful fuzzing is still challenging due to the large input space. In this paper, we present a new fuzzing system termed ResolverFuzz to address the aforementioned challenges related to DNS resolvers, with a suite of new techniques being developed. First, ResolverFuzz performs constrained stateful fuzzing by focusing on the short query-response sequence, which has been demonstrated as the most effective way to find resolver bugs, based on our study of the published DNS CVEs. Second, to generate test cases that are more likely to trigger resolver bugs, we combine probabilistic context-free grammar (PCFG) based input generation with byte-level mutation for both queries and responses. Third, we leverage differential testing and clustering to identify non-crash bugs like cache poisoning bugs. We evaluated ResolverFuzz against 6 mainstream DNS software under 4 resolver modes. Overall, we identify 23 vulnerabilities that can result in cache poisoning, resource consumption, and crash attacks. After responsible disclosure, 19 of them have been confirmed or fixed, and 15 CVE numbers have been assigned., Comment: Extended version. Accepted by USENIX Security 2024

Although the prevention of AI vulnerabilities is critical to preserve the safety and privacy of users and businesses, educational tools for robust AI are still underdeveloped worldwide. We present the design, implementation, and assessment of Maestro. Maestro is an effective open-source game-based platform that contributes to the advancement of robust AI education. Maestro provides goal-based scenarios where college students are exposed to challenging life-inspired assignments in a competitive programming environment. We assessed Maestro's influence on students' engagement, motivation, and learning success in robust AI. This work also provides insights into the design features of online learning tools that promote active learning opportunities in the robust AI domain. We analyzed the reflection responses (measured with Likert scales) of 147 undergraduate students using Maestro in two quarterly college courses in AI. According to the results, students who felt the acquisition of new skills in robust AI tended to appreciate highly Maestro and scored highly on material consolidation, curiosity, and mastery in robust AI. Moreover, the leaderboard, our key gamification element in Maestro, has effectively contributed to students' engagement and learning. Results also indicate that Maestro can be effectively adapted to any course length and depth without losing its educational quality., Comment: 9 pages, 6 figures, published at the Thirteenth Symposium on Educational Advances in Artificial Intelligence (EAAI-23) in the Association for the Advancement of Artificial Intelligence Conference (AAAI), 2023

We develop a numerical method for the time evolution of Gaussian wave packets on flat-band lattices in the presence of correlated disorder. To achieve this, we introduce a method to generate random on-site energies with prescribed correlations. We verify this method with a one-dimensional (1D) cross-stitch model, and find good agreement with analytical results obtained from the disorder-dressed evolution equations. This allows us to reproduce previous findings, that disorder can mobilize 1D flat-band states which would otherwise remain localized. As explained by the corresponding disorder-dressed evolution equations, such mobilization requires an asymmetric disorder-induced coupling to dispersive bands, a condition that is generically not fulfilled when the flat-band is resonant with the dispersive bands at a Dirac point-like crossing. We exemplify this with the 1D Lieb lattice. While analytical expressions are not available for the two-dimensional (2D) system due to its complexity, we extend the numerical method to the 2D $\alpha-T_3$ model, and find that the initial flat-band wave packet preserves its localization when $\alpha = 0$, regardless of disorder and intersections. However, when $\alpha\neq 0$, the wave packet shifts in real space. We interpret this as a Berry phase controlled, disorder-induced wave-packet mobilization. In addition, we present density functional theory calculations of candidate materials, specifically $\rm Hg_{1-x}Cd_xTe$. The flat-band emerges near the $\Gamma$ point ($\bf{k}=$0) in the Brillouin zone., Comment: Accepted on Chin. Phys. B

Graphene aerogel (GA) is a promising material for thermal management applications across many fields due to its lightweight and thermally insulative properties. However, standard values for important thermal properties, such as thermal conductivity, remain elusive due to the lack of reliable characterization techniques for highly porous materials. Comparative infrared thermal microscopy (CITM) is an attractive technique to obtain thermal conductance values of porous materials like GA, due to its non-invasive character, which requires no probing of, or contact with, the often-delicate structures and frameworks. In this study, we improve upon CITM by utilizing a higher resolution imaging setup and reducing the need for pore-filling coating of the sample (previously used to adjust for emissivity). This upgraded setup, verified by characterizing porous silica aerogel, allows for a more accurate confirmation of the fundamental thermal conductivity value of GA while still accounting for the thermal resistance at material boundaries. Using this improved method, we measure a thermal conductivity below 0.036 W/m$\cdot$K for commercial GA using multiple reference materials. These measurements demonstrate the impact of higher resolution thermal imaging to improve accuracy in low density, highly porous materials characterization. This study also reports thermal conductivity for much lower density (less than 15 mg/cm$^3$) GA than previously published studies while maintaining the robustness of the CITM technique., Comment: v3: Submitted to Journal of Porous Materials v2: Resubmitted to correct MathJax typos in abstract

In secure summation, $K$ users, each holds an input, wish to compute the sum of the inputs at a server without revealing any information about {\em all the inputs} even if the server may collude with {\em an arbitrary subset of users}. In this work, we relax the security and colluding constraints, where the set of inputs whose information is prohibited from leakage is from a predetermined collection of sets (e.g., any set of up to $S$ inputs) and the set of colluding users is from another predetermined collection of sets (e.g., any set of up to $T$ users). For arbitrary collection of security input sets and colluding user sets, we characterize the optimal randomness assumption, i.e., the minimum number of key bits that need to be held by the users, per input bit, for weakly secure summation to be feasible, which generally involves solving a linear program., Comment: 22 pages, 1 figure

Achieving strong repulsive Casimir forces through engineered coatings can pave the way for micro- and nano-electromechanical applications where adhesive forces currently cause reliability issues. Here, we exploit Lifshitz theory to identify the requirements for repulsive Casimir forces in gyrotropic media for two limiting cases (ultra-strong gyroelectric and non-gyroelectric). We show that the origin of repulsive force in media with strong gyrotropy such as Weyl semi-metals arises from the giant interconversion of polarization of vacuum fluctuations., Comment: 9 pages, 4 figures

We investigate the nonlocal optical conductivity of Fermi surface nesting materials which support charge density waves or spin density waves. The nonlocal optical conductivity contains information of correlations in electron fluids which could not be accessed by standard optical probes. Half metal emerges from doping a charge density wave and similarly spin-valley half metal emerges from doping a spin density wave. Based on the parabolic band approximation, we find the Drude peak is shifted to higher frequency and splits into two peaks in the nonlocal optical conductivity. We attribute this to the two Fermi velocities in the half-metal or spin-valley half metal states., Comment: 16 pages, 12 figures, to appear on Science China Physics, Mechanics & Astronomy

A storage code over a graph maps $K$ independent source symbols, each of $L_w$ bits, to $N$ coded symbols, each of $L_v$ bits, such that each coded symbol is stored in a node of the graph and each edge of the graph is associated with one source symbol. From a pair of nodes connected by an edge, the source symbol that is associated with the edge can be decoded. The ratio $L_w/L_v$ is called the symbol rate of a storage code and the highest symbol rate is called the capacity. We show that the three highest capacity values of storage codes over graphs are $2, 3/2, 4/3$. We characterize all graphs over which the storage code capacity is $2$ and $3/2$, and for capacity value of $4/3$, necessary condition and sufficient condition (that do not match) on the graphs are given., Comment: 28 pages, 11 figures

We investigate high-order harmonic generations (HHGs) under the comparison of Weyl cones in two types. Due to the hyperboloidal electron pocket structure, strong noncentrosymmetrical generations in high orders are observed around a single type-II Weyl point, especially at frequency zero. Such remarkable DC signal is proved to have attributions from the intraband transition after spectral decomposition. Under weak pulse electric field , the linear optical response of a non-tilted Weyl cone is consistent with the Kubo theory. With more numerical simulations, we conclude the non-zero chemical potential can enhance the even-order generations, from the slightly tilted system to the over-tilted systems. In consideration of dynamical symmetries, type-I and -II Weyl cones also show different selective responses under the circularly polarized light. Finally, using a more realistic model containing two pairs of Weyl points, we demonstrate the paired Weyl points with opposite chirality could suppress the overall even-order generations.

A secure storage code maps $K$ source symbols, each of $L_w$ bits, to $N$ coded symbols, each of $L_v$ bits, such that each coded symbol is stored in a node of a graph. Each edge of the graph is either associated with $D$ of the $K$ source symbols such that from the pair of nodes connected by the edge, we can decode the $D$ source symbols and learn no information about the remaining $K-D$ source symbols; or the edge is associated with no source symbols such that from the pair of nodes connected by the edge, nothing about the $K$ source symbols is revealed. The ratio $L_w/L_v$ is called the symbol rate of a secure storage code and the highest possible symbol rate is called the capacity. We characterize all graphs over which the capacity of a secure storage code is equal to $1$, when $D = 1$. This result is generalized to $D> 1$, i.e., we characterize all graphs over which the capacity of a secure storage code is equal to $1/D$ under a mild condition that for any node, the source symbols associated with each of its connected edges do not include a common element. Further, we characterize all graphs over which the capacity of a secure storage code is equal to $2/D$., Comment: 20 pages, 6 figures

Recent research efforts on 3D point cloud semantic segmentation (PCSS) have achieved outstanding performance by adopting neural networks. However, the robustness of these complex models have not been systematically analyzed. Given that PCSS has been applied in many safety-critical applications like autonomous driving, it is important to fill this knowledge gap, especially, how these models are affected under adversarial samples. As such, we present a comparative study of PCSS robustness. First, we formally define the attacker's objective under performance degradation and object hiding. Then, we develop new attack by whether to bound the norm. We evaluate different attack options on two datasets and three PCSS models. We found all the models are vulnerable and attacking point color is more effective. With this study, we call the attention of the research community to develop new approaches to harden PCSS models.

Conditional disclosure of secrets (CDS) is the problem of disclosing as efficiently as possible, one secret from Alice and Bob to Carol if and only if the inputs at Alice and Bob satisfy some function $f$. The information theoretic capacity of CDS is the maximum number of bits of the secret that can be securely disclosed per bit of total communication. All CDS instances, where the capacity is the highest and is equal to $1/2$, are recently characterized through a noise and signal alignment approach and are described using a graph representation of the function $f$. In this work, we go beyond the best case scenarios and further develop the alignment approach to characterize the linear capacity of a class of CDS instances to be $(\rho-1)/(2\rho)$, where $\rho$ is a covering parameter of the graph representation of $f$., Comment: 19 pages, 8 figures

Cache side-channel attacks lead to severe security threats to the settings that a CPU is shared across users, e.g., in the cloud. The existing attacks rely on sensing the micro-architectural state changes made by victims, and this assumption can be invalidated by combining spatial (\eg, Intel CAT) and temporal isolation (\eg, time protection). In this work, we advance the state of cache side-channel attacks by showing stateless cache side-channel attacks that cannot be defeated by both spatial and temporal isolation. This side-channel exploits the timing difference resulted from interconnect congestion. Specifically, to complete cache transactions, for Intel CPUs, cache lines would travel across cores via the CPU mesh interconnect. Nonetheless, the mesh links are shared by all cores, and cache isolation does not segregate the traffic. An attacker can generate interconnect traffic to contend with the victim's on a mesh link, hoping that extra delay will be measured. With the variant delays, the attacker can deduce the memory access pattern of a victim program, and infer its sensitive data. Based on this idea, we implement Volcano and test it against the existing RSA implementations of JDK. We found the RSA private key used by a victim process can be partially recovered. In the end, we propose a few directions for defense and call for the attention of the security community.

In this paper, we study the problem of publishing a stream of real-valued data satisfying differential privacy (DP). One major challenge is that the maximal possible value can be quite large; thus it is necessary to estimate a threshold so that numbers above it are truncated to reduce the amount of noise that is required to all the data. The estimation must be done based on the data in a private fashion. We develop such a method that uses the Exponential Mechanism with a quality function that approximates well the utility goal while maintaining a low sensitivity. Given the threshold, we then propose a novel online hierarchical method and several post-processing techniques. Building on these ideas, we formalize the steps into a framework for private publishing of stream data. Our framework consists of three components: a threshold optimizer that privately estimates the threshold, a perturber that adds calibrated noises to the stream, and a smoother that improves the result using post-processing. Within our framework, we design an algorithm satisfying the more stringent setting of DP called local DP (LDP). To our knowledge, this is the first LDP algorithm for publishing streaming data. Using four real-world datasets, we demonstrate that our mechanism outperforms the state-of-the-art by a factor of 6-10 orders of magnitude in terms of utility (measured by the mean squared error of answering a random range query).

In the conditional disclosure of secrets (CDS) problem, Alice and Bob (each holds an input and a common secret) wish to disclose, as efficiently as possible, the secret to Carol if and only if their inputs satisfy some function. The capacity of CDS is the maximum number of bits of the secret that can be securely disclosed per bit of total communication. We characterize the necessary and sufficient condition for the extreme case where the capacity of CDS is the highest and is equal to 1/2. For the simplest instance where the capacity is smaller than 1/2, we show that the linear capacity is 2/5.

Monetizing websites and web apps through online advertising is widespread in the web ecosystem. The online advertising ecosystem nowadays forces publishers to integrate ads from these third-party domains. On the one hand, this raises several privacy and security concerns that are actively studied in recent years. On the other hand, given the ability of today's browsers to load dynamic web pages with complex animations and Javascript, online advertising has also transformed and can have a significant impact on webpage performance. The performance cost of online ads is critical since it eventually impacts user satisfaction as well as their Internet bill and device energy consumption. In this paper, we apply an in-depth and first-of-a-kind performance evaluation of web ads. Unlike prior efforts that rely primarily on adblockers, we perform a fine-grained analysis on the web browser's page loading process to demystify the performance cost of web ads. We aim to characterize the cost by every component of an ad, so the publisher, ad syndicate, and advertiser can improve the ad's performance with detailed guidance. For this purpose, we develop an infrastructure, adPerf, for the Chrome browser that classifies page loading workloads into ad-related and main-content at the granularity of browser activities (such as Javascript and Layout). Our evaluations show that online advertising entails more than 15% of browser page loading workload and approximately 88% of that is spent on JavaScript. We also track the sources and delivery chain of web ads and analyze performance considering the origin of the ad contents. We observe that 2 of the well-known third-party ad domains contribute to 35% of the ads performance cost and surprisingly, top news websites implicitly include unknown third-party ads which in some cases build up to more than 37% of the ads performance cost., Comment: 13 pages, 16 figures

A chiral absorber of light can emit spin-polarized (circularly polarized) thermal radiation based on Kirchhoff's law which equates spin-resolved emissivity with spin-resolved absorptivity for reciprocal media at thermal equilibrium. No such law is known for nonreciprocal media. In this work, we discover three spin-resolved Kirchhoff's laws of thermal radiation applicable for both reciprocal and nonreciprocal planar media. In particular, these laws are applicable to multi-layered or composite slabs of generic bianisotropic material classes which include (uniaxial or biaxial) birefringent crystals, (gyrotropic) Weyl semimetals, magnetized semiconductors, plasmas, ferromagnets and ferrites, (magnetoelectric) topological insulators, metamaterials and multiferroic media. We also propose an experiment to verify these laws using a single system of doped Indium Antimonide (InSb) thin film in an external magnetic field. Furthermore, we reveal a surprising result that the planar slabs of all these material classes can emit partially circularly polarized thermal light without requiring any surface patterning, and identify planar configurations which can experience nontrivial thermal optomechanical forces and torques upon thermal emission into the external environment at lower temperature (nonequilibrium). Our work also provides a new fundamental insight of detailed balance of angular momentum (in addition to energy) of equilibrium thermal radiation, and paves the way for practical functionalities based on thermal radiation using nonreciprocal bianisotropic materials.

The IoT (Internet of Things) technology has been widely adopted in recent years and has profoundly changed the people's daily lives. However, in the meantime, such a fast-growing technology has also introduced new privacy issues, which need to be better understood and measured. In this work, we look into how private information can be leaked from network traffic generated in the smart home network. Although researchers have proposed techniques to infer IoT device types or user behaviors under clean experiment setup, the effectiveness of such approaches become questionable in the complex but realistic network environment, where common techniques like Network Address and Port Translation (NAPT) and Virtual Private Network (VPN) are enabled. Traffic analysis using traditional methods (e.g., through classical machine-learning models) is much less effective under those settings, as the features picked manually are not distinctive any more. In this work, we propose a traffic analysis framework based on sequence-learning techniques like LSTM and leveraged the temporal relations between packets for the attack of device identification. We evaluated it under different environment settings (e.g., pure-IoT and noisy environment with multiple non-IoT devices). The results showed our framework was able to differentiate device types with a high accuracy. This result suggests IoT network communications pose prominent challenges to users' privacy, even when they are protected by encryption and morphed by the network gateway. As such, new privacy protection methods on IoT traffic need to be developed towards mitigating this new issue.

Nonlinear phenomena are inherent in most systems in nature. Second or higher-order harmonic generations, three-wave and four-wave mixing are typical phenomena in nonlinear optics. To obtain a nonzero signal for second-harmonic generation in the long-wavelength limit ($q\rightarrow0$), the breaking of inversion symmetry is required. In topological materials, a hexagonal warping term which breaks the rotation symmetry of the Fermi surface is observed by angular-resolved photo-emission spectroscopy (ARPES). If a gap opens (e.g., by doping with magnetic impurities) the inversion symmetry will be broken. Here we use a nonlinear response theory based on a generalized Kubo formula to explain the frequency up-conversion in topological materials., Comment: 9 pages, 5 figures

Flatbands feature the distortion-free storage of compact localized states of tailorable shape. Their reliable storage sojourn is, however, limited by disorder potentials, which generically cause uncontrolled coupling into dispersive bands. We find that, while detuning flatband states from band intersections suppresses their direct decay into dispersive bands, disorder-induced state distortion causes a delayed, dephasing-mediated decay, lifting the static nature of flatband states and setting a finite lifetime for the reliable storage sojourn. We exemplify this generic, disorder-induced decay mechanism at the cross-stitch lattice. Our analysis, which applies platform-independently, relies on the time-resolved treatment of disorder-averaged quantum systems with quantum master equations., Comment: 7 pages

In this paper, we seek to better understand Android obfuscation and depict a holistic view of the usage of obfuscation through a large-scale investigation in the wild. In particular, we focus on four popular obfuscation approaches: identifier renaming, string encryption, Java reflection, and packing. To obtain the meaningful statistical results, we designed efficient and lightweight detection models for each obfuscation technique and applied them to our massive APK datasets (collected from Google Play, multiple third-party markets, and malware databases). We have learned several interesting facts from the result. For example, malware authors use string encryption more frequently, and more apps on third-party markets than Google Play are packed. We are also interested in the explanation of each finding. Therefore we carry out in-depth code analysis on some Android apps after sampling. We believe our study will help developers select the most suitable obfuscation approach, and in the meantime help researchers improve code analysis systems in the right direction.

In this paper, we present that security threats coming with existing GPU memory management strategy are overlooked, which opens a back door for adversaries to freely break the memory isolation: they enable adversaries without any privilege in a computer to recover the raw memory data left by previous processes directly. More importantly, such attacks can work on not only normal multi-user operating systems, but also cloud computing platforms. To demonstrate the seriousness of such attacks, we recovered original data directly from GPU memory residues left by exited commodity applications, including Google Chrome, Adobe Reader, GIMP, Matlab. The results show that, because of the vulnerable memory management strategy, commodity applications in our experiments are all affected.

The fluorescence quantum yield of bis-MSB, a widely used liquid scintillator wavelength shifter, was measured to study the photon absorption and re-emission processes in liquid scintillator. The re-emission process affects the photoelectron yield and distribution, especially in a large liquid scintillator detector, thus must be understood to optimize the liquid scintillator for good energy resolution and to precisely simulate the detector with Monte Carlo. In this study, solutions of different bis-MSB concentration were prepared for absorption and fluorescence emission measurements to cover a broad range of wavelengths. Harmane was used as a standard reference to obtain the absolution fluorescence quantum yield. For the first time we measured the fluorescence quantum yield of bis-MSB up to 430 nm as inputs required by Monte Carlo simulation, which is 0.926$\pm$0.053 at $\lambda_{\rm ex}$ = 350 nm., Comment: 7 pages, 6 figures

The Fermi velocity ($v_{F}$) associated with the spin-orbit coupling is two orders of magnitude smaller for spintronic semiconductors than it is for topological insulators. Both families can be treated with the same Hamiltonian which contains a relativistic (Dirac) linear in momentum term proportional to $v_{F}$ and a non-relativistic quadratic contribution with Schr\"{o}dinger mass (m). We find that the AC dynamic longitudinal and transverse (Hall) magneto-conductivities are strongly dependent on the size of $v_{F}$. When the Dirac fermi velocity is small, the absorption background provided by the interband optical transitions is finite only over a very limited range of photon energies as compared with topological insulators. Its onset depends on the value of the chemical potential ($\mu$) and on the magnetic field (B), as does its upper cut off. Within this limited range its magnitude is however constant and has the same magnitude of $e^{2}\pi/(8h)$ as is found in topological insulators and also in graphene noting a difference in degeneracy factor. The total optical spectral weight under the universal interband background is $e^{2}\pi/(8h)4mv_{F}^{2}$. In contrast to the known result for graphene no strict conservation law applies to the spectral weight transfers between inter and intra band transition brought about by variations in the magnitude of the chemical potential when a non-relativistic contribution is present in the Hamiltonian whatever size it may have., Comment: 13 pages, 7 figures, accepted to PRB

The metallic surface states of a topological insulator support helical Dirac fermions protected by topology with their spin locked perpendicular to their momentum. They can acquire mass through magnetic doping or through hybridization of states on opposite faces of a thin sample. In this case there can be a component of electron spin oriented perpendicular to the surface plane. The electron-phonon interaction renormalizes the dynamics of the charge carriers through their spectral density. It also modifies the gap channel and a second spectral function enters which, not only determines the out of plane spin component, but also comes into in-plane properties. While the out of plane spin component is decreased below the Fermi momentum ($k_F$), the in plane component increases. There are also correlation tails extending well beyond $k_F$. The angular resolved photo-emission line shapes aquire Holstein side bands. The effective gap in the density of states is reduced and the optical conductivity aquires distinct measurable phonon structure even for modest value of the electron-phonon coupling., Comment: 9pages, 9 figures

Recent years have seen the rise of more sophisticated attacks including advanced persistent threats (APTs) which pose severe risks to organizations and governments by targeting confidential proprietary information. Additionally, new malware strains are appearing at a higher rate than ever before. Since many of these malware are designed to evade existing security products, traditional defenses deployed by most enterprises today, e.g., anti-virus, firewalls, intrusion detection systems, often fail at detecting infections at an early stage. We address the problem of detecting early-stage infection in an enterprise setting by proposing a new framework based on belief propagation inspired from graph theory. Belief propagation can be used either with "seeds" of compromised hosts or malicious domains (provided by the enterprise security operation center -- SOC) or without any seeds. In the latter case we develop a detector of C&C communication particularly tailored to enterprises which can detect a stealthy compromise of only a single host communicating with the C&C server. We demonstrate that our techniques perform well on detecting enterprise infections. We achieve high accuracy with low false detection and false negative rates on two months of anonymized DNS logs released by Los Alamos National Lab (LANL), which include APT infection attacks simulated by LANL domain experts. We also apply our algorithms to 38TB of real-world web proxy logs collected at the border of a large enterprise. Through careful manual investigation in collaboration with the enterprise SOC, we show that our techniques identified hundreds of malicious domains overlooked by state-of-the-art security products.

With millions of apps that can be downloaded from official or third-party market, Android has become one of the most popular mobile platforms today. These apps help people in all kinds of ways and thus have access to lots of user's data that in general fall into three categories: sensitive data, data to be shared with other apps, and non-sensitive data not to be shared with others. For the first and second type of data, Android has provided very good storage models: an app's private sensitive data are saved to its private folder that can only be access by the app itself, and the data to be shared are saved to public storage (either the external SD card or the emulated SD card area on internal FLASH memory). But for the last type, i.e., an app's non-sensitive and non-shared data, there is a big problem in Android's current storage model which essentially encourages an app to save its non-sensitive data to shared public storage that can be accessed by other apps. At first glance, it seems no problem to do so, as those data are non-sensitive after all, but it implicitly assumes that app developers could correctly identify all sensitive data and prevent all possible information leakage from private-but-non-sensitive data. In this paper, we will demonstrate that this is an invalid assumption with a thorough survey on information leaks of those apps that had followed Android's recommended storage model for non-sensitive data. Our studies showed that highly sensitive information from billions of users can be easily hacked by exploiting the mentioned problematic storage model. Although our empirical studies are based on a limited set of apps, the identified problems are never isolated or accidental bugs of those apps being investigated. On the contrary, the problem is rooted from the vulnerable storage model recommended by Android. To mitigate the threat, we also propose a defense framework.

The topological protected electronic states on the surface of a topological insulator can progressively change their Fermi cross-section from circular to a snowflake shape as the chemical potential is increased above the Dirac point because of an hexagonal warping term in the Hamiltonian. Another effect of warping is to change the spin texture which exists when a finite gap is included by magnetic doping, although the in-plane spin component remains locked perpendicular to momentum. It also changes the orbital magnetic moment, the matrix element for optical absorption and the circular dichroism. We find that the Fermi surface average of z-component of spin is closely related to the value of the Berry phase. This holds even when the Hamiltonian includes a subdominant non-relativistic quadratic in momentum term (which provides particle-hole asymmetry) in addition to the dominant relativistic Dirac term. There is also a qualitative correlation between $\left\langle S_z \right\rangle$ and the dichroism. For the case when the chemical potential falls inside the gap between valence and conduction band, the Hall conductivity remains quantized and unaffected in value by the hexagonal warping term., Comment: 10 figures, accepted in PRB

We studied the temperature dependence of the light yield of the linear alkyl benzene (LAB)-based and mesitylene-based liquid scintillators. The light yield increases by 23% for both liquid scintillators when the temperature is lowered from $26\;^{\circ}$C to $-40\;^{\circ }$C, correcting for the temperature response of the photomultiplier tube. The measurements help to understand the energy response of the liquid scintillator detectors. Especially, the next generation reactor neutrino experiments for neutrino mass hierarchy, such as the Jiangmen Underground Neutrino Observatory (JUNO), require very high energy resolution. As no apparent degradation on the liquid scintillator transparency was observed, lowering the operation temperature of the detector to $\sim4\;^\circ$C will increase the photoelectron yield of the detector by 13%, combining the light yield increase of the liquid scintillator and the quantum efficiency increase of the photomultiplier tubes.

The helical Dirac states on the surface of a topological insulator are protected by topology and display significant particle-hole asymmetry. This asymmetry arises from a subdominant Schr\"{o}dinger type contribution to the Hamiltonian which provides a small perturbation to a dominant Dirac contribution. This changes the Landau levels energies in an external magnetic field ($B$) and provides modifications to the usual relativistic optical matrix elements. Nevertheless we find that the relativistic quantization of the Hall plateaux remains even when the ratio of the Schr\"{o}dinger ($E_0$) to Dirac ($E_1$) magnetic energy scale increases either through an increase in $B$, a decrease in the Schr\"{o}dinger mass or of the Dirac fermi velocity. First corrections to the optical matrix elements(OME) in the relativistic case drop out at least to order $(E_0/E_1)^3$. In the opposite limit $E_1$ small, the quantization remains classical but there is a split into two series. The first corrections to the OME in this case, cancel out at least to order $(E_1/E_0)^4$., Comment: 10 pages, 7 figures, to appear in Phys. Rev. B

We study the Hall conductivity in single layer gapped Dirac fermion materials including coupling to a phonon field, which not only modifies the quasi-particle dynamics through the usual self-energy term but also renormalizes directly the gap. Consequently the Berry curvature is modified. As the temperature is increased the sign of the renormalized gap can change and the material can cross over from a band insulator to a topological insulator at higher temperature (T). The effective Chern numbers defined for valley and spin Hall conductivity show a rich phase diagram with increasing temperature. While the spin and valley DC Hall conductivity is no longer quantized at elevated temperature a change in sign with increasing T is a clear indication of a topological crossover. The chirality of the circularly polarized light which is dominantly absorbed by a particular valley can change with temperature as a result of a topological crossover., Comment: 6 pages, 5 figures, to appear in Phys. Rev. B

Spin-orbit coupling plays an important role in various properties of very different materials. Moreover efforts are underway to control the degree and quality of spin-orbit coupling in materials with a concomitant control of transport properties. We calculate the frequency dependent optical conductivity in systems with both Rashba and Dresselhaus spin-orbit coupling. We find that when the linear Dresselhaus spin-orbit coupling is tuned to be equal to the Rashba spin-orbit coupling, the interband optical conductivity disappears. This is taken to be the signature of the recovery of SU(2) symmetry. The presence of the cubic Dresselhaus spin-orbit coupling modifies the dispersion relation of the charge carriers and the velocity operator. Thus the conductivity is modified, but the interband contribution remains suppressed at most but not all photon energies for a cubic coupling of reasonable magnitude. Hence, such a measurement can serve as a diagnostic probe of engineered spin-orbit coupling.

Dirac fermions exist in many solid state systems including graphene, silicene and other two dimensional membranes such as are found in group VI dichalcogenides, as well as on the surface of some insulators where such states are protected by topology. Coupling of those fermions to phonons introduces new structures in their dispersion curves and, in the case of massive Dirac fermions, can shift and modify the gap. We show how these changes present in angular-resolved photoemission spectroscopy of the dressed charge carrier dispersion curves and scanning tunneling microscopy measurements of their density of states. In particular we focus on the region around the band gap. In this region the charge carrier spectral density no longer consists of a dominant quasiparticle peak and a smaller incoherent phonon related background. The quasiparticle picture has broken down and this leads to important modification in both dispersion curves and density of states., Comment: 12 pages, 6 figures, to appear in PRB

Adding a small subdominant quadratic in momentum term to a dominant linear Dirac dispersion curve affects conduction and valence band differently and leads to an hourglass-like structure for energy as a function of momentum. This applies to the protected surface states in topological insulators. The energies of the conduction and valence band Landau levels are also different and this leads to the splitting of optical absorption lines produced by the magnetic field, which acquire a two peak structure. It also changes the peaks in the imaginary part of the Hall conductivity into two distinct contributions of opposite signs. The real part of the circularly polarized optical conductivity however retains its single peak structure but the peaks in right and left handedness case are shifted in energy with respect to each other in contrast to the pure Dirac case. The magnitude of the semiclassical cyclotron frequency is significantly modified by the presence of a mass term as is its variation with value of the chemical potential $\mu$. Its optical spectral weight is found to decrease with increasing $\mu$ rather than increase as it does in the pure Dirac limit., Comment: 11 pages, 8 figures, to appear in PRB

ARPES studies of the protected surface states in the Topological Insulator $% Bi_{2}Te_{3}$ have revealed the existence of an important hexagonal warping term in its electronic band structure. This term distorts the shape of the Dirac cone from a circle at low energies to a snowflake shape at higher energies. We show that this implies important modifications of the interband optical transitions which no longer provide a constant universal background as seen in graphene. Rather the conductivity shows a quasilinear increase with a slightly concave upward bending as energy is increased. Its slope increases with increasing magnitude of the hexagonal distortion as does the magnitude of the jump at the interband onset. The energy dependence of the density of states is also modified and deviates downward from linear with increasing energy., Comment: 6 pages, 4 figures, accepted to Phys. Rev. B

A monolayer of $MoS_{2}$ has a non-centrosymmetric crystal structure, with spin polarized bands. It is a two valley semiconductor with direct gap falling in the visible range of the electromagnetic spectrum. Its optical properties are of particular interest in relation to valleytronics and possible device applications. We study the longitudinal and the transverse Hall dynamical conductivity which is decomposed into charge, spin and valley contributions. Circular polarized light associated with each of the two valleys separately is considered and results are filtered according to spin polarization. Temperature can greatly change the spin admixture seen in the frequency window where they are not closely in balance., Comment: 8 pages, 5 figures, accepted by Phys. Rev. B

When an electron interacts with phonons, the electron can exhibit either free electron-like or polaron-like properties. The latter tends to occur for very strong coupling, and results in a phonon cloud accompanying the electron as it moves, thus raising its mass considerably. We summarize this behaviour for the Holstein model in one, two and three dimensions, and note that the crossover occurs for fairly low coupling strengths compared to those attributed to real materials exhibiting conventional superconductivity., Comment: 5 pages; contains a summary of single particle results for the Holstein model

We utilize an exact variational numerical procedure to calculate the ground state properties of a polaron in the presence of Rashba and linear Dresselhaus spin-orbit coupling. We find that when the linear Dresselhaus spin-orbit coupling approaches the Rashba spin-orbit coupling, the Van-Hove singularity in the density of states will be shifted away from the bottom of the band and finally disappear when the two spin-orbit couplings are tuned to be equal. The effective mass will be suppressed; the trend will become more significant for low phonon frequency. The presence of two dominant spin-orbit couplings will make it possible to tune the effective mass with more varied observables., Comment: 6 pages, low resolution figures

We utilize an exact variational numerical procedure to calculate the ground state properties of a polaron in the presence of a Rashba-like spin orbit interaction. Our results corroborate with previous work performed with the Momentum Average approximation and with weak coupling perturbation theory. We find that spin orbit coupling increases the effective mass in the regime with weak electron phonon coupling, and decreases the effective mass in the intermediate and strong electron phonon coupling regime. Analytical strong coupling perturbation theory results confirm our numerical results in the small polaron regime. A large amount of spin orbit coupling can lead to a significant lowering of the polaron effective mass., Comment: 10 pages, 7 figures

We use both a perturbative Green's function analysis and standard perturbative quantum mechanics to calculate the decrease in energy and the effective mass for an electron interacting with acoustic phonons. The interaction is between the difference in lattice displacements for neighbouring ions, and the hopping amplitude for an electron between those two sites. The calculations are performed in one, two, and three dimensions, and comparisons are made with results from other electron-phonon models. We also compute the spectral function and quasiparticle residue, as a function of characteristic phonon frequency. There are strong indications that this model is always polaronic on one dimension, where an unusual relation between the effective mass and the quasiparticle residue is also found., Comment: 9 pages, 5 figures, submitted to PRB

We adapt a variational procedure to calculate ground state properties of the Holstein model in the adiabatic limit. At strong coupling, this adaption leads to rapid convergence of results. The intermediate coupling regime is further handled with an adaptive algorithm. We also use semi-classically derived results for the adiabatic end-point, along with weak coupling perturbation theory. These establish weak and strong coupling (or large and small polaron, respectively) regimes in two dimensions or higher. As is well known, these are connected smoothly, but the cross-over becomes increasingly abrupt as the phonon frequency decreases., Comment: 6 pages, 5 figures

We show that the changes in the electronic density of states (DOS) in graphene induced by impurity scattering with short-range potentials are completely different from those caused by the long-range Coulomb potential. The spectral weight of the state that eventually disappears into the valence band (as the strength of scattering increases) does not transform into a resonance state. Therefore no unusual screening effects related to a redistribution of the density of states in the valence band are observed. The states induced by the short-range impurities in graphene, therefore, have distinctively different properties compared with the long-range potential case. These properties, in fact, closely resemble the case of a short-range single impurity in other bipartite lattices, such as the square, body centered cubic, and simple cubic lattices.

We derive out a complete series expression of Hamiltonian eigenvalues without any approximation and cut in the general quantum systems based on Wang's formal framework \cite{wang1}. In particular, we then propose a calculating approach of eigenvalues of arbitrary Hamiltonian via solving an algebra equation satisfied by a kernal function, which involves the contributions from all order perturbations. In order to verify the validity of our expressions and reveal the power of our approach, we calculate the ground state energy of a quartic anharmonic oscillator and have obtained good enough results comparing with the known one., Comment: 18 pages, No figure. This is the fifth manuscript. Previous manuscripts see arXiv:quant-ph/0611216, arXiv:quant-ph/0611217, arXiv:quant-ph/0601051 and arXiv:quant-ph/0612068

A bipartite producer-consumer network is constructed to describe the industrial structure. The edges from consumer to producer represent the choices of the consumer for the final products and the degree of producer can represent its market share. So the size distribution of firms can be characterized by producer's degree distribution. The probability for a producer receiving a new consumption is determined by its competency described by initial attractiveness and the self-reinforcing mechanism in the competition described by preferential attachment. The cases with constant total consumption and with growing market are studied. The following results are obtained: 1, Without market growth and a uniform initial attractiveness $a$, the final distribution of firm sizes is Gamma distribution for $a>1$ and is exponential for $a=1$. If $a<1$, the distribution is power in small size and exponential in upper tail; 2, For a growing market, the size distribution of firms obeys the power law. The exponent is affected by the market growth and the initial attractiveness of the firms., Comment: 13 pages, 3 figures