arXiv subjects

Nan Zhang

Publications and source records attributed to Nan Zhang.

At least 181 records · Page 10Linked to original sources

arXiv2018

A characterization of the consistent Hoare powerdomains over dcpos

It has been shown that for a dcpo P, the Scott closure of Γ_c(P) in Γ(P) is a consistent Hoare powerdomain of P, where Γ_c(P) is the family of nonempty, consistent and Scott closed subsets of P, and Γ(P) is the collection of all nonempty Scott closed subsets of P. In this paper, by introducing the notion of a \vee-existing set, we present a direct characterization of the consistent Hoare powerdomain: the set of all \vee-existing Scott closed subsets of a dcpo P is exactly the consistent Hoare powerdomain of P. We also introduce the concept of an F-Scott closed set over each dcpo-\vee-semilattice. We prove that the Scott closed set lattice of a dcpo P is isomorphic to the family of all F-Scott closed sets of P's consistent Hoare powerdomain.

cs.LO↗

arXiv2018

QR2: A Third-party Query Reranking Service Over Web Databases

The ranked retrieval model has rapidly become the de-facto way for search query processing in web databases. Despite the extensive efforts on designing better ranking mechanisms, in practice, many such databases fail to address the diverse and sometimes contradicting preferences of users. In this paper, we present QR2, a third-party service that uses nothing but the public search interface of a web database and enables the on-the-fly processing of queries with any user-specified ranking functions, no matter if the ranking function is supported by the database or not.

cs.DB↗

arXiv2018

Understanding and Mitigating the Security Risks of Voice-Controlled Third-Party Skills on Amazon Alexa and Google Home

Virtual personal assistants (VPA) (e.g., Amazon Alexa and Google Assistant) today mostly rely on the voice channel to communicate with their users, which however is known to be vulnerable, lacking proper authentication. The rapid growth of VPA skill markets opens a new attack avenue, potentially allowing a remote adversary to publish attack skills to attack a large number of VPA users through popular IoT devices such as Amazon Echo and Google Home. In this paper, we report a study that concludes such remote, large-scale attacks are indeed realistic. More specifically, we implemented two new attacks: voice squatting in which the adversary exploits the way a skill is invoked (e.g., "open capital one"), using a malicious skill with similarly pronounced name (e.g., "capital won") or paraphrased name (e.g., "capital one please") to hijack the voice command meant for a different skill, and voice masquerading in which a malicious skill impersonates the VPA service or a legitimate skill to steal the user's data or eavesdrop on her conversations. These attacks aim at the way VPAs work or the user's mis-conceptions about their functionalities, and are found to pose a realistic threat by our experiments (including user studies and real-world deployments) on Amazon Echo and Google Home. The significance of our findings have already been acknowledged by Amazon and Google, and further evidenced by the risky skills discovered on Alexa and Google markets by the new detection systems we built. We further developed techniques for automatic detection of these attacks, which already capture real-world skills likely to pose such threats.

cs.CR↗

arXiv2018

Intervalley Scattering of Interlayer Excitons in a MoS$_2$/MoSe$_2$/MoS$_2$ Heterostructure in High Magnetic Field

Degenerate extrema in the energy dispersion of charge carriers in solids, also referred to as valleys, can be regarded as a binary quantum degree of freedom, which can potentially be used to implement valleytronic concepts in van der Waals heterostructures based on transition metal dichalcogenides. Using magneto-photoluminescence spectroscopy, we achieve a deeper insight into the valley polarization and depolarization mechanisms of interlayer excitons formed across a MoS$_2$/MoSe$_2$/MoS$_2$ heterostructure. We account for the non-trivial behavior of the valley polarization as a function of the magnetic field by considering the interplay between exchange interaction and phonon mediated intervalley scattering in a system consisting of Zeeman-split energy levels. Our results represent a crucial step towards the understanding of the properties of interlayer excitons, with strong implications for the implementation of atomically thin valleytronic devices.

cond-mat.mes-hall↗

arXiv2018

Understanding the Relationships between Information Architectures and Business Models

Based on the dualism of information architecture and business model by Kuk and Janssen (2011), the study proposed a theoretical framework to understanding the relationship among IoT and smart community which regards a path of smart community development as a configurations set including both information architecture factors and business model patterns.

cs.CY↗

arXiv2018

RRR: Rank-Regret Representative

Selecting the best items in a dataset is a common task in data exploration. However, the concept of "best" lies in the eyes of the beholder: different users may consider different attributes more important, and hence arrive at different rankings. Nevertheless, one can remove "dominated" items and create a "representative" subset of the data set, comprising the "best items" in it. A Pareto-optimal representative is guaranteed to contain the best item of each possible ranking, but it can be almost as big as the full data. Representative can be found if we relax the requirement to include the best item for every possible user, and instead just limit the users' "regret". Existing work defines regret as the loss in score by limiting consideration to the representative instead of the full data set, for any chosen ranking function. However, the score is often not a meaningful number and users may not understand its absolute value. Sometimes small ranges in score can include large fractions of the data set. In contrast, users do understand the notion of rank ordering. Therefore, alternatively, we consider the position of the items in the ranked list for defining the regret and propose the {\em rank-regret representative} as the minimal subset of the data containing at least one of the top-$k$ of any possible ranking function. This problem is NP-complete. We use the geometric interpretation of items to bound their ranks on ranges of functions and to utilize combinatorial geometry notions for developing effective and efficient approximation algorithms for the problem. Experiments on real datasets demonstrate that we can efficiently find small subsets with small rank-regrets.

cs.DB↗

arXiv2017

Network Slicing for Service-Oriented Networks Under Resource Constraints

To support multiple on-demand services over fixed communication networks, network operators must allow flexible customization and fast provision of their network resources. One effective approach to this end is network virtualization, whereby each service is mapped to a virtual subnetwork providing dedicated on-demand support to network users. In practice, each service consists of a prespecified sequence of functions, called a service function chain (SFC), while each service function in a SFC can only be provided by some given network nodes. Thus, to support a given service, we must select network function nodes according to the SFC and determine the routing strategy through the function nodes in a specified order. A crucial network slicing problem that needs to be addressed is how to optimally localize the service functions in a physical network as specified by the SFCs, subject to link and node capacity constraints. In this paper, we formulate the network slicing problem as a mixed binary linear program and establish its strong NP-hardness. Furthermore, we propose efficient penalty successive upper bound minimization (PSUM) and PSUM-R(ounding) algorithms, and two heuristic algorithms to solve the problem. Simulation results are shown to demonstrate the effectiveness of the proposed algorithms.

cs.NI↗

arXiv2017

Understanding IoT Security Through the Data Crystal Ball: Where We Are Now and Where We Are Going to Be

Inspired by the boom of the consumer IoT market, many device manufacturers, start-up companies and technology giants have jumped into the space. Unfortunately, the exciting utility and rapid marketization of IoT, come at the expense of privacy and security. Industry reports and academic work have revealed many attacks on IoT systems, resulting in privacy leakage, property loss and large-scale availability problems. To mitigate such threats, a few solutions have been proposed. However, it is still less clear what are the impacts they can have on the IoT ecosystem. In this work, we aim to perform a comprehensive study on reported attacks and defenses in the realm of IoT aiming to find out what we know, where the current studies fall short and how to move forward. To this end, we first build a toolkit that searches through massive amount of online data using semantic analysis to identify over 3000 IoT-related articles. Further, by clustering such collected data using machine learning technologies, we are able to compare academic views with the findings from industry and other sources, in an attempt to understand the gaps between them, the trend of the IoT security risks and new problems that need further attention. We systemize this process, by proposing a taxonomy for the IoT ecosystem and organizing IoT security into five problem areas. We use this taxonomy as a beacon to assess each IoT work across a number of properties we define. Our assessment reveals that relevant security and privacy problems are far from solved. We discuss how each proposed solution can be applied to a problem area and highlight their strengths, assumptions and constraints. We stress the need for a security framework for IoT vendors and discuss the trend of shifting security liability to external or centralized entities. We also identify open research problems and provide suggestions towards a secure IoT ecosystem.

cs.CR↗

arXiv2017

Energy conditions and constraints on the generalized non-local gravity model

We study and derive the energy conditions in generalized non-local gravity, which is the modified theory of general relativity (GR) obtained by adding a term $m^{2n-2}R\Box^{-n}R$ to the Einstein-Hilbert action. Moreover, in order to get some insight on the meaning of the energy conditions, we illustrate the evolutions of four energy conditions with the model parameter $\varepsilon$ for different $n$. By analysis we give the constraints on the model parameters $\varepsilon$.

gr-qc↗

arXiv2017

Guardian of the HAN: Thwarting Mobile Attacks on Smart-Home Devices Using OS-level Situation Awareness

A new development of smart-home systems is to use mobile apps to control IoT devices across a Home Area Network (HAN). Those systems tend to rely on the Wi-Fi router to authenticate other devices; as verified in our study, IoT vendors tend to trust all devices connected to the HAN. This treatment exposes them to the attack from malicious apps, particularly those running on authorized phones, which the router does not have information to control, as confirmed in our measurement study. Mitigating this threat cannot solely rely on IoT manufacturers, which may need to change the hardware on the devices to support encryption, increasing the cost of the device, or software developers who we need to trust to implement security correctly. In this work, we present a new technique to control the communication between the IoT devices and their apps in a unified, backward-compatible way. Our approach, called Hanguard, does not require any changes to the IoT devices themselves, the IoT apps or the OS of the participating phones. Hanguard achieves a fine-grained, per-app protection through bridging the OS-level situation awareness and the router-level per-flow control: each phone runs a non-system userspace Monitor app to identify the party that attempts to access the protected IoT device and inform the router through a control plane of its access decision; the router enforces the decision on the data plane after verifying whether the phone should be allowed to talk to the device. Hanguard uses a role-based access control (RBAC) schema which leverages type enforcement (TE) and multi-category security (MCS) primitives to define highly flexible access control rules. We implemented our design over both Android and iOS (>95% of mobile OS market share) and a popular router. Our study shows that Hanguard is both efficient and effective in practice.

cs.CR↗

arXiv2017

Citation personal display: A case study of personal websites by physicists in 11 well-known universities

This paper aims to investigate the extent to which researchers display citation, and wants to examine whether there are researcher differences in citation personal display at the level of university, country, and academic rank. Physicists in 11 well-known universities in USA, Britain, and China were chosen as the object of study. It was manually identified if physicists had mentioned citation counts, citation-based indices, or a link to Google Scholar Citations (GSC) on the personal websites. A chi-square test is constructed to test researcher differences in citation personal display. Results showed that the overall proportion of citation personal display is not high (14.8%), with 129 of 870 physicists displaying citation. And physicists from different well-known universities indeed had a significant difference in citation personal display. Moreover, at the national level, it was noticed that physicists in well-known Chinese universities had the highest level of citation personal display, followed by Britain and the USA. Further, this study also found that researchers who had the academic rank of professor had the highest citation personal display. In addition, the differences in h-index personal display by university, country or academic rank were analyzed, and the results showed that they were not statistically significant.

cs.DL↗

arXiv2017

Adaptive Basis Selection for Exponential Family Smoothing Splines with Application in Joint Modeling of Multiple Sequencing Samples

Second-generation sequencing technologies have replaced array-based technologies and become the default method for genomics and epigenomics analysis. Second-generation sequencing technologies sequence tens of millions of DNA/cDNA fragments in parallel. After the resulting sequences (short reads) are mapped to the genome, one gets a sequence of short read counts along the genome. Effective extraction of signals in these short read counts is the key to the success of sequencing technologies. Nonparametric methods, in particular smoothing splines, have been used extensively for modeling and processing single sequencing samples. However, nonparametric joint modeling of multiple second-generation sequencing samples is still lacking due to computational cost. In this article, we develop an adaptive basis selection method for efficient computation of exponential family smoothing splines for modeling multiple second-generation sequencing samples. Our adaptive basis selection gives a sparse approximation of smoothing splines, yielding a lower-dimensional effective model space for a more scalable computation. The asymptotic analysis shows that the effective model space is rich enough to retain essential features of the data. Moreover, exponential family smoothing spline models computed via adaptive basis selection are shown to have good statistical properties, e.g., convergence at the same rate as that of full basis exponential family smoothing splines. The empirical performance is demonstrated through simulation studies and two second-generation sequencing data examples.

stat.ME↗

arXiv2016

Discover Aggregates Exceptions over Hidden Web Databases

Nowadays, many web databases "hidden" behind their restrictive search interfaces (e.g., Amazon, eBay) contain rich and valuable information that is of significant interests to various third parties. Recent studies have demonstrated the possibility of estimating/tracking certain aggregate queries over dynamic hidden web databases. Nonetheless, tracking all possible aggregate query answers to report interesting findings (i.e., exceptions), while still adhering to the stringent query-count limitations enforced by many hidden web databases providers, is very challenging. In this paper, we develop a novel technique for tracking and discovering exceptions (in terms of sudden changes of aggregates) over dynamic hidden web databases. Extensive real-world experiments demonstrate the superiority of our proposed algorithms over baseline solutions.

cs.DB↗

arXiv2016

All passive photonic power divider with arbitrary split ratio

Integrated optical power splitter is one of the fundamental building blocks in photonic integrated circuits (PIC). Conventional multimode interferometer based power splitter is widely used as it has reasonable footprint and is easy to fabricate. However, it is challenging to realize arbitrary split ratio especially for multi-outputs. In this work, an ultra-compact power splitter with a QR code-like nanostructure is designed by a nonlinear fast search method (FSM). The highly functional structure is composed of a number of freely designed square pixels with the size of 120nm x 120nm which could be either dielectric or air. The lightwaves are scattered by a number of etched squares with optimized locations and the scattered waves superimpose at the outputs with the desired power ratio. We demonstrate 1x2 splitters with 1:1, 1:2, 1:3 split ratios and a 1x3 splitter with the ratio of 1:2:1. The footprint for all the devices is only 3.6umx3.6 um. Well-controlled split ratios are measured for all the cases. The measured transmission efficiencies of all the splitters are close to 80% over 30 nm wavelength range.

physics.optics↗

arXiv2016

Piezo Voltage Controlled Planar Hall Effect Devices

The electrical control of the magnetization switching in ferromagnets is highly desired for future spintronic applications. Here we report on hybrid piezoelectric (PZT) /ferromagnetic (Co2FeAl) devices in which the planar Hall voltage in the ferromagnetic layer is tuned solely by piezo voltages. The change of planar Hall voltage is associated with magnetization switching through 90 in the plane under piezo voltages. Room temperature magnetic NOT and NOR gates are demonstrated based on the piezo voltage controlled Co2FeAl planar Hall effect devices without the external magnetic field. Our demonstration may lead to the realization of both information storage and processing using ferromagnetic materials.

cond-mat.mes-hall↗

arXiv2016

Electric field control of deterministic current-induced magnetization switching in a hybrid ferromagnetic/ferroelectric structure

All-electrical and programmable manipulations of ferromagnetic bits are highly pursued for the aim of high integration and low energy consumption in modern information technology. Methods based on the spin-orbit torque switching in heavy metal/ferromagnet structures have been proposed with magnetic field, and recently are heading toward deterministic switching without external magnetic field. Here we demonstrate that an in-plane effective magnetic field can be induced by an electric field without breaking the symmetry of the structure of the thin film, and realize the deterministic magnetization switching in a hybrid ferromagnetic/ferroelectric structure with Pt/Co/Ni/Co/Pt layers on PMN-PT substrate. The effective magnetic field can be reversed by changing the direction of the applied electric field on the PMN-PT substrate, which fully replaces the controllability function of the external magnetic field. The electric field is found to generate an additional spin-orbit torque on the CoNiCo magnets, which is confirmed by macrospin calculations.

cond-mat.mtrl-sci↗

arXiv2016

Discovering the Skyline of Web Databases

Many web databases are "hidden" behind proprietary search interfaces that enforce the top-$k$ output constraint, i.e., each query returns at most $k$ of all matching tuples, preferentially selected and returned according to a proprietary ranking function. In this paper, we initiate research into the novel problem of skyline discovery over top-$k$ hidden web databases. Since skyline tuples provide critical insights into the database and include the top-ranked tuple for every possible ranking function following the monotonic order of attribute values, skyline discovery from a hidden web database can enable a wide variety of innovative third-party applications over one or multiple web databases. Our research in the paper shows that the critical factor affecting the cost of skyline discovery is the type of search interface controls provided by the website. As such, we develop efficient algorithms for three most popular types, i.e., one-ended range, free range and point predicates, and then combine them to support web databases that feature a mixture of these types. Rigorous theoretical analysis and extensive real-world online and offline experiments demonstrate the effectiveness of our proposed techniques and their superiority over baseline solutions.

cs.DB↗

arXiv2016

HDBSCAN: Density based Clustering over Location Based Services

Location Based Services (LBS) have become extremely popular and used by millions of users. Popular LBS run the entire gamut from mapping services (such as Google Maps) to restaurants (such as Yelp) and real-estate (such as Redfin). The public query interfaces of LBS can be abstractly modeled as a kNN interface over a database of two dimensional points: given an arbitrary query point, the system returns the k points in the database that are nearest to the query point. Often, k is set to a small value such as 20 or 50. In this paper, we consider the novel problem of enabling density based clustering over an LBS with only a limited, kNN query interface. Due to the query rate limits imposed by LBS, even retrieving every tuple once is infeasible. Hence, we seek to construct a cluster assignment function f(.) by issuing a small number of kNN queries, such that for any given tuple t in the database which may or may not have been accessed, f(.) outputs the cluster assignment of t with high accuracy. We conduct a comprehensive set of experiments over benchmark datasets and popular real-world LBS such as Yahoo! Flickr, Zillow, Redfin and Google Maps.

cs.DB↗