arXiv subjects

Jun Han

Publications and source records attributed to Jun Han.

At least 73 records · Page 4Linked to original sources

arXiv2019

SurFi: Detecting Surveillance Camera Looping Attacks with Wi-Fi Channel State Information (Extended Version)

The proliferation of surveillance cameras has greatly improved the physical security of many security-critical properties including buildings, stores, and homes. However, recent surveillance camera looping attacks demonstrate new security threats - adversaries can replay a seemingly benign video feed of a place of interest while trespassing or stealing valuables without getting caught. Unfortunately, such attacks are extremely difficult to detect in real-time due to cost and implementation constraints. In this paper, we propose SurFi to detect these attacks in real-time by utilizing commonly available Wi-Fi signals. In particular, we leverage that channel state information (CSI) from Wi-Fi signals also perceives human activities in the place of interest in addition to surveillance cameras. SurFi processes and correlates the live video feeds and the Wi-Fi CSI signals to detect any mismatches that would identify the presence of the surveillance camera looping attacks. SurFi does not require the deployment of additional infrastructure because Wi-Fi transceivers are easily found in the urban indoor environment. We design and implement the SurFi system and evaluate its effectiveness in detecting surveillance camera looping attacks. Our evaluation demonstrates that SurFi effectively identifies attacks with up to an attack detection accuracy of 98.8% and 0.1% false positive rate

cs.CR↗

arXiv2018

ContextServ: Towards Model-Driven Development of Context-AwareWeb Services

In the era of Web of Things and Services, Context-aware Web Services (CASs) are emerging as an important technology for building innovative context-aware applications. CASs enable the information integration from both the physical and virtual world, which affects human living. However, it is challenging to build CASs, due to the lack of context provisioning management approach and limited generic approach for formalizing the development process. We therefore propose ContextServ, a platform that uses a model-driven approach to support the full life cycle of CASs development, hence offering significant design and management flexibility. ContextServ implements a proposed UML-based modelling language ContextUML to support multiple modelling languages. It also supports dynamic adaptation of WS-BPEL based context-aware composite services by weaving context-aware rules into the process. Extensive experimental evaluations on ContextServ and its components showcase that ContextServ can support effective development and efficient execution of context-aware Web services.

cs.SE↗

arXiv2018

Individualized Time-Series Segmentation for Mining Mobile Phone User Behavior

Mobile phones can record individual's daily behavioral data as a time-series. In this paper, we present an effective time-series segmentation technique that extracts optimal time segments of individual's similar behavioral characteristics utilizing their mobile phone data. One of the determinants of an individual's behavior is the various activities undertaken at various times-of-the-day and days-of-the-week. In many cases, such behavior will follow temporal patterns. Currently, researchers use either equal or unequal interval-based segmentation of time for mining mobile phone users' behavior. Most of them take into account static temporal coverage of 24-h-a-day and few of them take into account the number of incidences in time-series data. However, such segmentations do not necessarily map to the patterns of individual user activity and subsequent behavior because of not taking into account the diverse behaviors of individuals over time-of-the-week. Therefore, we propose a behavior-oriented time segmentation (BOTS) technique that takes into account not only the temporal coverage of the week but also the number of incidences of diverse behaviors dynamically for producing similar behavioral time segments over the week utilizing time-series data. Experiments on the real mobile phone datasets show that our proposed segmentation technique better captures the user's dominant behavior at various times-of-the-day and days-of-the-week enabling the generation of high confidence temporal rules in order to mine individual mobile phone users' behavior.

cs.CY↗

arXiv2018

Jiamusi Pulsar Observations: II. Scintillations of 10 Pulsars

Context. Pulsars scintillate. Dynamic spectra show brightness variation of pulsars in the time and frequency domain. Secondary spectra demonstrate the distribution of fluctuation power in the dynamic spectra. Aims. Dynamic spectra strongly depend on observational frequencies, but were often observed at frequencies lower than 1.5 GHz. Scintillation observations at higher frequencies help to constrain the turbulence feature of the interstellar medium over a wide frequency range and can detect the scintillations of more distant pulsars. Methods. Ten pulsars were observed at 2250 MHz (S-band) with the Jiamusi 66 m telescope to study their scintillations. Their dynamic spectra were first obtained, from which the decorrelation bandwidths and time scales of diffractive scintillation were then derived by autocorrelation. Secondary spectra were calculated by forming the Fourier power spectra of the dynamic spectra. Results. Most of the newly obtained dynamic spectra are at the highest frequency or have the longest time span of any published data for these pulsars. For PSRs B0540+23, B2324+60 and B2351+61, these were the first dynamic spectra ever reported. The frequencydependence of scintillation parameters indicates that the intervening medium can rarely be ideally turbulent with a Kolmogorov spectrum. The thin screen model worked well at S-band for the scintillation of PSR B1933+16. Parabolic arcs were detected in the secondary spectra of three pulsars, PSRs B0355+54, B0540+23 and B2154+40, all of which were asymmetrically distributed. The inverted arclets of PSR B0355+54 were seen to evolve along the main parabola within a continuous observing session of 12 hours, from which the angular velocity of the pulsar was estimated that was consistent with the measurement by very long baseline interferometry (VLBI).

astro-ph.HE↗

arXiv2018

Stein Variational Gradient Descent Without Gradient

Stein variational gradient decent (SVGD) has been shown to be a powerful approximate inference algorithm for complex distributions. However, the standard SVGD requires calculating the gradient of the target density and cannot be applied when the gradient is unavailable. In this work, we develop a gradient-free variant of SVGD (GF-SVGD), which replaces the true gradient with a surrogate gradient, and corrects the induced bias by re-weighting the gradients in a proper form. We show that our GF-SVGD can be viewed as the standard SVGD with a special choice of kernel, and hence directly inherits the theoretical properties of SVGD. We shed insights on the empirical choice of the surrogate gradient and propose an annealed GF-SVGD that leverages the idea of simulated annealing to improve the performance on high dimensional complex distributions. Empirical studies show that our method consistently outperforms a number of recent advanced gradient-free MCMC methods.

stat.ML↗

arXiv2018

A hybrid architecture for astronomical computing

With many large science equipment constructing and putting into use, astronomy has stepped into the big data era. The new method and infrastructure of big data processing has become a new requirement of many astronomers. Cloud computing, Map/Reduce, Hadoop, Spark, etc. many new technology has sprung up in recent years. Comparing to the high performance computing(HPC), Data is the center of these new technology. So, a new computing architecture infrastructure is necessary, which can be shared by both HPC and big data processing. Based on Astronomy Cloud project of Chinese Virtual Observatory (China-VO), we have made much efforts to optimize the designation of the hybrid computing platform. which include the hardware architecture, cluster management, Job and Resource scheduling.

cs.DC↗

arXiv2018

A Conception of Engineering Design for Remote Unattended Operation Public Observatory

Public observatory project is playing more and more important role in science popularization education and scientific research, and many amateur astronomers also have began to build their own observatories in remote areas. As a result of the limitation of technical condition and construction funds for amateur astronomers, their system often breaks down, and then a stable remote unattended operation system becomes very critical. Hardware connection and control is the basic and core part in observatory design. Here we propose a conception of engineering hardware design for public observatory operation as a bridge between observatory equipment and observation software. It can not only satisfy multiple observation mode requirement, but also save cost.

astro-ph.IM↗

arXiv2017

Identifying Recent Behavioral Data Length in Mobile Phone Log

Mobile phone log data (e.g., phone call log) is not static as it is progressively added to day-by-day according to individ- ual's diverse behaviors with mobile phones. Since human behavior changes over time, the most recent pattern is more interesting and significant than older ones for predicting in- dividual's behavior. The goal of this poster paper is to iden- tify the recent behavioral data length dynamically from the entire phone log for recency-based behavior modeling. To the best of our knowledge, this is the first dynamic recent log-based study that takes into account individual's recent behavioral patterns for modeling their phone call behaviors.

cs.CY↗

arXiv2017

An Improved Naive Bayes Classifier-based Noise Detection Technique for Classifying User Phone Call Behavior

The presence of noisy instances in mobile phone data is a fundamental issue for classifying user phone call behavior (i.e., accept, reject, missed and outgoing), with many potential negative consequences. The classification accuracy may decrease and the complexity of the classifiers may increase due to the number of redundant training samples. To detect such noisy instances from a training dataset, researchers use naive Bayes classifier (NBC) as it identifies misclassified instances by taking into account independence assumption and conditional probabilities of the attributes. However, some of these misclassified instances might indicate usages behavioral patterns of individual mobile phone users. Existing naive Bayes classifier based noise detection techniques have not considered this issue and, thus, are lacking in classification accuracy. In this paper, we propose an improved noise detection technique based on naive Bayes classifier for effectively classifying users' phone call behaviors. In order to improve the classification accuracy, we effectively identify noisy instances from the training dataset by analyzing the behavioral patterns of individuals. We dynamically determine a noise threshold according to individual's unique behavioral patterns by using both the naive Bayes classifier and Laplace estimator. We use this noise threshold to identify noisy instances. To measure the effectiveness of our technique in classifying user phone call behavior, we employ the most popular classification algorithm (e.g., decision tree). Experimental results on the real phone call log dataset show that our proposed technique more accurately identifies the noisy instances from the training datasets that leads to better classification accuracy.

cs.LG↗

arXiv2017

High efficiently numerical simulation of the TDGL equation with reticular free energy in hydrogel

In this paper, we focus on the numerical simulation of phase separation about macromolecule microsphere composite (MMC) hydrogel. The model equation is based on Time-Dependent Ginzburg-Landau (TDGL) equation with reticular free energy. We have put forward two $L^2$ stable schemes to simulate simplified TDGL equation. In numerical experiments, we observe that simulating the whole process of phase separation requires a considerably long time. We also notice that the total free energy changes significantly in initial time and varies slightly in the following time. Based on these properties, we introduce an adaptive strategy based on one of stable scheme mentioned. It is found that the introduction of the time adaptivity cannot only resolve the dynamical changes of the solution accurately but also can significantly save CPU time for the long time simulation.

math.NA↗

arXiv2017

Stein Variational Adaptive Importance Sampling

We propose a novel adaptive importance sampling algorithm which incorporates Stein variational gradient decent algorithm (SVGD) with importance sampling (IS). Our algorithm leverages the nonparametric transforms in SVGD to iteratively decrease the KL divergence between our importance proposal and the target distribution. The advantages of this algorithm are twofold: first, our algorithm turns SVGD into a standard IS algorithm, allowing us to use standard diagnostic and analytic tools of IS to evaluate and interpret the results; second, we do not restrict the choice of our importance proposal to predefined distribution families like traditional (adaptive) IS methods. Empirical experiments demonstrate that our algorithm performs well on evaluating partition functions of restricted Boltzmann machines and testing likelihood of variational auto-encoders.

stat.ML↗

arXiv2017

Service Virtualisation of Internet-of-Things Devices: Techniques and Challenges

Service virtualization is an approach that uses virtualized environments to automatically test enterprise services in production-like conditions. Many techniques have been proposed to provide such a realistic environment for enterprise services. The Internet-of-Things (IoT) is an emerging field which connects a diverse set of devices over different transport layers, using a variety of protocols. Provisioning a virtual testbed of IoT devices can accelerate IoT application development by enabling automated testing without requiring a continuous connection to the physical devices. One solution is to expand existing enterprise service virtualization to IoT environments. There are various structural differences between the two environments that should be considered to implement appropriate service virtualization for IoT. This paper examines the structural differences between various IoT protocols and enterprise protocols and identifies key technical challenges that need to be addressed to implement service virtualization in IoT environments.

cs.SE↗

arXiv2017

Spectral indices for radio emission of 228 pulsars

We determine spectral indices of 228 pulsars by using Parkes pulsar data observed at 1.4 GHz, among which 200 spectra are newly determined. The indices are distributed in the range from -4.84 to -0.46.Together with known pulsar spectra from literature, we tried to find clues to the pulsar emission process. The weak correlations between the spectral index, the spin-down energy loss rate $\dot{E}$ and the potential drop in the polar gap $ΔΨ$ hint that emission properties are related to the particle acceleration process in a pulsar's magnetosphere.

astro-ph.HE↗

arXiv2017

A Policy Model and Framework for Context-Aware Access Control to Information Resources

In today's dynamic ICT environments, the ability to control users' access to resources becomes ever important. On the one hand, it should adapt to the users' changing needs; on the other hand, it should not be compromised. Therefore, it is essential to have a flexible access control model, incorporating dynamically changing context information. Towards this end, this paper introduces a policy framework for context-aware access control (CAAC) applications that extends the role-based access control model with both dynamic associations of user-role and role-permission capabilities. We first present a formal model of CAAC policies for our framework. Using this model, we then introduce an ontology-based approach and a software prototype for modelling and enforcing CAAC policies. In addition, we evaluate our policy ontology model and framework by considering (i) the completeness of the ontology concepts, specifying different context-aware user-role and role-permission assignment policies from the healthcare scenarios; (ii) the correctness and consistency of the ontology semantics, assessing the core and domain-specific ontologies through the healthcare case study; and (iii) the performance of the framework by means of response time. The evaluation results demonstrate the feasibility of our framework and quantify the performance overhead of achieving context-aware access control to information resources.

cs.CR↗

arXiv2017

Bootstrap Model Aggregation for Distributed Statistical Learning

In distributed, or privacy-preserving learning, we are often given a set of probabilistic models estimated from different local repositories, and asked to combine them into a single model that gives efficient statistical estimation. A simple method is to linearly average the parameters of the local models, which, however, tends to be degenerate or not applicable on non-convex models, or models with different parameter dimensions. One more practical strategy is to generate bootstrap samples from the local models, and then learn a joint model based on the combined bootstrap set. Unfortunately, the bootstrap procedure introduces additional noise and can significantly deteriorate the performance. In this work, we propose two variance reduction methods to correct the bootstrap noise, including a weighted M-estimator that is both statistically efficient and practically powerful. Both theoretical and empirical analysis is provided to demonstrate our methods.

stat.ML↗

arXiv2016

Enterprise Software Service Emulation: Constructing Large-Scale Testbeds

Constructing testbeds for systems which are interconnected with large networks of other software services is a challenging task. It is particularly difficult to create testbeds facilitating evaluation of the non-functional qualities of a system, such as scalability, that can be expected in production deployments. Software service emulation is an approach for creating such testbeds where service behaviour is defined by emulate-able models executed in an emulation runtime environment. We present (i) a meta-modelling framework supporting emulate-able service modelling (including messages, protocol, behaviour and states), and (ii) Kaluta, an emulation environment able to concurrently execute large numbers (thousands) of service models, providing a testbed which mimics the behaviour and characteristics of large networks of interconnected software services. Experiments show that Kaluta can emulate 10,000 servers using a single physical machine, and is a practical testbed for scalability testing of a real, enterprise-grade identity management suite. The insights gained into the tested enterprise system were used to enhance its design.

cs.SE↗

arXiv2016

Opaque Service Virtualisation: A Practical Tool for Emulating Endpoint Systems

Large enterprise software systems make many complex interactions with other services in their environment. Developing and testing for production-like conditions is therefore a very challenging task. Current approaches include emulation of dependent services using either explicit modelling or record-and-replay approaches. Models require deep knowledge of the target services while record-and-replay is limited in accuracy. Both face developmental and scaling issues. We present a new technique that improves the accuracy of record-and-replay approaches, without requiring prior knowledge of the service protocols. The approach uses Multiple Sequence Alignment to derive message prototypes from recorded system interactions and a scheme to match incoming request messages against prototypes to generate response messages. We use a modified Needleman-Wunsch algorithm for distance calculation during message matching. Our approach has shown greater than 99% accuracy for four evaluated enterprise system messaging protocols. The approach has been successfully integrated into the CA Service Virtualization commercial product to complement its existing techniques.

cs.SE↗

arXiv2016

Enhanced Playback of Automated Service Emulation Models Using Entropy Analysis

Service virtualisation is a supporting tool for DevOps to generate interactive service models of dependency systems on which a system-under-test relies. These service models allow applications under development to be continuously tested against production-like conditions. Generating these virtual service models requires expert knowledge of the service protocol, which may not always be available. However, service models may be generated automatically from network traces. Previous work has used the Needleman-Wunsch algorithm to select a response from the service model to play back for a live request. We propose an extension of the Needleman-Wunsch algorithm, which uses entropy analysis to automatically detect the critical matching fields for selecting a response. Empirical tests against four enterprise protocols demonstrate that entropy weighted matching can improve response accuracy.

cs.SE↗