arXiv subjects

Pan Hui

Publications and source records attributed to Pan Hui.

At least 181 records · Page 10Linked to original sources

arXiv2018

Privacy Preserving and Cost Optimal Mobile Crowdsensing using Smart Contracts on Blockchain

The popularity and applicability of mobile crowdsensing applications are continuously increasing due to the widespread of mobile devices and their sensing and processing capabilities. However, we need to offer appropriate incentives to the mobile users who contribute their resources and preserve their privacy. Blockchain technologies enable semi-anonymous multi-party interactions and can be utilized in crowdsensing applications to maintain the privacy of the mobile users while ensuring first-rate crowdsensed data. In this work, we propose to use blockchain technologies and smart contracts to orchestrate the interactions between mobile crowdsensing providers and mobile users for the case of spatial crowdsensing, where mobile users need to be at specific locations to perform the tasks. Smart contracts, by operating as processes that are executed on the blockchain, are used to preserve users' privacy and make payments. Furthermore, for the assignment of the crowdsensing tasks to the mobile users, we design a truthful, cost-optimal auction that minimizes the payments from the crowdsensing providers to the mobile users. Extensive experimental results show that the proposed privacy preserving auction outperforms state-of-the-art proposals regarding cost by ten times for high numbers of mobile users and tasks.

cs.GT↗

arXiv2018

The focusing effect of electron flow and negative refraction in three dimensional topological insulators

We studied the focusing effect of electron flow induced by a single p-n junction (PNJ) in three-dimensional topological insulator. It is found that the electrons flowing from the n region can be focused at the symmetric position in the p region, acting as a perfect Veselago lens, regardless whether the incident energy is within or beyond the bulk energy gap. In the former case, the focusing effect occurs only in the surfaces. While in the latter case, the focusing effect occurs beyond the surfaces. These results show that the focusing effect of electron flow is a general phenomenon. It means the negative refraction may arise in all materials that are described by the massive or massless Dirac equation of 2D or beyond 2D system. Furthermore, we also find the focusing effect is robust in resisting the moderate random disorders. Finally, in the presence of a weak perpendicular magnetic field, the focusing effect remains well except that the position of the focal point is deflected by the transverse Lorentz force. Due to the finite size effect, the position of focal point oscillates periodically with a period of Delta B.

cond-mat.mes-hall↗

arXiv2018

Boosting the Performance of Content Centric Networking using Delay Tolerant Networking Mechanisms

Content-centric networking (CCN) introduces a paradigm shift from a host centric to an information centric communication model for future Internet architectures. It supports the retrieval of a particular content regardless of the physical location of the content. Content caching and content delivery networks are the most popular approaches to deal with the inherent issues of content delivery on the Internet that are caused by its design. Moreover, intermittently connected mobile environments or disruptive networks present a significant challenge to CCN deployment. In this paper, we consider the possibility of using mobile users in improving the efficiency of content delivery. Mobile users are producing a significant fraction of the total Internet traffic, and modern mobile devices have enough storage to cache the downloaded content that may interest other mobile users for a short period too. We present an analytical model of the CCN framework that integrates a delay tolerant networking architecture into the native CCN, and we present large-scale simulation results. Caching on mobile devices can improve the content retrieval time by more than 50%, while the fraction of the requests that are delivered from other mobile devices can be more than 75% in many cases.

cs.NI↗

arXiv2018

Where's YOUR focus: Personalized Attention

Human visual attention is subjective and biased according to the personal preference of the viewer, however, current works of saliency detection are general and objective, without counting the factor of the observer. This will make the attention prediction for a particular person not accurate enough. In this work, we present the novel idea of personalized attention prediction and develop Personalized Attention Network (PANet), a convolutional network that predicts saliency in images with personal preference. The model consists of two streams which share common feature extraction layers, and one stream is responsible for saliency prediction, while the other is adapted from the detection model and used to fit user preference. We automatically collect user preference from their albums and leaves them freedom to define what and how many categories their preferences are divided into. To train PANet, we dynamically generate ground truth saliency maps upon existing detection labels and saliency labels, and the generation parameters are based upon our collected datasets consists of 1k images. We evaluate the model with saliency prediction metrics and test the trained model on different preference vectors. The results have shown that our system is much better than general models in personalized saliency prediction and is efficient to use for different preferences.

cs.CV↗

arXiv2017

LocalCoin: An Ad-hoc Payment Scheme for Areas with High Connectivity

The popularity of digital currencies, especially cryptocurrencies, has been continuously growing since the appearance of Bitcoin. Bitcoin's security lies in a proof-of-work scheme, which requires high computational resources at the miners. Despite advances in mobile technology, existing cryptocurrencies cannot be maintained by mobile devices due to their low processing capabilities. Mobile devices can only accommodate mobile applications (wallets) that allow users to exchange credits of cryptocurrencies. In this work, we propose LocalCoin, an alternative cryptocurrency that requires minimal computational resources, produces low data traffic and works with off-the-shelf mobile devices. LocalCoin replaces the computational hardness that is at the root of Bitcoin's security with the social hardness of ensuring that all witnesses to a transaction are colluders. Localcoin features (i) a lightweight proof-of-work scheme and (ii) a distributed blockchain. We analyze LocalCoin for double spending for passive and active attacks and prove that under the assumption of sufficient number of users and properly selected tuning parameters the probability of double spending is close to zero. Extensive simulations on real mobility traces, realistic urban settings, and random geometric graphs show that the probability of success of one transaction converges to 1 and the probability of the success of a double spending attempt converges to 0.

cs.CR↗

arXiv2017

A survey on haptic technologies for mobile augmented reality

Augmented Reality (AR) and Mobile Augmented Reality (MAR) applications have gained much research and industry attention these days. The mobile nature of MAR applications limits users' interaction capabilities such as inputs, and haptic feedbacks. This survey reviews current research issues in the area of human computer interaction for MAR and haptic devices. The survey first presents human sensing capabilities and their applicability in AR applications. We classify haptic devices into two groups according to the triggered sense: cutaneous/tactile: touch, active surfaces, and mid-air, kinesthetic: manipulandum, grasp, and exoskeleton. Due to the mobile capabilities of MAR applications, we mainly focus our study on wearable haptic devices for each category and their AR possibilities. To conclude, we discuss the future paths that haptic feedbacks should follow for MAR applications and their challenges.

cs.HC↗

arXiv2017

Multitarget search on complex networks: A logarithmic growth of global mean random cover time

We investigate multitarget search on complex networks and derive an exact expression for the mean random cover time that quantifies the expected time a walker needs to visit multiple targets. Based on this, we recover and extend some interesting results of multitarget search on networks. Specifically, we observe the logarithmic increase of the global mean random cover time with the target number for a broad range of random search processes, including generic random walks, biased random walks, and maximal entropy random walks. We show that the logarithmic growth pattern is a universal feature of multi-target search on networks by using the annealed network approach and the Sherman-Morrison formula. Moreover, we find that for biased random walks, the global mean random cover time can be minimized, and that the corresponding optimal parameter also minimizes the global mean first passage time, pointing towards its robustness. Our findings further confirm that the logarithmic growth pattern is a universal law governing multitarget search in confined media.

physics.soc-ph↗

arXiv2017

Interaction Methods for Smart Glasses

Since the launch of Google Glass in 2014, smart glasses have mainly been designed to support micro-interactions. The ultimate goal for them to become an augmented reality interface has not yet been attained due to an encumbrance of controls. Augmented reality involves superimposing interactive computer graphics images onto physical objects in the real world. This survey reviews current research issues in the area of human computer interaction for smart glasses. The survey first studies the smart glasses available in the market and afterwards investigates the interaction methods proposed in the wide body of literature. The interaction methods can be classified into hand-held, touch, and touchless input. This paper mainly focuses on the touch and touchless input. Touch input can be further divided into on-device and on-body, while touchless input can be classified into hands-free and freehand. Next, we summarize the existing research efforts and trends, in which touch and touchless input are evaluated by a total of eight interaction goals. Finally, we discuss several key design challenges and the possibility of multi-modal input for smart glasses.

cs.HC↗

arXiv2017

Spatial Interference Detection for Mobile Visible Light Communication

Taking advantage of the rolling shutter effect of CMOS cameras in smartphones is a common practice to increase the transfered data rate with visible light communication (VLC) without employing external equipment such as photodiodes. VLC can then be used as replacement of other marker based techniques for object identification for Augmented Reality and Ubiquitous computing applications. However, the rolling shutter effect only allows to transmit data over a single dimension, which considerably limits the available bandwidth. In this article we propose a new method exploiting spacial interference detection to enable parallel transmission and design a protocol that enables easy identification of interferences between two signals. By introducing a second dimension, we are not only able to significantly increase the available bandwidth, but also identify and isolate light sources in close proximity.

cs.NI↗

arXiv2017

Steal Your Life Using 5 Cents: Hacking Android Smartphones with NFC Tags

Nowadays privacy in the connected world is a big user's concern. The ubiquity of mobile devices permits billions of users browse the web at anytime, anywhere. Near Field Communication (NFC) appeared as a seamlessly and simply communication protocol between devices. Commercial services such as Android Pay, and Apple Pay offer contactless payment methods that are spreading in more and more scenarios. However, we take risks while using NFC on Android devices, we can be hacked, and our privacy can be affected. In this paper we study the current vulnerabilities in the NFC-Android ecosystem. We conduct a series of experiments and we expose that with NFC and Android devices are vulnerable to URL/URI spoofing, Bank/social network information hacking, and user's device tracking via fingerprint and geo-location. It is important for the community to understand the problem and come up solution that can tackle these issues and inform the users about privacy awareness and risks on using these contactless services.

cs.CR↗

arXiv2017

Semantic homophily in online communication: evidence from Twitter

People are observed to assortatively connect on a set of traits. This phenomenon, termed assortative mixing or sometimes homophily, can be quantified through assortativity coefficient in social networks. Uncovering the exact causes of strong assortative mixing found in social networks has been a research challenge. Among the main suggested causes from sociology are the tendency of similar individuals to connect (often itself referred as homophily) and the social influence among already connected individuals. An important question to researchers and in practice can be tackled, as we present here: understanding the exact mechanisms of interplay between these tendencies and the underlying social network structure. Namely, in addition to the mentioned assortativity coefficient, there are several other static and temporal network properties and substructures that can be linked to the tendencies of homophily and social influence in the social network and we herein investigate those. Concretely, we tackle a computer-mediated \textit{communication network} (based on Twitter mentions) and a particular type of assortative mixing that can be inferred from the semantic features of communication content that we term \textit{semantic homophily}. Our work, to the best of our knowledge, is the first to offer an in-depth analysis on semantic homophily in a communication network and the interplay between them. We quantify diverse levels of semantic homophily, identify the semantic aspects that are the drivers of observed homophily, show insights in its temporal evolution and finally, we present its intricate interplay with the communication network on Twitter. By analyzing these mechanisms we increase understanding on what are the semantic aspects that shape and how they shape the human computer-mediated communication.

physics.soc-ph↗

arXiv2016

Keep Your Nice Friends Close, but Your Rich Friends Closer -- Computation Offloading Using NFC

The increasing complexity of smartphone applications and services necessitate high battery consumption but the growth of smartphones' battery capacity is not keeping pace with these increasing power demands. To overcome this problem, researchers gave birth to the Mobile Cloud Computing (MCC) research area. In this paper we advance on previous ideas, by proposing and implementing the first known Near Field Communication (NFC)-based computation offloading framework. This research is motivated by the advantages of NFC's short distance communication, with its better security, and its low battery consumption. We design a new NFC communication protocol that overcomes the limitations of the default protocol; removing the need for constant user interaction, the one-way communication restraint, and the limit on low data size transfer. We present experimental results of the energy consumption and the time duration of two computationally intensive representative applications: (i) RSA key generation and encryption, and (ii) gaming/puzzles. We show that when the helper device is more powerful than the device offloading the computations, the execution time of the tasks is reduced. Finally, we show that devices that offload application parts considerably reduce their energy consumption due to the low-power NFC interface and the benefits of offloading.

cs.NI↗

arXiv2016

Dissecting the End-to-end Latency of Interactive Mobile Video Applications

In this paper we measure the step-wise latency in the pipeline of three kinds of interactive mobile video applications that are rapidly gaining popularity, namely Remote Graphics Rendering (RGR) of which we focus on mobile cloud gaming, Mobile Augmented Reality (MAR), and Mobile Virtual Reality (MVR). The applications differ from each other by the way in which the user interacts with the application, i.e., video I/O and user controls, but they all share in common the fact that their user experience is highly sensitive to end-to-end latency. Long latency between a user control event and display update renders the application unusable. Hence, understanding the nature and origins of latency of these applications is of paramount importance. We show through extensive measurements that control input and display buffering have a substantial effect on the overall delay. Our results shed light on the latency bottlenecks and the maturity of technology for seamless user experience with these applications.

cs.HC↗

arXiv2016

Navigation by anomalous random walks on complex networks

Anomalous random walks having long-range jumps are a critical branch of dynamical processes on networks, which can model a number of search and transport processes. However, traditional measurements based on mean first passage time are not useful as they fail to characterize the cost associated with each jump. Here we introduce a new concept of mean first traverse distance (MFTD) to characterize anomalous random walks that represents the expected traverse distance taken by walkers searching from source node to target node, and we provide a procedure for calculating the MFTD between two nodes. We use Levy walks on networks as an example, and demonstrate that the proposed approach can unravel the interplay between diffusion dynamics of Levy walks and the underlying network structure. Interestingly, applying our framework to the famous PageRank search, we can explain why its damping factor empirically chosen to be around 0.85. The framework for analyzing anomalous random walks on complex networks offers a new useful paradigm to understand the dynamics of anomalous diffusion processes, and provides a unified scheme to characterize search and transport processes on networks.

physics.soc-ph↗

arXiv2016

Cardea: Context-Aware Visual Privacy Protection from Pervasive Cameras

The growing popularity of mobile and wearable devices with built-in cameras, the bright prospect of camera related applications such as augmented reality and life-logging system, the increased ease of taking and sharing photos, and advances in computer vision techniques have greatly facilitated people's lives in many aspects, but have also inevitably raised people's concerns about visual privacy at the same time. Motivated by recent user studies that people's privacy concerns are dependent on the context, in this paper, we propose Cardea, a context-aware and interactive visual privacy protection framework that enforces privacy protection according to people's privacy preferences. The framework provides people with fine-grained visual privacy protection using: i) personal privacy profiles, with which people can define their context-dependent privacy preferences; and ii) visual indicators: face features, for devices to automatically locate individuals who request privacy protection; and iii) hand gestures, for people to flexibly interact with cameras to temporarily change their privacy preferences. We design and implement the framework consisting of the client app on Android devices and the cloud server. Our evaluation results confirm this framework is practical and effective with 86% overall accuracy, showing promising future for context-aware visual privacy protection from pervasive cameras.

cs.CR↗

arXiv2016

Security Pricing as an Enabler of Cyber-Insurance: A First Look at Differentiated Pricing Markets

Despite the promising potential of network risk management services (e.g., cyber-insurance) to improve information security, their deployment is relatively scarce, primarily due to such service companies being unable to guarantee profitability. As a novel approach to making cyber-insurance services more viable, we explore a symbiotic relationship between security vendors (e.g., Symantec) capable of price differentiating their clients, and cyber-insurance agencies having possession of information related to the security investments of their clients. The goal of this relationship is to (i) allow security vendors to price differentiate their clients based on security investment information from insurance agencies, (ii) allow the vendors to make more profit than in homogeneous pricing settings, and (iii) subsequently transfer some of the extra profit to cyber-insurance agencies to make insurance services more viable. \noindent In this paper, we perform a theoretical study of a market for differentiated security product pricing, primarily with a view to ensuring that security vendors (SVs) make more profit in the differentiated pricing case as compared to the case of non-differentiated pricing. In order to practically realize such pricing markets, we propose novel and \emph{computationally efficient} consumer differentiated pricing mechanisms for SVs based on (i) the market structure, (ii) the communication network structure of SV consumers captured via a consumer's \emph{Bonacich centrality} in the network, and (iii) security investment amounts made by SV consumers.

cs.GT↗

arXiv2016

GraphPrints: Towards a Graph Analytic Method for Network Anomaly Detection

This paper introduces a novel graph-analytic approach for detecting anomalies in network flow data called GraphPrints. Building on foundational network-mining techniques, our method represents time slices of traffic as a graph, then counts graphlets -- small induced subgraphs that describe local topology. By performing outlier detection on the sequence of graphlet counts, anomalous intervals of traffic are identified, and furthermore, individual IPs experiencing abnormal behavior are singled-out. Initial testing of GraphPrints is performed on real network data with an implanted anomaly. Evaluation shows false positive rates bounded by 2.84% at the time-interval level, and 0.05% at the IP-level with 100% true positive rates at both.

cs.CR↗

arXiv2015

Explaining the Power-law Distribution of Human Mobility Through Transportation Modality Decomposition

Human mobility has been empirically observed to exhibit Levy flight characteristics and behaviour with power-law distributed jump size. The fundamental mechanisms behind this behaviour has not yet been fully explained. In this paper, we analyze urban human mobility and we propose to explain the Levy walk behaviour observed in human mobility patterns by decomposing them into different classes according to the different transportation modes, such as Walk/Run, Bicycle, Train/Subway or Car/Taxi/Bus. Our analysis is based on two real-life GPS datasets containing approximately 10 and 20 million GPS samples with transportation mode information. We show that human mobility can be modelled as a mixture of different transportation modes, and that these single movement patterns can be approximated by a lognormal distribution rather than a power-law distribution. Then, we demonstrate that the mixture of the decomposed lognormal flight distributions associated with each modality is a power-law distribution, providing an explanation to the emergence of Levy Walk patterns that characterize human mobility patterns.

physics.soc-ph↗