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Vector Abstraction And Concretization For Scalable Detection Of Refactorings, Narcisa Andreea Milea, Lingxiao Jiang, Siau-Cheng Khoo
Vector Abstraction And Concretization For Scalable Detection Of Refactorings, Narcisa Andreea Milea, Lingxiao Jiang, Siau-Cheng Khoo
Research Collection School Of Computing and Information Systems
Automated techniques have been proposed to either identify refactoring opportunities (i.e., code fragments that can be but have not yet been restructured in a program), or reconstruct historical refactorings (i.e., code restructuring operations that have happened between different versions of a program). In this paper, we propose a new technique that can detect both refactoring opportunities and historical refactorings in large code bases. The key of our technique is the design of vector abstraction and concretization operations that can encode code changes induced by certain refactorings as characteristic vectors. Thus, the problem of identifying refactorings can be reduced to the …
Grumon: Fast And Accurate Group Monitoring For Heterogeneous Urban Spaces, Rijurekha Sen, Youngki Lee, Kasthuri Jayarajah, Rajesh Krishna Balan, Archan Misra
Grumon: Fast And Accurate Group Monitoring For Heterogeneous Urban Spaces, Rijurekha Sen, Youngki Lee, Kasthuri Jayarajah, Rajesh Krishna Balan, Archan Misra
Research Collection School Of Computing and Information Systems
Real-time monitoring of groups and their rich contexts will be a key building block for futuristic, group-aware mobile services. In this paper, we propose GruMon, a fast and accurate group monitoring system for dense and complex urban spaces. GruMon meets the performance criteria of precise group detection at low latencies by overcoming two critical challenges of practical urban spaces, namely (a) the high density of crowds, and (b) the imprecise location information available indoors. Using a host of novel features extracted from commodity smartphone sensors, GruMon can detect over 80% of the groups, with 97% precision, using 10 minutes latency …
Perspectives On Task Ownership In Mobile Operating System Development [Invited Talk], Subhajit Datta
Perspectives On Task Ownership In Mobile Operating System Development [Invited Talk], Subhajit Datta
Research Collection School Of Computing and Information Systems
There can be little contention about Stroustrup's epigrammatic remark: our civilization runs on software. However a caveat is increasingly due, much of the software that runs our civilization, runs on mobile devices today. Mobile operating systems have come to play a preeminent role in the ubiquity and utility of such devices. The development ecosystem of Android - one of the most popular mobile operating systems - presents an interesting context for studying whether and how collaboration dynamics in mobile development differ from conventional software development. In this paper, we examine factors that influence task ownership in Android development. Our results …
Organizing Video Search Results To Adapted Semantic Hierarchies For Topic-Based Browsing, Jiajun Wang, Yu-Gang Jiang, Qiang Wang, Kuiyuan Yang, Chong-Wah Ngo
Organizing Video Search Results To Adapted Semantic Hierarchies For Topic-Based Browsing, Jiajun Wang, Yu-Gang Jiang, Qiang Wang, Kuiyuan Yang, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
Organizing video search results into semantically structured hierarchies can greatly improve the efficiency of browsing complex query topics. Traditional hierarchical clustering techniques are inadequate since they lack the ability to generate semantically interpretable structures. In this paper, we introduce an approach to organize video search results to an adapted semantic hierarchy. As many hot search topics such as celebrities and famous cities have Wikipedia pages where hierarchical topic structures are available, we start from the Wikipedia hierarchies and adjust the structures according to the characteristics of the returned videos from a search engine. Ordinary clustering based on textual information of …
Generative Modeling Of Entity Comparisons In Text, Maksim Tkachenko, Hady W. Lauw
Generative Modeling Of Entity Comparisons In Text, Maksim Tkachenko, Hady W. Lauw
Research Collection School Of Computing and Information Systems
Users frequently rely on online reviews for decision making. In addition to allowing users to evaluate the quality of individual products, reviews also support comparison shopping. One key user activity is to compare two (or more) products based on a specific aspect. However, making a comparison across two different reviews, written by different authors, is not always equitable due to the different standards and preferences of individual authors. Therefore, we focus instead on comparative sentences, whereby two products are compared directly by a review author within a single sentence. We study the problem of comparative relation mining. Given a set …
Semantics-Aware Android Malware Classification Using Weighted Contextual Api Dependency Graphs, Mu Zhang, Yue Duan, Heng Yin, Zhiruo Zhao
Semantics-Aware Android Malware Classification Using Weighted Contextual Api Dependency Graphs, Mu Zhang, Yue Duan, Heng Yin, Zhiruo Zhao
Research Collection School Of Computing and Information Systems
The drastic increase of Android malware has led to a strong interest in developing methods to automate the malware analysis process. Existing automated Android malware detection and classification methods fall into two general categories: 1) signature-based and 2) machine learning-based. Signature-based approaches can be easily evaded by bytecode-level transformation attacks. Prior learning-based works extract features from application syntax, rather than program semantics, and are also subject to evasion. In this paper, we propose a novel semantic-based approach that classifies Android malware via dependency graphs. To battle transformation attacks, we extract a weighted contextual API dependency graph as program semantics to …
Combining Multiple Kernel Methods On Riemannian Manifold For Emotion Recognition In The Wild, M. Liu, R. Wang, S. Li, S. Shan, Zhiwu Huang, X. Chen
Combining Multiple Kernel Methods On Riemannian Manifold For Emotion Recognition In The Wild, M. Liu, R. Wang, S. Li, S. Shan, Zhiwu Huang, X. Chen
Research Collection School Of Computing and Information Systems
In this paper, we present the method for our submission to the Emotion Recognition in the Wild Challenge (EmotiW 2014). The challenge is to automatically classify the emotions acted by human subjects in video clips under realworld environment. In our method, each video clip can be represented by three types of image set models (i.e. linear subspace, covariance matrix, and Gaussian distribution) respectively, which can all be viewed as points residing on some Riemannian manifolds. Then different Riemannian kernels are employed on these set models correspondingly for similarity/distance measurement. For classification, three types of classifiers, i.e. kernel SVM, logistic regression, …
Celelabel: An Interactive System For Annotating Celebrities In Web Videos, Zhineng Chen, Jinfeng Bai, Chong-Wah Ngo, Bailan Feng, Bo Xu
Celelabel: An Interactive System For Annotating Celebrities In Web Videos, Zhineng Chen, Jinfeng Bai, Chong-Wah Ngo, Bailan Feng, Bo Xu
Research Collection School Of Computing and Information Systems
Manual annotation of celebrities in Web videos is an essential task in many people-related Web services. The task, however, poses a significant challenge even to skillful annotators, mainly due to the large quantity of unfamiliar and greatly varied celebrities, and the lack of a customized system for it. This work develops CeleLabel, an interactive system for manually annotating celebrities in the Web video domain. The peculiarity of CeleLabel is to exploit and display multiple types of information that could assist the annotation, including video content, context surrounding and within a video, celebrity images on the Web, and human factors. Using …
Scalable Visual Instance Mining With Threads Of Features, Wei Zhang, Hongzhi Li, Chong-Wah Ngo, Shih-Fu Chang
Scalable Visual Instance Mining With Threads Of Features, Wei Zhang, Hongzhi Li, Chong-Wah Ngo, Shih-Fu Chang
Research Collection School Of Computing and Information Systems
We address the problem of visual instance mining, which is to extract frequently appearing visual instances automatically from a multimedia collection. We propose a scalable mining method by exploiting Thread of Features (ToF). Specifically, ToF, a compact representation that links consistent features across images, is extracted to reduce noises, discover patterns, and speed up processing. Various instances, especially small ones, can be discovered by exploiting correlated ToFs. Our approach is significantly more effective than other methods in mining small instances. At the same time, it is also more efficient by requiring much fewer hash tables. We compared with several state-of-the-art …
Click-Through-Based Subspace Learning For Image Search, Yingwei Pan, Ting Yao, Xinmei Tian, Houqiang Li, Chong-Wah Ngo
Click-Through-Based Subspace Learning For Image Search, Yingwei Pan, Ting Yao, Xinmei Tian, Houqiang Li, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
One of the fundamental problems in image search is to rank image documents according to a given textual query. We address two limitations of the existing image search engines in this paper. First, there is no straightforward way of comparing textual keywords with visual image content. Image search engines therefore highly depend on the surrounding texts, which are often noisy or too few to accurately describe the image content. Second, ranking functions are trained on query-image pairs labeled by human labelers, making the annotation intellectually expensive and thus cannot be scaled up. We demonstrate that the above two fundamental challenges …
Vireo @ Trecvid 2014: Instance Search And Semantic Indexing, Wei Zhang, Hao Zhang, Ting Yao, Yijie Lu, Jingjing Chen, Chong-Wah Ngo
Vireo @ Trecvid 2014: Instance Search And Semantic Indexing, Wei Zhang, Hao Zhang, Ting Yao, Yijie Lu, Jingjing Chen, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
This paper summarizes the following two tasks participated by VIREO group: instance search and semantic indexing. We will present our approaches and analyze the results obtained in TRECVID 2014 benchmark evaluation
Imagespirit: Verbal Guided Image Parsing, Ming-Ming Cheng, Shuai Zheng, Wen-Yan Lin, Vibhav Vineet, Paul Sturgess, Nigel Crook, Niloy J. Mitra, Philip Torr
Imagespirit: Verbal Guided Image Parsing, Ming-Ming Cheng, Shuai Zheng, Wen-Yan Lin, Vibhav Vineet, Paul Sturgess, Nigel Crook, Niloy J. Mitra, Philip Torr
Research Collection School Of Computing and Information Systems
Humans describe images in terms of nouns and adjectives while algorithms operate on images represented as sets of pixels. Bridging this gap between how humans would like to access images versus their typical representation is the goal of image parsing, which involves assigning object and attribute labels to pixels. In this article we propose treating nouns as object labels and adjectives as visual attribute labels. This allows us to formulate the image parsing problem as one of jointly estimating per-pixel object and attribute labels from a set of training images. We propose an efficient (interactive time) solution. Using the extracted …
Web Application Vulnerability Prediction Using Hybrid Program Analysis And Machine Learning, Lwin Khin Shar, Lionel Briand, Hee Beng Kuan Tan
Web Application Vulnerability Prediction Using Hybrid Program Analysis And Machine Learning, Lwin Khin Shar, Lionel Briand, Hee Beng Kuan Tan
Research Collection School Of Computing and Information Systems
Due to limited time and resources, web software engineers need support in identifying vulnerable code. A practical approach to predicting vulnerable code would enable them to prioritize security auditing efforts. In this paper, we propose using a set of hybrid (staticþdynamic) code attributes that characterize input validation and input sanitization code patterns and are expected to be significant indicators of web application vulnerabilities. Because static and dynamic program analyses complement each other, both techniques are used to extract the proposed attributes in an accurate and scalable way. Current vulnerability prediction techniques rely on the availability of data labeled with vulnerability …
Stopwatch: A Cloud Architecture For Timing Channel Mitigation, Peng Li, Debin Gao, Michael K Reiter
Stopwatch: A Cloud Architecture For Timing Channel Mitigation, Peng Li, Debin Gao, Michael K Reiter
Research Collection School Of Computing and Information Systems
This article presents StopWatch, a system that defends against timing-based side-channel attacks that arise from coresidency of victims and attackers in infrastructure-as-a-service clouds. StopWatch triplicates each cloud-resident guest virtual machine (VM) and places replicas so that the three replicas of a guest VM are coresident with nonoverlapping sets of (replicas of) other VMs. StopWatch uses the timing of I/O events at a VM’s replicas collectively to determine the timings observed by each one or by an external observer, so that observable timing behaviors are similarly likely in the absence of any other individual, coresident VMs. We detail the design and …
Cama: Efficient Modeling Of The Capture Effect For Low Power Wireless Networks, Behnam Dezfouli, Marjan Radi, Kamin Whitehouse, Shukor Abd Razak, Hwee-Pink Tan
Cama: Efficient Modeling Of The Capture Effect For Low Power Wireless Networks, Behnam Dezfouli, Marjan Radi, Kamin Whitehouse, Shukor Abd Razak, Hwee-Pink Tan
Research Collection School Of Computing and Information Systems
Network simulation is an essential tool for the design and evaluation of wireless network protocols, and realistic channel modeling is essential for meaningful analysis. Recently, several network protocols have demonstrated substantial network performance improvements by exploiting the capture effect, but existing models of the capture effect are still not adequate for protocol simulation and analysis. Physical-level models that calculate the signal-to-interference-plus-noise ratio (SINR) for every incoming bit are too slow to be used for large-scale or long-term networking experiments, and link-level models such as those currently used by the NS2 simulator do not accurately predict protocol performance. In this article, …
Partisan Sharing: Facebook Evidence And Societal Consequences, Jisun An, Daniele Quercia, Jon Crowcroft
Partisan Sharing: Facebook Evidence And Societal Consequences, Jisun An, Daniele Quercia, Jon Crowcroft
Research Collection School Of Computing and Information Systems
The hypothesis of selective exposure assumes that people seek out information that supports their views and eschew information that conflicts with their beliefs, and that has negative consequences on our society. Few researchers have recently found counter evidence of selective exposure in social media: users are exposed to politically diverse articles. No work has looked at what happens after exposure, particularly how individuals react to such exposure, though. Users might well be exposed to diverse articles but share only the partisan ones. To test this, we study partisan sharing on Facebook: the tendency for users to predominantly share like-minded news …
Designing An Immersive And Entertaining Pervasive Gameplay Experience With Spheros As Game And Interface Elements, Brennan Jones, Kody Dillman, Setareh Aghel Manesh, Ehud Sharlin, Anthony Tang
Designing An Immersive And Entertaining Pervasive Gameplay Experience With Spheros As Game And Interface Elements, Brennan Jones, Kody Dillman, Setareh Aghel Manesh, Ehud Sharlin, Anthony Tang
Research Collection School Of Computing and Information Systems
The Sphero is a robotic remote-controlled ball capable of rolling around on its own in any direction at multiple speeds. Numerous games have been designed for the Sphero for smartphones and tablets. However, most of these games provide an interface for controlling the Sphero that is far from natural. These games also do not put a strong focus on the physical environment around the Sphero. This work discusses a control scheme used to control a Sphero with another Sphero, and a pervasive game leveraging this scheme that emphasizes physical properties of the environment to create an immersive experience.
Entity Linking On Microblogs With Spatial And Temporal Signals, Yuan Fang, Ming-Wei Chang
Entity Linking On Microblogs With Spatial And Temporal Signals, Yuan Fang, Ming-Wei Chang
Research Collection School Of Computing and Information Systems
Microblogs present an excellent opportunity for monitoring and analyzing world happenings. Given that words are often ambiguous, entity linking becomes a crucial step towards understanding microblogs. In this paper, we re-examine the problem of entity linking on microblogs. We first observe that spatiotemporal (i.e., spatial and temporal) signals play a key role, but they are not utilized in existing approaches. Thus, we propose a novel entity linking framework that incorporates spatiotemporal signals through a weakly supervised process. Using entity annotations1 on real-world data, our experiments show that the spatiotemporal model improves F1 by more than 10 points over existing systems. …
Survey On Wakeup Scheduling For Environmentally-Powered Wireless Sensor Networks, Alvin Cerdena Valera, Wee-Seng Soh, Hwee-Pink Tan
Survey On Wakeup Scheduling For Environmentally-Powered Wireless Sensor Networks, Alvin Cerdena Valera, Wee-Seng Soh, Hwee-Pink Tan
Research Collection School Of Computing and Information Systems
Advances in energy harvesting technologies and ultra low-power computing and communication devices are enabling the realization of environmentally-powered wireless sensor networks (EPWSNs). Because of limited and dynamic energy supply, EPWSNs are duty-cycled to achieve energy-neutrality, a condition where the energy demand does not exceed the energy supply. Duty cycling entails nodes to sleep and wakeup according to a wakeup scheduling scheme. In this paper, we survey the various wakeup scheduling schemes, with focus on their suitability for EPWSNs. A classification scheme is proposed to characterize existing wakeup scheduling schemes, with three main categories, namely, asynchronous, synchronous, and …
Dynamic Inference Of Change Contracts, Tien-Duy B. Le, Jooyong Yi, David Lo, Ferdian Thung, Abhik Roychoudhury
Dynamic Inference Of Change Contracts, Tien-Duy B. Le, Jooyong Yi, David Lo, Ferdian Thung, Abhik Roychoudhury
Research Collection School Of Computing and Information Systems
Software evolves and thus developers frequently make changes to systems that are logged in version control systems. These changes are often poorly documented -- often commit logs are empty or only contain minimal information. Thus, it is often a challenge to understand why certain changes are made especially if they were introduced many months or even years ago. Understanding these changes is important when pertinent questions are raised during future bug fixing or software evolution efforts. Thus, there is a need for an automated approach that can help developers better document changes with little or minimal effort. To address this …
Competition Between Software-As-A-Service Vendors, Dan Ma, Robert John Kauffman
Competition Between Software-As-A-Service Vendors, Dan Ma, Robert John Kauffman
Research Collection School Of Computing and Information Systems
We propose a model of software-as-a-service (SaaS) in a competitive marketplace that brings clarity to the choices that competing vendors must make for pricing and quality strategy. We focus on several features of SaaS competition, including differences in vendor offerings, incomplete information on application functionality, the potential lock-in risk of SaaS clients, and their cost of learning about what it will take to make the vendors’ software work well. Clients can sample the fit costs of adoption, but can switch to another vendor. We obtained several findings through the use of a game-theoretic model. First, a client’s switching cost is …
Strategic Sourcing In The Presence Of Uncertain Supply And Retail Competition, Jianqing Chen, Zhiling Guo
Strategic Sourcing In The Presence Of Uncertain Supply And Retail Competition, Jianqing Chen, Zhiling Guo
Research Collection School Of Computing and Information Systems
This paper develops an analytical model to evaluate competing retail firms’ sourcing strategies in the presence of supply uncertainty. We consider a common supplier that sells its uncertain supply to two downstream retail firms engaging in price competition in a horizontally differentiated product market. The focal firm has a dual-sourcing option, while the rival firm can only source from the common supplier. We assess the system-wide effects of supply uncertainty on the focal firm's incentive to pursue the dual-sourcing strategy. We find that the focal firm's dual-sourcing strategy can create a win-win situation that leads to increased retail prices and …
Hippi Care Hospital: Towards Proactive Business Processes In Emergency Room Services, Kar Way Tan, Venky Shankaraman
Hippi Care Hospital: Towards Proactive Business Processes In Emergency Room Services, Kar Way Tan, Venky Shankaraman
Research Collection School Of Computing and Information Systems
It was 2.35 am on a Saturday morning. Wiki Lim, process specialist from the Process Innovation Centre (PIC) of Hippi Care Hospital (HCH), desperately doodling on her notepad for ideas to improve service delivery at HCH’s Emergency Department (ED). HCH has committed to the public that its ED would meet the service quality criterion of serving 90% of A3 and A4 patients, non-emergency patients with moderate to mild symptoms, within 90 minutes of their arrival at the ED. The ED was not able to meet this performance goal and Dr. Edward Kim, the head of the ED at HCH, had …
Action Classification By Exploring Directional Co-Occurrence Of Weighted Stips, Mengyuan Liu, Hong Liu, Qianru Sun
Action Classification By Exploring Directional Co-Occurrence Of Weighted Stips, Mengyuan Liu, Hong Liu, Qianru Sun
Research Collection School Of Computing and Information Systems
Human action recognition is challenging mainly due to intro-variety, inter-ambiguity and clutter backgrounds in real videos. Bag-of-visual words model utilizes spatio-temporal interest points(STIPs), and represents action by the distribution of points which ignores visual context among points. To add more contextual information, we propose a method by encoding spatio-temporal distribution of weighted pairwise points. First, STIPs are extracted from an action sequence and clustered into visual words. Then, each word is weighted in both temporal and spatial domains to capture the relationships with other words. Finally, the directional relationships between co-occurrence pairwise words are used to encode visual contexts. We …
Multi-Agent Orienteering Problem With Time-Dependent Capacity Constraints, Cen Chen, Shih-Fen Cheng, Hoong Chuin Lau
Multi-Agent Orienteering Problem With Time-Dependent Capacity Constraints, Cen Chen, Shih-Fen Cheng, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
In this paper, we formulate and study the Multi-agent Orienteering Problem with Time-dependent Capacity Constraints (MOPTCC). MOPTCC is similar to the classical orienteering problem at single-agent level: given a limited time budget, an agent travels around the network and collects rewards by visiting different nodes, with the objective of maximizing the sum of his collected rewards. The most important feature we introduce in MOPTCC is the inclusion of multiple competing agents. All agents in MOPTCC are assumed to be self-interested, and they interact with each other when arrive at certain nodes simultaneously. As all nodes are capacitated, if a particular …
A Multi-Dimensional Image Quality Prediction Model For User-Generated Images In Social Networks, You Yang, Xu Wang, Tao Guan, Jialie Shen, Li Yu
A Multi-Dimensional Image Quality Prediction Model For User-Generated Images In Social Networks, You Yang, Xu Wang, Tao Guan, Jialie Shen, Li Yu
Research Collection School Of Computing and Information Systems
User-generated images (UGIs) are currently proliferating within social networks. These images contain multi-dimensional data, including the image itself, text and the social links of the owner. UGIs can be utilized for self-presentation, news dissemination and other purposes, and the quality of the image should be able to reveal these social functionalities. However, it is challenging to predict UGI quality utilizing existing models, such as image quality assessment, recommender systems or others, because these models have difficulties processing multi-dimensional data simultaneously. To address this problem, we propose a multi-dimensional image quality prediction model for UGIs in social networks. In this model, …
Auction With Rolling Horizon For Urban Consolidation Centre, Chen Wang, Stephanus Daniel Handoko, Hoong Chuin Lau
Auction With Rolling Horizon For Urban Consolidation Centre, Chen Wang, Stephanus Daniel Handoko, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
A number of cities around the world have adopted urban consolidation centres (UCCs) to address some challenges of their last-mile deliveries. At the UCC, goods are consolidated based on their destinations prior to their deliveries into the city centre. In many examples, the UCC owns a fleet of eco-friendly vehicles to carry out the deliveries. A carrier/shipper who buys the UCC’s service hence no longer needs to enter the city centre in which time-window and vehicle-type restrictions may apply. As a result, it becomes possible to retain the use of large trucks for the economies of scale outside the city …
Cost-Sensitive Online Classification, Jialei Wang, Peilin Zhao, Steven C. H. Hoi
Cost-Sensitive Online Classification, Jialei Wang, Peilin Zhao, Steven C. H. Hoi
Research Collection School Of Computing and Information Systems
Both cost-sensitive classification and online learning have been extensively studied in data mining and machine learning communities, respectively. However, very limited study addresses an important intersecting problem, that is, “Cost-Sensitive Online Classification". In this paper, we formally study this problem, and propose a new framework for Cost-Sensitive Online Classification by directly optimizing cost-sensitive measures using online gradient descent techniques. Specifically, we propose two novel cost-sensitive online classification algorithms, which are designed to directly optimize two well-known cost-sensitive measures: (i) maximization of weighted sum of sensitivity and specificity, and (ii) minimization of weighted misclassification cost. We analyze the theoretical bounds of …
Distributed Event Detection In Sensor Networks Under Random Spatial Deployment, P. Zhang, G. Peters, I. Nevat, G. Xiao, Hwee-Pink Tan
Distributed Event Detection In Sensor Networks Under Random Spatial Deployment, P. Zhang, G. Peters, I. Nevat, G. Xiao, Hwee-Pink Tan
Research Collection School Of Computing and Information Systems
We present a novel event detection algorithm in sensor networks for the case where the sensors are randomly deployed in space. In particular we consider a random sensors deployment according to a Homogeneous Finite Binomial Point Process. We first derive the optimal event detection decision rule. We then develop a novel algorithm to evaluate the intractable marginal likelihood based on the Gram-Charlier series expansion. We evaluate our algorithms through extensive Monte Carlo simulations. Simulation results present the detection and false alarm rates for different system parameters such as number of sensors deployed, deployment region size etc.
Analyzing The Dangers Posed By Chrome Extensions, Lujo Bauer, Shaoying Cai, Limin Jia, Timothy Passaro, Yuan Tian
Analyzing The Dangers Posed By Chrome Extensions, Lujo Bauer, Shaoying Cai, Limin Jia, Timothy Passaro, Yuan Tian
Research Collection School Of Computing and Information Systems
A common characteristic of modern web browsers is that their functionality can be extended via third-party addons. In this paper we focus on Chrome extensions, to which the Chrome browser exports a rich API: extensions can potentially make network requests, access the local file system, get low-level information about running processes, etc. To guard against misuse, Chrome uses a permission system to curtail an extension's privileges. We demonstrate a series of attacks by which extensions can steal data, track user behavior, and collude to elevate their privileges. Although some attacks have previously been reported, we show that subtler versions can …