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Articles 6061 - 6090 of 9024
Full-Text Articles in Computer Sciences
Risk Based Optimization For Improving Emergency Medical Systems, Sandhya Saisubramanian, Pradeep Varakantham, Hoong Chuin Lau
Risk Based Optimization For Improving Emergency Medical Systems, Sandhya Saisubramanian, Pradeep Varakantham, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
In emergency medical systems, arriving at the incident location a few seconds early can save a human life. Thus, this paper is motivated by the need to reduce the response time – time taken to arrive at the incident location after receiving the emergency call – of Emergency Response Vehicles, ERVs (ex: ambulances, fire rescue vehicles) for as many requests as possible. We expect to achieve this primarily by positioning the "right" number of ERVs at the "right" places and at the "right" times. Given the exponentially large action space (with respect to number of ERVs and their placement) and …
Designing A Portfolio Of Parameter Configurations For Online Algorithm Selection, Aldy Gunawan, Hoong Chuin Lau, Mustafa Misir
Designing A Portfolio Of Parameter Configurations For Online Algorithm Selection, Aldy Gunawan, Hoong Chuin Lau, Mustafa Misir
Research Collection School Of Computing and Information Systems
Algorithm portfolios seek to determine an effective set of algorithms that can be used within an algorithm selection framework to solve problems. A limited number of these portfolio studies focus on generating different versions of a target algorithm using different parameter configurations. In this paper, we employ a Design of Experiments (DOE) approach to determine a promising range of values for each parameter of an algorithm. These ranges are further processed to determine a portfolio of parameter configurations, which would be used within two online Algorithm Selection approaches for solving different instances of a given combinatorial optimization problem effectively. We …
Algorithm Selection Via Ranking, Jayadi Oentaryo Richard, Handoko Stephanus Daniel, Hoong Chuin Lau
Algorithm Selection Via Ranking, Jayadi Oentaryo Richard, Handoko Stephanus Daniel, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
The abundance of algorithms developed to solve different problems has given rise to an important research question: How do we choose the best algorithm for a given problem? Known as algorithm selection, this issue has been prevailing in many domains, as no single algorithm can perform best on all problem instances. Traditional algorithm selection and portfolio construction methods typically treat the problem as a classification or regression task. In this paper, we present a new approach that provides a more natural treatment of algorithm selection and portfolio construction as a ranking task. Accordingly, we develop a Ranking-Based Algorithm Selection (RAS) …
Solving Uncertain Mdps With Objectives That Are Separable Over Instantiations Of Model Uncertainty, Yossiri Adulyasak, Pradeep Varakantham, Asrar Ahmed, Patrick Jaillet
Solving Uncertain Mdps With Objectives That Are Separable Over Instantiations Of Model Uncertainty, Yossiri Adulyasak, Pradeep Varakantham, Asrar Ahmed, Patrick Jaillet
Research Collection School Of Computing and Information Systems
Markov Decision Problems, MDPs offer an effective mechanism for planning under uncertainty. However, due to unavoidable uncertainty over models, it is difficult to obtain an exact specification of an MDP. We are interested in solving MDPs, where transition and reward functions are not exactly specified. Existing research has primarily focussed on computing infinite horizon stationary policies when optimizing robustness, regret and percentile based objectives. We focus specifically on finite horizon problems with a special emphasis on objectives that are separable over individual instantiations of model uncertainty (i.e., objectives that can be expressed as a sum over instantiations of model uncertainty): …
Semi-Universal Portfolios With Transaction Costs, Dingjiang Huang, Yan Zhu, Bin Li, Shuigeng Zhou, Steven C. H. Hoi
Semi-Universal Portfolios With Transaction Costs, Dingjiang Huang, Yan Zhu, Bin Li, Shuigeng Zhou, Steven C. H. Hoi
Research Collection School Of Computing and Information Systems
Online portfolio selection (PS) has been extensively studied in artificial intelligence and machine learning communities in recent years. An important practical issue of online PS is transaction cost, which is unavoidable and nontrivial in real financial trading markets. Most existing strategies, such as universal portfolio (UP) based strategies, often rebalance their target portfolio vectors at every investment period, and thus the total transaction cost increases rapidly and the final cumulative wealth degrades severely. To overcome the limitation, in this paper we investigate new investment strategies that rebalances its portfolio only at some selected instants. Specifically, we design a novel on-line …
Improving Software Quality And Productivity Leveraging Mining Techniques: [Summary Of The Second Workshop On Software Mining, At Ase 2013], Ming Li, Hongyu Zhang, David Lo, Lucia Lucia
Improving Software Quality And Productivity Leveraging Mining Techniques: [Summary Of The Second Workshop On Software Mining, At Ase 2013], Ming Li, Hongyu Zhang, David Lo, Lucia Lucia
Research Collection School Of Computing and Information Systems
The second International Workshop on Software Mining (Soft-mine) was held on the 11th of November 2013. The workshop was held in conjunction with the 28th IEEE/ACM International Conference on Automated Software Engineering (ASE) in Silicon Valley, California, USA. The workshop has facilitated researchers who are interested in mining various types of software-related data and in applying data mining techniques to support software engineering tasks. During the workshop, seven papers on software mining and behavior models, execution trace mining, and bug localization and fixing were presented. One of the papers received the best paper award. Furthermore, there were two invited talk …
Are Features Equally Representative? A Feature-Centric Recommendation, Chenyi Zhang, Ke Wang, Ee-Peng Lim, Qinneng Xu, Jianling Sun, Hongkun Yu
Are Features Equally Representative? A Feature-Centric Recommendation, Chenyi Zhang, Ke Wang, Ee-Peng Lim, Qinneng Xu, Jianling Sun, Hongkun Yu
Research Collection School Of Computing and Information Systems
Typically a user prefers an item (e.g., a movie) because she likes certain features of the item (e.g., director, genre, producer). This observation motivates us to consider a feature-centric recommendation approach to item recommendation: instead of directly predicting the rating on items, we predict the rating on the features of items, and use such ratings to derive the rating on an item. This approach offers several advantages over the traditional item-centric approach: it incorporates more information about why a user chooses an item, it generalizes better due to the denser feature rating data, it explains the prediction of item ratings …
A Systematic Study On Explicit-State Non-Zenoness Checking For Timed Automata, Ting Wang, Jun Sun, Xinyu Wang, Yang Liu, Yuanjie Si, Jin Song Dong, Xiaohu Yang, Xiaohong Li
A Systematic Study On Explicit-State Non-Zenoness Checking For Timed Automata, Ting Wang, Jun Sun, Xinyu Wang, Yang Liu, Yuanjie Si, Jin Song Dong, Xiaohu Yang, Xiaohong Li
Research Collection School Of Computing and Information Systems
Zeno runs, where infinitely many actions occur within finite time, may arise in Timed Automata models. Zeno runs are not feasible in reality and must be pruned during system verification. Thus it is necessary to check whether a run is Zeno or not so as to avoid presenting Zeno runs as counterexamples during model checking. Existing approaches on non-Zenoness checking include either introducing an additional clock in the Timed Automata models or additional accepting states in the zone graphs. In addition, there are approaches proposed for alternative timed modeling languages, which could be generalized to Timed Automata. In this work, …
Ambiguous Optimistic Fair Exchange: Definition And Constructions, Qiong Huang, Guomin Yang, Duncan S. Wong, Willy Susilo
Ambiguous Optimistic Fair Exchange: Definition And Constructions, Qiong Huang, Guomin Yang, Duncan S. Wong, Willy Susilo
Research Collection School Of Computing and Information Systems
Optimistic fair exchange (OFE) is a protocol for solving the problem of exchanging items or services in a fair manner between two parties, a signer and a verifier, with the help of an arbitrator which is called in only when a dispute happens between the two parties. In almost all the previous work on OFE, after obtaining a partial signature from the signer, the verifier can present it to others and show that the signer has indeed committed itself to something corresponding to the partial signature even prior to the completion of the transaction. In some scenarios, this capability given …
Modeling Neuromorphic Persistent Firing Networks, Ning Ning, Guoqi Li, Wei He, Kejie Huang, Li Pan, Kiruthika Ramanathan, Rong Zhao, Luping Shi
Modeling Neuromorphic Persistent Firing Networks, Ning Ning, Guoqi Li, Wei He, Kejie Huang, Li Pan, Kiruthika Ramanathan, Rong Zhao, Luping Shi
Research Collection School Of Computing and Information Systems
Neurons are believed to be the brain computational engines of the brain. A recent discovery in neurophysiology reveals that interneurons can slowly integrate spiking, share the output across a coupled network of axons and respond with persistent firing even in the absence of input to the soma or dendrites, which has not been understood and could be very important for exploring the mechanism of human cognition. The conventional models are incapable of simulating the important newly-discovered phenomenon of persistent firing induced by axonal slow integration. In this paper, we propose a computationally efficient model of neurons through modeling the axon …
Ciphercard: A Token-Based Approach Against Camera-Based Shoulder Surfing Attacks On Common Touchscreen Devices, Teddy Seyed, Xing-Dong Yang, Anthony Tang, Saul Greenberg, Jiawei Gu, Bin Zhu, Xiang Ciao
Ciphercard: A Token-Based Approach Against Camera-Based Shoulder Surfing Attacks On Common Touchscreen Devices, Teddy Seyed, Xing-Dong Yang, Anthony Tang, Saul Greenberg, Jiawei Gu, Bin Zhu, Xiang Ciao
Research Collection School Of Computing and Information Systems
We present CipherCard, a physical token that defends against shoulder-surfing attacks on user authentication on capacitive touchscreen devices. When CipherCard is placed over a touchscreen’s pin-pad, it remaps a user’s touch point on the physical token to a different location on the pin-pad. It hence translates a visible user password into a different system password received by a touchscreen, but is hidden from observers as well as the user. CipherCard enhances authentication security through Two-Factor Authentication (TFA), in that both the correct user password and a specific card are needed for successful authentication. We explore the design space of CipherCard, …
Toward Mobile Robots Reasoning Like Humans, Jean Oh, Arne Suppe, Felix Duvallet, Abdeslam Boularias, Luis Navarro-Serment, Martial Hebert, Anthony Stentz, Jerry Vinokurov, Oscar Romero, Christian Lebiere, Robert Dean
Toward Mobile Robots Reasoning Like Humans, Jean Oh, Arne Suppe, Felix Duvallet, Abdeslam Boularias, Luis Navarro-Serment, Martial Hebert, Anthony Stentz, Jerry Vinokurov, Oscar Romero, Christian Lebiere, Robert Dean
Research Collection School Of Computing and Information Systems
Robots are increasingly becoming key players in human-robot teams. To become effective teammates, robots must possess profound understanding of an environment, be able to reason about the desired commands and goals within a specific context, and be able to communicate with human teammates in a clear and natural way. To address these challenges, we have developed an intelligence architecture that combines cognitive components to carry out high-level cognitive tasks, semantic perception to label regions in the world, and a natural language component to reason about the command and its relationship to the objects in the world. This paper describes recent …
Integrated Intelligence For Human-Robot Teams, Jean Oh, Et. Al.
Integrated Intelligence For Human-Robot Teams, Jean Oh, Et. Al.
Research Collection School Of Computing and Information Systems
With recent advances in robotics technologies and autonomous systems, the idea of human-robot teams is gaining ever-increasing attention. In this context, our research focuses on developing an intelligent robot that can autonomously perform non-trivial, but specific tasks conveyed through natural language. Toward this goal, a consortium of researchers develop and integrate various types of intelligence into mobile robot platforms, including cognitive abilities to reason about high-level missions, perception to classify regions and detect relevant objects in an environment, and linguistic abilities to associate instructions with the robot’s world model and to communicate with human teammates in a natural way. This …
Saliency-Guided Color-To-Gray Conversion Using Region-Based Optimization, Hao Du, Shengfeng He, Bin Sheng, Lizhuang Ma, Rynson W.H. Lau
Saliency-Guided Color-To-Gray Conversion Using Region-Based Optimization, Hao Du, Shengfeng He, Bin Sheng, Lizhuang Ma, Rynson W.H. Lau
Research Collection School Of Computing and Information Systems
Image decolorization is a fundamental problem for many real-world applications, including monochrome printing and photograph rendering. In this paper, we propose a new color-to-gray conversion method that is based on a region-based saliency model. First, we construct a parametric color-to-gray mapping function based on global color information as well as local contrast. Second, we propose a region-based saliency model that computes visual contrast among pixel regions. Third, we minimize the salience difference between the original color image and the output grayscale image in order to preserve contrast discrimination. To evaluate the performance of the proposed method in preserving contrast in …
Human Action Classification Based On Sequential Bag-Of-Words Model, Hong Liu, Qiaoduo Zhang, Qianru Sun
Human Action Classification Based On Sequential Bag-Of-Words Model, Hong Liu, Qiaoduo Zhang, Qianru Sun
Research Collection School Of Computing and Information Systems
Recently, approaches utilizing spatial-temporal features have achieved great success in human action classification. However, they typically rely on bag-of-words (BoWs) model, and ignore the spatial and temporal structure information of visual words, bringing ambiguities among similar actions. In this paper, we present a novel approach called sequential BoWs for efficient human action classification. It captures temporal sequential structure by segmenting the entire action into sub-actions. Each sub-action has a tiny movement within a narrow range of action. Then the sequential BoWs are created, in which each sub-action is assigned with a certain weight and salience to highlight the distinguishing sections. …
Online Learning On Incremental Distance Metric For Person Re-Identification, Yuke Sun, Hong Liu, Qianru Sun
Online Learning On Incremental Distance Metric For Person Re-Identification, Yuke Sun, Hong Liu, Qianru Sun
Research Collection School Of Computing and Information Systems
Person re-identification is to match persons appearing across non-overlapping cameras. The matching is challenging due to visual ambiguities and disparities of human bodies. Most previous distance metrics are learned by off-line and supervised approaches. However, they are not practical in real-world applications in which online data comes in without any label. In this paper, a novel online learning approach on incremental distance metric, OL-IDM, is proposed. The approach firstly modifies Self-Organizing Incremental Neural Network (SOINN) using Mahalanobis distance metric to cluster incoming data into neural nodes. Such metric maximizes the likelihood of a true image pair matches with a smaller …
Data Preparation For Social Network Mining And Analysis, Yazhe Wang
Data Preparation For Social Network Mining And Analysis, Yazhe Wang
Dissertations and Theses Collection (Open Access)
This dissertation studies the problem of preparing good-quality social network data for data analysis and mining. Modern online social networks such as Twitter, Facebook, and LinkedIn have rapidly grown in popularity. The consequent availability of a wealth of social network data provides an unprecedented opportunity for data analysis and mining researchers to determine useful and actionable information in a wide variety of fields such as social sciences, marketing, management, and security. However, raw social network data are vast, noisy, distributed, and sensitive in nature, which challenge data mining and analysis tasks in storage, efficiency, accuracy, etc. Many mining algorithms cannot …
Issues Of Social Data Analytics With A New Method For Sentiment Analysis Of Social Media Data, Zhaoxia Wang, Victor J. C. Tong, David Chan
Issues Of Social Data Analytics With A New Method For Sentiment Analysis Of Social Media Data, Zhaoxia Wang, Victor J. C. Tong, David Chan
Research Collection School of Social Sciences
Social media data consists of feedback, critiques and other comments that are posted online by internet users. Collectively, these comments may reflect sentiments that are sometimes not captured in traditional data collection methods such as administering a survey questionnaire. Thus, social media data offers a rich source of information, which can be adequately analyzed and understood. In this paper, we survey the extant research literature on sentiment analysis and discuss various limitations of the existing analytical methods. A major limitation in the large majority of existing research is the exclusive focus on social media data in the English language. There …
An Empirical Study On The Adequacy Of Testing In Open Source Projects, Pavneet Singh Kochhar, Ferdian Thung, David Lo, Julia Lawall
An Empirical Study On The Adequacy Of Testing In Open Source Projects, Pavneet Singh Kochhar, Ferdian Thung, David Lo, Julia Lawall
Research Collection School Of Computing and Information Systems
During software maintenance, testing is crucial to ensure the quality of code as it evolves. With the increasing size and complexity of software, adequate software testing has become increasingly important. Code coverage is an important metric to gauge the effectiveness of test cases and the adequacy of testing. However, what is the coverage level exhibited by large-scale open-source projects? What is the correlation between software metrics and the code coverage of the software?In this study, we investigate the state-of-the-practice of testing by measuring code coverage in open-source software projects. We examine over300 large open-source projects written in Java, coming from …
Orchestrating Service Innovation Using Design Moves: The Dynamics Of Fit Between Service And Enterprise It Architectures, Narayan Ramasubbu, Charles Jason Woodard, Sunil Mithas
Orchestrating Service Innovation Using Design Moves: The Dynamics Of Fit Between Service And Enterprise It Architectures, Narayan Ramasubbu, Charles Jason Woodard, Sunil Mithas
Research Collection School Of Computing and Information Systems
Service science perspectives highlight the central role of information technology (IT) in transforming the design and delivery of services. To discern the mechanisms through which IT impacts service innovation, we explore the dynamics of the relationship between enterprise IT and service architectures, and how these dynamics influence the performance of service innovation projects. We conducted six case studies to investigate how firms orchestrated service innovation, focusing on the design of the service architecture and its relationship to enterprise systems. We synthesize the case findings to develop a set of propositions on the antecedents and consequences of fit (or misfit) between …
Platform Pricing With Endogenous Network Effects, Mei Lin, Ruhai Wu, Wen Zhou
Platform Pricing With Endogenous Network Effects, Mei Lin, Ruhai Wu, Wen Zhou
Research Collection School Of Computing and Information Systems
This paper examines a monopoly platform’s two-sided pricing strategy through modeling the trades between the participating sellers and buyers. In this approach, the network effects emerge endogenously through the equilibrium trading strategies of the two sides. We show that platform pricing depends crucially on the characteristics associated with market liquidity, including both sides’ entry costs, the buyers’ preferences, and the distribution of the sellers’ quality. The platform may subsidize sellers if the market is sufficiently liquid, whereas buyer subsidy can be optimal given an illiquid market. We also illustrate the impact of the sellers’ quality heterogeneity on the platform’s optimal …
Modeling The Evolution Of Generativity And The Emergence Of Digital Ecosystems, C. Jason Woodard, Eric K. Clemons
Modeling The Evolution Of Generativity And The Emergence Of Digital Ecosystems, C. Jason Woodard, Eric K. Clemons
Research Collection School Of Computing and Information Systems
Recent literature on sociotechnical systems has employed the concept of generativity to explain the remarkable capacity for digital artifacts to support decentralized innovation and the emergence of rich business ecosystems. In this paper, we propose agent-based computational modeling as a tool for studying the evolution of generativity, and offer a set of building blocks for constructing agent-based models in which generativity evolves. We describe a series of models that we have created using these building blocks, and summarize the results of our computational experiments to date. We find in several different settings that key features of generative systems can themselves …
Measuring Student Performance And Providing Feedback Using Competency Framework, Joelle Elmaleh, Venky Shankararaman
Measuring Student Performance And Providing Feedback Using Competency Framework, Joelle Elmaleh, Venky Shankararaman
Research Collection School Of Computing and Information Systems
A number of Computer Science and Information Systems programs have effectively defined learning outcomes, course level competencies, and conducted assessments at the program level to determine areas for continuous improvement. However, many of these programs do not fully leverage the course competencies during the actual delivery and assessment of the course. This paper presents how course competencies can be used to effectively deliver and assess the course content, and give valuable timely feedback to the students. Using a large first year core course of the BSc (Information Systems Management) program (called Object Oriented Application Development course-OOAD) as an example, this …
Cardioguard: A Brassiere-Based Reliable Ecg Monitoring Sensor System For Supporting Daily Smartphone Healthcare Applications, Sungjun Kwon, Jeehoon Kim, Seungwoo Kang, Youngki Lee, Hyunjae Baek, Kwangsuk Park
Cardioguard: A Brassiere-Based Reliable Ecg Monitoring Sensor System For Supporting Daily Smartphone Healthcare Applications, Sungjun Kwon, Jeehoon Kim, Seungwoo Kang, Youngki Lee, Hyunjae Baek, Kwangsuk Park
Research Collection School Of Computing and Information Systems
We propose CardioGuard, a brassiere-based reliable electrocardiogram (ECG) monitoring sensor system, for supporting daily smartphone healthcare applications. It is designed to satisfy two key requirements for user-unobtrusive daily ECG monitoring: reliability of ECG sensing and usability of the sensor. The system is validated through extensive evaluations. The evaluation results showed that the CardioGuard sensor reliably measure the ECG during 12 representative daily activities including diverse movement levels; 89.53% of QRS peaks were detected on average. The questionnaire-based user study with 15 participants showed that the CardioGuard sensor was comfortable and unobtrusive. Additionally, the signal-to-noise ratio test and the washing durability …
A Metrics Suite Of Cloud Computing Adoption Readiness, Robert J. Kauffman, Dan Ma, Martin Yu
A Metrics Suite Of Cloud Computing Adoption Readiness, Robert J. Kauffman, Dan Ma, Martin Yu
Research Collection School Of Computing and Information Systems
Recent research on cloud computing adoption indicates that there has been a lack of deep understanding of its benefits by managers and organizations. This has been an obstacle for adoption. We report on an initial design for a firm-level cloud computing readiness metrics suite. We propose categories and measures to form a set of metrics to measure adoption readiness and assess the required adjustments in strategy and management, technology and operations, and business policies. We reviewed the relevant interdisciplinary literature and interviewed industry professionals to ground our metrics based on theory and practice knowledge. We identified four relevant categories for …
Probabilistic Latent Document Network Embedding, Tuan M. V. Le, Hady W. Lauw
Probabilistic Latent Document Network Embedding, Tuan M. V. Le, Hady W. Lauw
Research Collection School Of Computing and Information Systems
A document network refers to a data type that can be represented as a graph of vertices, where each vertex is associated with a text document. Examples of such a data type include hyperlinked Web pages, academic publications with citations, and user profiles in social networks. Such data have very high-dimensional representations, in terms of text as well as network connectivity. In this paper, we study the problem of embedding, or finding a low-dimensional representation of a document network that "preserves" the data as much as possible. These embedded representations are useful for various applications driven by dimensionality reduction, such …
Detecting Camouflaged Applications On Mobile Application Markets, Mon Kywe Su, Yingjiu Li, Huijie Robert Deng, Jason Hong
Detecting Camouflaged Applications On Mobile Application Markets, Mon Kywe Su, Yingjiu Li, Huijie Robert Deng, Jason Hong
Research Collection School Of Computing and Information Systems
Application plagiarism or application cloning is an emerging threat in mobile application markets. It reduces profits of original developers and sometimes even harms the security and privacy of users. In this paper, we introduce a new concept, called camouflaged applications, where external features of mobile applications, such as icons, screenshots, application names or descriptions, are copied. We then propose a scalable detection framework, which can find these suspiciously similar camouflaged applications. To accomplish this, we apply text-based retrieval methods and content-based image retrieval methods in our framework. Our framework is implemented and tested with 30,625 Android applications from the official …
Detecting Flow Anomalies In Distributed Systems, Freddy Chong-Tat Chua, Ee Peng Lim, Bernardo Huberman
Detecting Flow Anomalies In Distributed Systems, Freddy Chong-Tat Chua, Ee Peng Lim, Bernardo Huberman
Research Collection School Of Computing and Information Systems
Deep within the networks of distributed systems, one often finds anomalies that affect their efficiency and performance. These anomalies are difficult to detect because the distributed systems may not have sufficient sensors to monitor the flow of traffic within the interconnected nodes of the networks. Without early detection and making corrections, these anomalies may aggravate over time and could possibly cause disastrous outcomes in the system in the unforeseeable future. Using only coarse-grained information from the two end points of network flows, we propose a network transmission model and a localization algorithm, to detect the location of anomalies and rank …
Mydeal: A Mobile Shopping Assistant Matching User Preferences To Promotions, Kartik Muralidharan, Swapna Gottipati, Jing Jiang, Narayan Ramasubbu, Rajesh Krishna Balan
Mydeal: A Mobile Shopping Assistant Matching User Preferences To Promotions, Kartik Muralidharan, Swapna Gottipati, Jing Jiang, Narayan Ramasubbu, Rajesh Krishna Balan
Research Collection School Of Computing and Information Systems
A common problem in large urban cities is the huge number of retail options available. In response, a number of shopping assistance applications have been created for mobile phones. However, these applications mostly allow users to know where stores are or find promotions on specific items. What is missing is a system that factors in a user's shopping preferences and automatically tells them which stores are of their interest. The key challenge in this system is twofold; 1) building a matching algorithm that can combine user preferences with fairly unstructured deals and store information to generate a final rank ordered …
Android Or Ios For Better Privacy Protection?, Jin Han, Qiang Yan, Debin Gao, Jianying Zhou, Huijie Robert Deng
Android Or Ios For Better Privacy Protection?, Jin Han, Qiang Yan, Debin Gao, Jianying Zhou, Huijie Robert Deng
Research Collection School Of Computing and Information Systems
With the rapid growth of the mobile market, security of mobile platforms is receiving increasing attention from both research community as well as the public. In this paper, we make the first attempt to establish a baseline for security comparison between the two most popular mobile platforms. We investigate applications that run on both Android and iOS and examine the difference in the usage of their security sensitive APIs (SS-APIs). Our analysis over 2,600 applications shows that iOS applications consistently access more SS-APIs than their counterparts on Android. The additional privileges gained on iOS are often associated with accessing private …