Computer Sciences Commons^™

Engagemon: Multi-Modal Engagement Sensing For Mobile Games, Sinh Huynh, Seungmin Kim, Jeonggil Ko, Rajesh Krishna Balan, Youngki Lee

Research Collection School Of Computing and Information Systems

Understanding the engagement levels players have with a game is a useful proxy for evaluating the game design and user experience. This is particularly important for mobile games as an alternative game is always just an easy download away. However, engagement is a subjective concept and usually requires fine-grained highly disruptive interviews or surveys to determine accurately. In this paper, we present EngageMon, a first-of-its-kind system that uses a combination of sensors from the smartphone (touch events), a wristband (photoplethysmography and electrodermal activity sensor readings), and an external depth camera (skeletal motion information) to accurately determine the engagement level of …

An Lstm Model For Cloze-Style Machine Comprehension, Shuohang Wang, Jing Jiang

Research Collection School Of Computing and Information Systems

Machine comprehension is concerned with teaching machines to answer reading comprehension questions. In this paper we adopt an LSTM-based model we designed earlier for textual entailment and propose two new models for cloze-style machine comprehension. In our first model, we treat the document as a premise and the question as a hypothesis, and use an LSTM with attention mechanisms to match the question with the document. This LSTM remembers the best answer token found in the document while processing the question. Furthermore, we observe some special properties of machine comprehension and propose a two-layer LSTM model. In this model, we …

Sclib: A Practical And Lightweight Defense Against Component Hijacking In Android Applications, Daoyuan Wu, Yao Cheng, Debin Gao, Yingjiu Li, Robert H. Deng

Research Collection School Of Computing and Information Systems

Cross-app collaboration via inter-component communication is a fundamental mechanism on Android. Although it brings the benefits such as functionality reuse and data sharing, a threat called component hijacking is also introduced. By hijacking a vulnerable component in victim apps, an attack app can escalate its privilege for operations originally prohibited. Many prior studies have been performed to understand and mitigate this issue, but no defense is being deployed in the wild, largely due to the deployment difficulties and performance concerns. In this paper we present SCLib, a secure component library that performs in-app mandatory access control on behalf of app …

Mining Sandboxes: Are We There Yet?, Lingfeng Bao, Tien Duy B. Le, David Lo

Research Collection School Of Computing and Information Systems

The popularity of Android platform on mobile devices has attracted much attention from many developers and researchers, as well as malware writers. Recently, Jamrozik et al. proposed a technique to secure Android applications referred to as mining sandboxes. They used an automated test case generation technique to explore the behavior of the app under test and then extracted a set of sensitive APIs that were called. Based on the extracted sensitive APIs, they built a sandbox that can block access to APIs not used during testing. However, they only evaluated the proposed technique with benign apps but not investigated whether …

Urlnet: Learning A Url Representation With Deep Learning For Malicious Url Detection, Hung Le, Hong Quang Pham, Doyen Sahoo, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

Malicious URLs host unsolicited content and are used to perpetrate cybercrimes. It is imperative to detect them in a timely manner. Traditionally, this is done through the usage of blacklists, which cannot be exhaustive, and cannot detect newly generated malicious URLs. To address this, recent years have witnessed several efforts to perform Malicious URL Detection using Machine Learning. The most popular and scalable approaches use lexical properties of the URL string by extracting Bag-of-words like features, followed by applying machine learning models such as SVMs. There are also other features designed by experts to improve the prediction performance of the …

An Efficient And Expressive Ciphertext-Policy Attribute-Based Encryption Scheme With Partially Hidden Access Structures, Revisited, Hui Cui, Robert H. Deng, Junzuo Lai, Xun Yi, Surya Nepal

Research Collection School Of Computing and Information Systems

Ciphertext-policy attribute-based encryption (CP-ABE) has been regarded as one of the promising solutions to protect data security and privacy in cloud storage services. In a CP-ABE scheme, an access structure is included in the ciphertext, which, however, may leak sensitive information about the underlying plaintext and the privileged recipients in that anyone who sees the ciphertext is able to learn the attributes of the privileged recipients from the associated access structure. In order to address this issue, CP-ABE with partially hidden access structures was introduced where each attribute is divided into an attribute name and an attribute value and the …

A Model Of Competition Between Perpetual Software And Software As A Service, Zhiling Guo, Dan Ma

Research Collection School Of Computing and Information Systems

Duplicate record, see https://ink.library.smu.edu.sg/sis_research/3744/. Software as a service (SaaS) has grown to be a significant segment of many software product markets. SaaS vendors, which charge customers based on use and continuously improve the quality of their products, have put competitive pressure on traditional perpetual software vendors, which charge a licensing fee and periodically upgrade the quality of their software. We develop an analytical model to study the competitive pricing strategies of an incumbent perpetual software vendor in the presence of a SaaS competitor. We find that, depending on both the SaaS quality improvement rate and the network effect, the …

A Model Of Competition Between Perpetual Software And Software As A Service, Zhiling Guo, Dan Ma

Research Collection School Of Computing and Information Systems

Software as a service (SaaS) has grown to be a significant segment of many software product markets. SaaS vendors, which charge customers based on use and continuously improve the quality of their products, have put competitive pressure on traditional perpetual software vendors, which charge a licensing fee and periodically upgrade the quality of their software. We develop an analytical model to study the competitive pricing strategies of an incumbent perpetual software vendor in the presence of a SaaS competitor. We find that, depending on both the SaaS quality improvement rate and the network effect, the perpetual software vendor adopts one …

Multigeneration Product Diffusion In The Presence Of Strategic Consumers, Zhiling Guo, Jianqing Chen

Research Collection School Of Computing and Information Systems

Frequent new product releases pose significant challenges for firms as they manage successive generations of product diffusion. We develop an analytical model to study the effect of different purchase options by strategic consumers on a firm's profit and the firm's strategies for the timing and pricing of its successive generations of product diffusion. We show that consumers' strategic behavior, although adversely affecting the sales of the first-generation product, positively influences the sales of the second-generation product through an initial “seeding” effect. The influence of strategic consumers on profit and sales depends largely on the discount-to-price ratio of the first generation …

A New Revocable And Re-Delegable Proxy Signature And Its Application, Shengmin Xu, Guomin Yang, Yi Mu

Research Collection School Of Computing and Information Systems

With the popularity of cloud computing and mobile Apps, on-demand services such as on-line music or audio streaming and vehicle booking are widely available nowadays. In order to allow efficient delivery and management of the services, for large-scale on-demand systems, there is usually a hierarchy where the service provider can delegate its service to a top-tier (e.g., countrywide) proxy who can then further delegate the service to lower level (e.g., region-wide) proxies. Secure (re-)delegation and revocation are among the most crucial factors for such systems. In this paper, we investigate the practical solutions for achieving re-delegation and revocation utilizing proxy …

An Efficient And Privacy-Preserving Biometric Identification Scheme In Cloud Computing, Liehuang Zhu, Chuan Zhang, Chang Xu, Ximeng Liu, Cheng Huang

Research Collection School Of Computing and Information Systems

Biometric identification has become increasingly popular in recent years.With the development of cloud computing, database owners are motivated to outsource the large size of biometric data and identification tasks to the cloud to get rid of the expensive storage and computation costs, which, however, brings potential threats to users’ privacy. In this paper, we propose an efficient and privacy-preserving biometric identification outsourcing scheme. Specifically, the biometric: To execute a biometric identification, the database owner encrypts the query data and submits it to the cloud. The cloud performs identification operations over the encrypted database and returns the result to the database …

Attributed Social Network Embedding, Lizi Liao, Xiangnan He, Hanwang Zhang, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Embedding network data into a low-dimensional vector space has shown promising performance for many real-world applications, such as node classification and entity retrieval. However, most existing methods focused only on leveraging network structure. For social networks, besides the network structure, there also exists rich information about social actors, such as user profiles of friendship networks and textual content of citation networks. These rich attribute information of social actors reveal the homophily effect, exerting huge impacts on the formation of social networks. In this paper, we explore the rich evidence source of attributes in social networks to improve network embedding. We …

Constant-Size Ciphertexts In Threshold Attribute-Based Encryption Without Dummy Attributes, Willy Susilo, Guomin Yang, Fuchun Guo, Qiong Huang

Research Collection School Of Computing and Information Systems

Attribute-based encryption (ABE) is an augmentation of public key encryption that allows users to encrypt and decrypt messages based on users' attributes. In a (t, s) threshold ABE, users who can decrypt a ciphertext must hold at least t attributes among the s attributes specified by the encryptor. At PKC 2010, Herranz, Laguillaumie and Raft& proposed the first threshold ABE with constant-size ciphertexts. In order to ensure the encryptor can flexibly select the attribute set and a threshold value, they use dummy attributes to satisfy the decryption requirement. The advantage of their scheme is that any addition or removal of …

Fixation And Confusion: Investigating Eye-Tracking Participants' Exposure To Information In Personas, Joni Salminen, Bernard J. Jansen, Jisun An, Soon-Gyo Jung, Lene Nielsen, Haewoon Kwak

Research Collection School Of Computing and Information Systems

To more effectively convey relevant information to end users of persona profiles, we conducted a user study consisting of 29 participants engaging with three persona layout treatments. We were interested in confusion engendered by the treatments on the participants, and conducted a within-subjects study in the actual work environment, using eye-tracking and talk-aloud data collection. We coded the verbal data into classes of informativeness and confusion and correlated it with fixations and durations on the Areas of Interests recorded by the eye-tracking device. We used various analysis techniques, including Mann-Whitney, regression, and Levenshtein distance, to investigate how confused users differed …

Hiddencode: Hidden Acoustic Signal Capture With Vibration Energy Harvesting, Guohao Lan, Dong Ma, Mahbub Hassan, Wen Hu

Research Collection School Of Computing and Information Systems

The feasibility of using vibration energy harvesting (VEH) as an energy-efficient receiver for short-range acoustic data communication has been investigated recently. When data was encoded in acoustic signal within the energy harvesting frequency band and transmitted through a speaker, a VEH receiver was capable of decoding the data by processing the harvested energy signal. Although previous work created new opportunities for simultaneous energy harvesting and communication using the same hardware, the communication makes annoying sounds as the energy harvesting frequency band lies within the sensitive region of human auditory system. In this work, we present a novel modulation scheme to …

Visualizing Research Impact Through Citation Data, Yong Wang, Conglei Shi, Liangyue Li, Hanghang Tong, Huamin Qu

Research Collection School Of Computing and Information Systems

Research impact plays a critical role in evaluating the research quality and influence of a scholar, a journal, or a conference. Many researchers have attempted to quantify research impact by introducing different types of metrics based on citation data, such as h-index, citation count, and impact factor. These metrics are widely used in the academic community. However, quantitative metrics are highly aggregated in most cases and sometimes biased, which probably results in the loss of impact details that are important for comprehensively understanding research impact. For example, which research area does a researcher have great research impact on? How does …

Opportunity Identification For New Product Planning: Ontological Semantic Patent Classification, Farshad Madani

Dissertations and Theses

Intelligence tools have been developed and applied widely in many different areas in engineering, business and management. Many commercialized tools for business intelligence are available in the market. However, no practically useful tools for technology intelligence are available at this time, and very little academic research in technology intelligence methods has been conducted to date.

Patent databases are the most important data source for technology intelligence tools, but patents inherently contain unstructured data. Consequently, extracting text data from patent databases, converting that data to meaningful information and generating useful knowledge from this information become complex tasks. These tasks are currently …

A Modified Balcik Last Mile Distribution Model For Relief Operations Using Open Road Networks, Lance L. Putong, Marlene M. De Leon

Department of Information Systems & Computer Science Faculty Publications

The last mile in disaster relief distribution chain is the delivery of goods from a central warehouse to the evacuation centers assigned for a given area. Its effectiveness relies on the proper allocation of each kind of relief good amongst the demand areas on a given frequency. Because these operations involve a limited supply of relief goods, vehicles, and time, it is important to optimize these operations to satisfy as much demand as possible. The study aims to create a linear programming model which provides a set of recommendations on how the current disaster relief supply chain may be carried …

Use Of House Arrest In The Context Of The Respecting The Constitutional Rights Of An Individual In Russia, Svetlana Afanasieva 2365999, Irina Kilina

Journal of Digital Forensics, Security and Law

The authors analyze the selection of preventive measures in the form of house arrest in Russian criminal procedures on the basis of universal and European standards of guaranteeing respect for individual rights. The article states that the application of preventive measures significantly restricts the right to protect the dignity of the individual, the right to freedom and personal inviolability, the right to free movement, choose the place of residence. The authors argue for the alternative method of applying the house arrest. as a form of prevention This preventive measure, unlike detention does not provide for the isolation of a person …

Back Matter, Adfsl

Annual ADFSL Conference on Digital Forensics, Security and Law

No abstract provided.

Front Matter, Adfsl

Annual ADFSL Conference on Digital Forensics, Security and Law

No abstract provided.

Contents, Adfsl

Annual ADFSL Conference on Digital Forensics, Security and Law

No abstract provided.

A Call To Promote Soft Skills In Software Engineering, Luiz Fernando Capretz, Fahem Ahmed

Electrical and Computer Engineering Publications

We have been thinking about other aspects of software engineering for many years; the missing link in engineering software is the soft skills set, essential in the software development process. Although soft skills are among the most important aspects in the creation of software, they are often overlooked by educators and practitioners. One of the main reasons for the oversight is that soft skills are usually related to social and personality factors, i.e., teamwork, motivation, commitment, leadership, multi-culturalism, emotions, interpersonal skills, etc. This editorial is a manifesto declaring the importance of soft skills in software engineering with the intention to …

Faith And Finance, Todd W. Neller

Computer Science Faculty Publications

The seminar covered scriptures concerning money, basic concepts of financial literacy, and a Christian perspective on investing. More information is available at http://cs.gettysburg.edu/~tneller/resources/investing/ .

Stem Outreach Activity With Fitbit Wearable Devices, Joseph Carrigan, David Kotz, Aviel Rubin

Computer Science Technical Reports

This document provides a toolkit for an STEM outreach activity based on Fitbit wearable fitness devices. The activity is targeted toward high-school students. This document provides guidance preparing for and executing the activity and measuring outcomes. This document contains templates that can be used as is or altered to suit your specific needs.

Automating Data Analysis For Two-Dimensional Gas Chromatography/Time-Of-Flight Mass Spectrometry Non-Targeted Analysis Of Comparative Samples, Ivan A. Titaley, O. Maduka Ogba, Leah Chibwe, Eunha Hoh, Paul H.-Y. Cheong, Staci L. Massey Simonich

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Non-targeted analysis of environmental samples, using comprehensive two‐dimensional gas chromatography coupled with time-of-flight mass spectrometry (GC × GC/ToF-MS), poses significant data analysis challenges due to the large number of possible analytes. Non-targeted data analysis of complex mixtures is prone to human bias and is laborious, particularly for comparative environmental samples such as contaminated soil pre- and post-bioremediation. To address this research bottleneck, we developed OCTpy, a Python™ script that acts as a data reduction filter to automate GC × GC/ToF-MS data analysis from LECO^® ChromaTOF^® software and facilitates selection of analytes of interest based on peak area …

Supporting Accurate Interpretation Of Self-Administered Medical Test Results For Mobile Health: Assessment Of Design, Demographics, And Health Condition, Jess C. Hohenstein, Eric P.S. Baumer, Lindsay Reynolds, Elizabeth L. Murnane, Dakota O'Dell, Seoho Lee, Shion Guha, Yu Qi, Erin Rieger, Geri K. Gay

Mathematics, Statistics and Computer Science Faculty Research and Publications

Background: Technological advances in personal informatics allow people to track their own health in a variety of ways, representing a dramatic change in individuals’ control of their own wellness. However, research regarding patient interpretation of traditional medical tests highlights the risks in making complex medical data available to a general audience.

Objective: This study aimed to explore how people interpret medical test results, examined in the context of a mobile blood testing system developed to enable self-care and health management.

Methods: In a preliminary investigation and main study, we presented 27 and 303 adults, respectively, with hypothetical results from several …

Patent Keyword Extraction Algorithm Based On Distributed Representation For Patent Classification, Jie Hu, Shaobo Li, Yong Yao, Liya Yu, Guanci Yang, Jianjun Hu

Faculty Publications

Many text mining tasks such as text retrieval, text summarization, and text comparisons depend on the extraction of representative keywords from the main text. Most existing keyword extraction algorithms are based on discrete bag-of-words type of word representation of the text. In this paper, we propose a patent keyword extraction algorithm (PKEA) based on the distributed Skip-gram model for patent classification. We also develop a set of quantitative performance measures for keyword extraction evaluation based on information gain and cross-validation, based on Support Vector Machine (SVM) classification, which are valuable when human-annotated keywords are not available. We used a standard …

Hack The Planet! -- Cybersecurity Tips To Keep You, Your Data, And Your Clients Safe, Jason Tubinis

Continuing Legal Education Presentations

It is really easy to make you, your practice, and your clients safe from being the victims of a cyber-crime. This paper will discuss some tips, tricks, and considerations you can implement quickly, safely, and on the cheap.

These are relatively simple suggestions, though. You should be able to implement most of these practices within an hour, and while they will save you from the most common security flaws Bad Guys are looking to exploit.

How To Monitor Possible Side Effects Of Enhanced Oil Recovery Process, Jose Manuel Dominguez Esquivel, Solymar Ayala Cortez, Aaron A. Velasco, Vladik Kreinovich

Departmental Technical Reports (CS)

To extract all the oil from a well, petroleum engineers pump hot reactive chemicals into the well. This enhanced oil recovery process needs to be thoroughly monitored, since the aggressively hot liquid can seep out and, if unchecked, eventually pollute the sources of drinking water. At present, to monitor this process, engineers measure the seismic waves generated when the liquid fractures the minerals. However, the resulting seismic waves are weak in comparison with the background noise. Thus, the accuracy with which we can locate the spreading liquid based on these weak signals is low, and we get only a very …