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It is important to provide sightseeing information to foreign people to promote tourism industry. However, in order to provide fresh information or intend for new sightseeing contents, we need to pay for the cost of contents updating and system migration. Therefore, we propose “Self-extending Type Open Data Platform” that can take in the tweet of the tourist automatically. This proposed platform has...
Automatic Generation Control (AGC) is a key control system in the power grid. It is used to calculate the Area Control Error (ACE) based on frequency and tie-line power flow between balancing areas, and then adjust power generation to maintain the power system frequency in an acceptable range. However, attackers might inject malicious frequency or tie-line power flow measurements to mislead AGC to...
Our research is initially motivated by a conversation we had with a group of cyber security analysts that are responsible for monitoring enterprise security at a large corporation who were experiencing day-to-day operational burdens. As a result, this paper focuses on the design and implementation of an Intelligent Cyber Security Assistant (ICSA) architecture that would provide intelligent assistance...
Applications in computer network security, social media analysis, and other areas rely on analyzing a changing environment. The data is rich in relationships and lends itself to graph analysis. Traditional static graph analysis cannot keep pace with network security applications analyzing nearly one million events per second and social networks like Facebook collecting 500 thousand comments per second...
Compute-intensive simulations typically chargesubstantial workloads on an online simulation platform backedby limited computing clusters and storage resources. Some (ormost) of the simulations initiated by users may accompany inputparameters/files that have been already provided by other (orsame) users in the past. Unfortunately, these duplicatesimulations may aggravate the performance of the platform...
Internet of vehicles (IoVs) emerges as a promising technology to facilitate vehicular wireless communication by approving vehicle-to-everything (V2X) services for intelligent transportation systems including vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I) and vehicle-to-pedestrian (V2P) services. V2V networks have been rapidly developed to support short distance data transmission among vehicles...
In order to enable the development of smart services, many IoT platforms were proposed to securely and reliably connect IoT devices to the Internet and to each other. Examples are IoTivity from Open Connectivity Foundation (OCF), AllJoyn from AllSeen Alliance, Weave from Google and HomeKit from Apple. However, such fragmentation of IoT platforms has made the development of IoT applications very difficult...
Recently, Malaysia has been reported with dengue epidemic, that could rise up to 120, 000 cases recorded per year. This serious issue needs a vital look to prevent the dengue occurrences as it has no medicine yet to be found. Therefore, studies need to be done in order to prevent the dengue occurrences. This paper presents a high accuracy dengue occurrences prediction model which could forecast the...
The emergence of mobile games has caused a paradigm shift in the video-game industry. Game developers now have at their disposal a plethora of information on their players, and thus can take advantage of reliable models that can accurately predict player behavior and scale to huge datasets. Churn prediction, a challenge common to a variety of sectors, is particularly relevant for the mobile game industry,...
The two-ray model has been used for modelling of wireless channels already for decades. However, since researchers and industry are pushing forward to unlock the millimeter wave bands, we revisited this model. We re-derive the break point distance based on a generalized first Fresnel zone. The simplified approximation formula — four times the product of antenna heights scaled by wavelength — is especially...
The design of recommendation method is the core of personalized recommendation, and the implementation of recommendation depends on the matching relation between user preference and resource object. This paper proposes a hybrid personalized recommendation method based on context-based collaborative filtering and knowledge recommendation, which is based on personalized recommendation knowledge model,...
Different from representation learning models using deep learning to project original feature space into lower density ones, we propose a feature space learning (FSL) model based on a semi-supervised clustering framework. There are three main contributions in our approach: (1) Inspired by Zipf's law and word bursts, the feature space learning processes not only select trusted unlabeled samples and...
Rumors spread on Online Social Networks sometimes can lead to serious social issues. To accurately identify them from normal posts is proved to be of great value. Users' behaviors are different when they post rumors and normal posts. Since rumors only account for a small percentage of all posts, they can be regarded as anomalies. Therefore, we propose an anomaly detection method based on autoencoder...
We propose AccountTrade, a set of accountable protocols, for big data trading among dishonest consumers. To secure the big data trading environment, our protocols achieve book-keeping ability and accountability against dishonest consumers who may misbehave throughout the dataset transactions. Specifically, we study the responsibilities of the consumers in the dataset trading and design AccountTrade...
We study learning outcome prediction for online courses. Whereas prior work has focused on semester-long courses with frequent student assessments, we focus on short-courses that have single outcomes assigned by instructors at the end. The lack of performance data makes the behavior of learners, captured as they interact with course content and with one another in Social Learning Networks (SLN), essential...
Rapid pace of global urbanization has posed significant challenges to urban transportation infrastructures. Existing urban transit systems suffer many well-known shortcomings, where public transits have limits on coverage areas, and fixed schedules, and private transits are expensive and fail to timely meet the demand needs. We thus envision a Cloud-Commuting system, that employs a giant pool of centralized...
Over the past few years, many major wireless providers restricted their unlimited data plans and replaced them with limited-size fixed-price data packages. While this could be perceived as a disadvantage for customers, it helps the cellular wireless providers to reduce the traffic intensity at their base stations. Then the lower traffic intensity leads to a better service quality and higher rates...
Malware, short for malicious software, contuses to morph and change. Traditional anti-virus software may have problems detecting malicious software that have not been seen before. By employing machine learning techniques, one can learn the general behavior patterns of different threat types and use these to detect variants of unknown threats. We have developed a malware detection system based on machine...
A set of instructions for data flow virtual machine is researched. An experimental virtual machine for data flow paradigm is presented for demonstration of computational model. Backus-Naur form of input file for data flow virtual machine is described. A definition of data flow processing in virtual machine is proposed. Some simple data flow computation examples are described.
We consider a Physical-Unclonable-Function (PUF)-based authentication process. We define achievable secret-key rate versus privacy-leakage rate pairs featuring perfect secrecy and uniform distribution of the secret-key. We derive the capacity region corresponding to this definition of achievability and thus show that it equals the known capacity region corresponding to weak secrecy. We define achievability...
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