The global climate change has been one of the serious problems in the 21 st century. In this paper, we analyze the correlations or patterns associated with the global temperature data, carbon-dioxide emission and the location information based on the latitude or longitude. We do find some interesting patterns, especially the ones based on latitude or longitude information. The analytical results can be used to better understand the characteristics of climate change in different locations.
Multicopters are small, typically unmanned helicopters having more than two rotors. The wide range of possible applications of multicopters, spanning from environmental research to recreation, has raised the need to come up with innovative solutions to reduce the power demand of these platforms, with the goal of guaranteeing safe completion of missions. To this end, it is of paramount importance to understand the way in which the energy is invested and spent. The goal of this work is to provide reliable means to monitor multicopters energy consumption. We developed a monitoring platform to keep track of the energy consumption of multicopters. The platform relies on a set of sensors to collect the energy consumption data at different points of interest; data are then visualized in a monitoring dashboard. The monitoring system allows further analysis of the recorded data, which could be used to optimize multicopters energy consumption.
Recommender Systems have been successfully applied to alleviate the information overload problem and assist the process of decision making. Collaborative filtering, as one of the most popular recommendation algorithms, has been fully explored and developed in the past two decades. However, one of the challenges in collaborative filtering, the problem of "Grey Sheep" user, is still under investigation. "Grey Sheep" users is a group of the users who have special tastes and they may neither agree nor disagree with the majority of the users. The identification of them becomes a challenge in collaborative filtering, since they may introduce difficulties to produce accurate collaborative recommendations. In this paper, we propose a novel approach which can identify the Grey Sheep users by reusing the outlier detection techniques based on the distribution of user-user similarities. Our experimental results based on the MovieLens 10M rating data demonstrate the ease and effectiveness of our proposed approach.
This study1 determined the factors that influenced the usability of "Fatchum" - a mobile application Filipino recipe recommender system. Toward this goal, two sets of data were gathered to determine the usability of the mobile app. The first set of data gathered the demographic factors (i.e., age, gender, occupation, level of occupation, and level of knowledge in cooking) and the subjective measures of usability of the app in terms of its design-related factors. The design-related factors were measured in terms of user-interface, navigability, and functionality. It was shown that age, gender, and navigability were significant factors that influenced the usability of the app. The objective measures showed that the app can provide recipe names quickly but fails to share the recipes in a social networking site. Thus, the system is partially successful in meeting its intended purpose. Recommendations for future studies are also offered.
The Cyber Transport Systems (CTSs) have made significant advancement along with the development of the information technology and transportation industries worldwide. The rapid proliferation of cyber transportation technology provides rich information and infinite possibilities for our society to understand and use the complex inherent mechanism, which governs the novel intelligence world. In addition, applying information technology to cyber transportation applications open a range of new application scenarios, such as vehicular safety, energy efficiency, reduced pollution, and intelligent maintenance services. However, while enjoying the services and convenience provided by CTS, users, vehicles, even the systems might lose privacy during information transmitting and processing. This paper summarizes the state-of-art research findings on information privacy issues in a broad range. We firstly introduce the typical types of information and the basic mechanisms of information communication in CTS. Secondly, considering the information privacy issues of CTS, we present the literature on information privacy issues and privacy protection approaches in CTS. Thirdly, we discuss the emerging challenges and the opportunities for the information technology community in CTS.
Bluetooth Low Energy device is increasing in popularity due to its lower energy consumption and reliable connectivity compared to the classic Bluetooth. Some of these BLE devices collects and transmits health care data like the heart rate as in a Fitbit smart band. This paper will demonstrate that Bluetooth Low Energy devices that relies on BLE security has weak communication security and how to solve that problem using a private-key encryption algorithm.
As crimes, along with nearly every aspect of life, continue to transit into cyberspace, network traffic becomes an increasingly important source of evidence for forensic investigators. Network forensics is most commonly used in analyzing network traffic, identifying suspicious patterns and tracing the source of attack. This paper takes a different approach and views network traffic not as a means to an end, but the source from which evidence can be extracted. When criminals take extra measures to wipe evidence from all physical servers and disks, carving the files from network traffic may become critical to investigations. However, with limitations in current computing power, analyzing each packet for extractable evidence is impractical. This study proposes an architecture for file extraction that incorporates network flow aggregation and indexing for faster, more efficient packet and file extraction.
The internet changes the way we do business, with companies like Amazon, Uber, and Google reshaping the way commerce is done delivering packages. Companies, such as Nokia, are demonstrating drone fleets being used for public safety over large scale desert areas. Our research asked, could this technology be replicated on a small scale for independent operators to use? The initial goal of this project was to design and develop a framework to control and manage drone fleets for use in search and rescue and disaster relief. We were able to design a platform and framework that integrated common off-the-shelf drones and accessible Windows computers and Android Phones to build and deploy our Autonomous Movement Framework.
In this paper, the security posture of two versions of the Cisco Nexus 1000V virtual switch is tested against a set of exploits known to be valid on physical switching infrastructure. Specifically, the Nexus 1000V as implemented with VMware's ESXi hypervisor is examined. The attempted exploits are CAM table overflows, VLAN hopping, Spanning Tree manipulation, ARP poisoning, and Private VLAN attacks. With the exception of Spanning Tree manipulation, the Nexus 1000V is vulnerable to all of the attacks in at least one of the tested release combinations. This leads to a call for additional security considerations when deploying the Nexus 1000V/ESXi combination in data centers and cloud provider networks as intended by their design.
Technology is an incredible enabler for change. However, when we consider the uses of technology in an urban or community context, we need to take a human-centered approach that puts the needs of people ahead of the dependence on business models, revenue, etc. In this talk, I'll discuss the people-first approach to technology and design that the Mayor's Office of New Urban Mechanics has embraced to bring transformative change to the City of Boston.
Touch-sensitive displays have become very popular with the advent of smartphones and tablets. Most smartphones and tablets are designed for multi-touch finger control. Displays with stylus or light pen input predate the modern multi-touch displays but became less popular for a variety of reasons, one of which is that their usability and user experience was not good. Stylus usability was limited by the available technology. In recent years stylus input devices have become more capable and popular. In particular, they are not only used for navigation and minor input, they are becoming popular for content creation in the form of sketching and handwriting. Recent stylus-tablet combinations from Microsoft and Apple, among others, specifically target content creation. However, the technical performance of the latest devices is still less than completely desirable, particularly in the areas of latency, accuracy and precision. As stylus input devices grow in popularity and become a growing part of Information Technology these aspects need more understanding. This study investigates the quantitatively measurable usability characteristics of stylus performance with particular emphasis on latency and accuracy. Latency and positioning accuracy are measured for a few current technology stylus/tablet combinations with different operating systems and application software packages. We find that the line-drawing mechanism exhibits an unexpected step-wise behavior and that there are still significant latency and accuracy delays and other anomalies, as well as other concerns. While modern stylus/tablet systems give generally satisfactory performance there is room for improvement.
Intrusion detection systems need to be both accurate and fast. Speed is important especially when operating at the network level. Additionally, many intrusion detection systems rely on signature based detection approaches. However, machine learning can also be helpful for intrusion detection. One key challenge when using machine learning, aside from the detection accuracy, is using machine learning algorithms that are fast. In this paper, several processing architectures are considered for use in machine learning based intrusion detection systems. These architectures include standard CPUs, GPUs, and cognitive processors. Results of their processing speeds are compared and discussed.
This project was designed to discover the relationship between the number of enabled rules maintained by Snort and the amount of computing resources necessary to operate this intrusion detection system (IDS) as a sensor. A physical environment was set up to loosely simulate a network and an IDS sensor monitoring it. The experiment was conducted in five trials. A different number of Snort rules was enabled in each trial and the corresponding utilization of computing resources was measured. Remarkable variation and a clear trend of CPU usage were observed in the experiment.
A honeypot is a deception tool for enticing attackers to make efforts to compromise the electronic information systems of an organization. A honeypot can serve as an advanced security surveillance tool for use in minimizing the risks of attacks on information technology systems and networks. Honeypots are useful for providing valuable insights into potential system security loopholes. The current research investigated the effectiveness of the use of centralized system management technologies called Puppet and Virtual Machines in the implementation automated honeypots for intrusion detection, correction and prevention. A centralized logging system was used to collect information of the source address, country and timestamp of intrusions by attackers. The unique contributions of this research include: a demonstration how open source technologies is used to dynamically add or modify hacking incidences in a high-interaction honeynet system; a presentation of strategies for making honeypots more attractive for hackers to spend more time to provide hacking evidences; and an exhibition of algorithms for system and network intrusion prevention.
Although the iPad device has become a new trend as a teaching and learning tool in schools, using it in Saudi schools is still relatively new. The purpose of the study was to investigate whether teaching and learning with the iPad enhances Arabic language learning for first graders. Participants were separated into two groups: a technology group where students used the iPad and educational apps to learn the Arabic Language and a traditional group where students used pencil and paper. Progress in reading, writing, and cognitive skills were measured before and after instruction of Arabic language lessons. Independent t-tests were used to determine if there was a statistically significant difference in the scores and times taken to complete tasks. The study results show that the technology group had significantly higher scores on the post tests for cognitive and reading skills than the technology group. The results also show a significant difference between the writing scores of the two groups, and the technology group had lower writing scores than the traditional group.
Social networking sites have become major targets for cyber-security attacks due to their massive user base. Many studies investigated the security vulnerabilities and privacy issues of social networking sites and made recommendations on how to mitigate security risks. Users are an integral part of any security mix. In this paper, we explore the relationship between users' security perceptions and their actual behavior on social networking sites. Protection motivation theory (PMT), initially was developed to study fear appeals, and has been widely used to examine people's behavior in information security domains. We propose that PMT theory can also be adapted to explain and predict social media users' behaviors that have security implications. We plan to use a web-based survey to measure users' security awareness on social networking sites and collect data on their actual behavior. The research design and plan are presented in accordance to our research
The MP4 files have become the most used video media file available, and will mostly likely remain at the top for some time to come. This makes MP4 files an interesting candidate for steganography. With its size and structure, it offers a challenge to steganography developers. While some attempts have been made to create a truly covert file, few are as successful as Martin Fiedler's TCSteg. TCSteg allows users to hide a TrueCrypt hidden volume in an MP4 file. The structure of the file makes it difficult to identify that a volume exists. In our analysis of TCSteg, we will show how Fielder's code works and how we may be able to detect the existence of steganography. We will then implement these methods in hope that other steganography analysis can use them to determine if an MP4 file is a carrier file. Finally, we will address the future of MP4 steganography.
Insider threats remain a significant problem within organizations, especially as industries that rely on technology continue to grow. Traditionally, research has been focused on the malicious insider; someone that intentionally seeks to perform a malicious act against the organization that trusts him or her. While this research is important, more commonly organizations are the victims of non-malicious insiders. These are trusted employees that are not seeking to cause harm to their employer; rather, they misuse systems-either intentional or unintentionally-that results in some harm to the organization. In this paper, we look at both by developing and validating instruments to measure the behavior and circumstances of a malicious insider versus a non-malicious insider. We found that in many respects their psychological profiles are very similar. The results are also consistent with other research on the malicious insider from a personality standpoint. We expand this and also find that trait negative affect, both its higher order dimension and the lower order dimensions, are highly correlated with insider threat behavior and circumstances. This paper makes four significant contributions: 1) Development and validation of survey instruments designed to measure the insider threat; 2) Comparison of the malicious insider with the non-malicious insider; 3) Inclusion of trait affect as part of the psychological profile of an insider; 4) Inclusion of a measure for financial well-being, and 5) The successful use of survey research to examine the insider threat problem.
We examine the role personality may play in individuals taking the measures necessary to help keep their personal information from being compromised. This is done by using a previously developed and validated survey instrument and combining it with measures for personality in a large-scale survey to see what, if any, relationships may be found. Extraversion, agreeableness, openness, and conscientiousness were all positively associated with taking measures necessary to help mitigate the loss of one's personal information. In contrast, individuals considered more neurotic were less likely to engage in such protective behavior.
The Physical Web is a project announced by Google's Chrome team that essentially provides a framework to discover "smart" physical objects (e.g. vending machines, classroom, conference room, cafeteria etc.) and interact with specific, contextual content without having to resort to downloading a specific app. A common app such as the open source and freely available Physical Web app on the Google Play Store or the BKON Browser on the Apple App Store, can access nearby beacons. A current work-in-progress at the University of Maui College is developing a campus-wide prototype of beacon technology using Eddystone-URL and EID protocol from various beacon vendors.
