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- Creators: Schumann, Robert, 1810-1856
Description
Internet browsers are today capable of warning internet users of a potential phishing attack. Browsers identify these websites by referring to blacklists of reported phishing websites maintained by trusted organizations like Google, Phishtank etc. On identifying a Unified Resource Locator (URL) requested by a user as a reported phishing URL, browsers like Mozilla Firefox and Google Chrome display an 'active' warning message in an attempt to stop the user from making a potentially dangerous decision of visiting the website and sharing confidential information like username-password, credit card information, social security number etc.
However, these warnings are not always successful at safeguarding the user from a phishing attack. On several occasions, users ignore these warnings and 'click through' them, eventually landing at the potentially dangerous website and giving away confidential information. Failure to understand the warning, failure to differentiate different types of browser warnings, diminishing trust on browser warnings due to repeated encounter are some of the reasons that make users ignore these warnings. It is important to address these factors in order to eventually improve a user’s reaction to these warnings.
In this thesis, I propose a novel design to improve the effectiveness and reliability of phishing warning messages. This design utilizes the name of the target website that a fake website is mimicking, to display a simple, easy to understand and interactive warning message with the primary objective of keeping the user away from a potentially spoof website.
However, these warnings are not always successful at safeguarding the user from a phishing attack. On several occasions, users ignore these warnings and 'click through' them, eventually landing at the potentially dangerous website and giving away confidential information. Failure to understand the warning, failure to differentiate different types of browser warnings, diminishing trust on browser warnings due to repeated encounter are some of the reasons that make users ignore these warnings. It is important to address these factors in order to eventually improve a user’s reaction to these warnings.
In this thesis, I propose a novel design to improve the effectiveness and reliability of phishing warning messages. This design utilizes the name of the target website that a fake website is mimicking, to display a simple, easy to understand and interactive warning message with the primary objective of keeping the user away from a potentially spoof website.
ContributorsSharma, Satyabrata (Author) / Bazzi, Rida (Thesis advisor) / Walker, Erin (Committee member) / Gaffar, Ashraf (Committee member) / Arizona State University (Publisher)
Created2015
Description
Despite the various driver assistance systems and electronics, the threat to life of driver, passengers and other people on the road still persists. With the growth in technology, the use of in-vehicle devices with a plethora of buttons and features is increasing resulting in increased distraction. Recently, speech recognition has emerged as an alternative to distraction and has the potential to be beneficial. However, considering the fact that automotive environment is dynamic and noisy in nature, distraction may not arise from the manual interaction, but due to the cognitive load. Hence, speech recognition certainly cannot be a reliable mode of communication.
The thesis is focused on proposing a simultaneous multimodal approach for designing interface between driver and vehicle with a goal to enable the driver to be more attentive to the driving tasks and spend less time fiddling with distractive tasks. By analyzing the human-human multimodal interaction techniques, new modes have been identified and experimented, especially suitable for the automotive context. The identified modes are touch, speech, graphics, voice-tip and text-tip. The multiple modes are intended to work collectively to make the interaction more intuitive and natural. In order to obtain a minimalist user-centered design for the center stack, various design principles such as 80/20 rule, contour bias, affordance, flexibility-usability trade-off etc. have been implemented on the prototypes. The prototype was developed using the Dragon software development kit on android platform for speech recognition.
In the present study, the driver behavior was investigated in an experiment conducted on the DriveSafety driving simulator DS-600s. Twelve volunteers drove the simulator under two conditions: (1) accessing the center stack applications using touch only and (2) accessing the applications using speech with offered text-tip. The duration for which user looked away from the road (eyes-off-road) was measured manually for each scenario. Comparison of results proved that eyes-off-road time is less for the second scenario. The minimalist design with 8-10 icons per screen proved to be effective as all the readings were within the driver distraction recommendations (eyes-off-road time < 2sec per screen) defined by NHTSA.
The thesis is focused on proposing a simultaneous multimodal approach for designing interface between driver and vehicle with a goal to enable the driver to be more attentive to the driving tasks and spend less time fiddling with distractive tasks. By analyzing the human-human multimodal interaction techniques, new modes have been identified and experimented, especially suitable for the automotive context. The identified modes are touch, speech, graphics, voice-tip and text-tip. The multiple modes are intended to work collectively to make the interaction more intuitive and natural. In order to obtain a minimalist user-centered design for the center stack, various design principles such as 80/20 rule, contour bias, affordance, flexibility-usability trade-off etc. have been implemented on the prototypes. The prototype was developed using the Dragon software development kit on android platform for speech recognition.
In the present study, the driver behavior was investigated in an experiment conducted on the DriveSafety driving simulator DS-600s. Twelve volunteers drove the simulator under two conditions: (1) accessing the center stack applications using touch only and (2) accessing the applications using speech with offered text-tip. The duration for which user looked away from the road (eyes-off-road) was measured manually for each scenario. Comparison of results proved that eyes-off-road time is less for the second scenario. The minimalist design with 8-10 icons per screen proved to be effective as all the readings were within the driver distraction recommendations (eyes-off-road time < 2sec per screen) defined by NHTSA.
ContributorsMittal, Richa (Author) / Gaffar, Ashraf (Thesis advisor) / Femiani, John (Committee member) / Gray, Robert (Committee member) / Arizona State University (Publisher)
Created2015
Description
Brains and computers have been interacting since the invention of the computer. These two entities have worked together to accomplish a monumental set of goals, from landing man on the moon to helping to understand how the universe works on the most microscopic levels, and everything in between. As the years have gone on, the extent and depth of interaction between brains and computers have consistently widened, to the point where computers help brains with their thinking in virtually infinite everyday situations around the world. The first purpose of this research project was to conduct a brief review for the purposes of gaining a sound understanding of how both brains and computers operate at fundamental levels, and what it is about these two entities that allow them to work evermore seamlessly as the years go on. Next, a history of interaction between brains and computers was developed, which expanded upon the first task and helped to contribute to visions of future brain-computer interaction (BCI). The subsequent and primary task of this research project was to develop a theoretical framework for a potential brain-aiding device of the future. This was done by conducting an extensive literature review regarding the most advanced BCI technology in modern times and expanding upon the findings to argue feasibility of the future device and its components. Next, social predictions regarding the acceptance and use of the new technology were made by designing and executing a survey based on the Unified Theory of the Acceptance and Use of Technology (UTAUT). Finally, general economic predictions were inferred by examining several relationships between money and computers over time.
ContributorsThum, Giuseppe Edwardo (Author) / Gaffar, Ashraf (Thesis director) / Gonzalez-Sanchez, Javier (Committee member) / College of Integrative Sciences and Arts (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
Description
Intelligence is a loosely defined term, but it is a quality that we try to measure in humans, animals, and recently machines. Progress in artificial intelligence is slow, but we have recently made breakthroughs by paying attention to biology and neuroscience. We have not fully explored what biology has to offer us in AI research, and this paper explores aspects of intelligent behavior in nature that machines still struggle with.
ContributorsLahtinen, David (Author) / Gaffar, Ashraf (Thesis director) / Sanchez, Javier Gonzalez (Committee member) / Software Engineering (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
Driver distraction research has a long history spanning nearly 50 years, intensifying in the last decade. The focus has always been on identifying the distractive tasks and measuring the respective harm level. As in-vehicle technology advances, the list of distractive activities grows along with crash risk. Additionally, the distractive activities become more common and complicated, especially with regard to In-Car Interactive System. This work's main focus is on driver distraction caused by the in-car interactive System. There have been many User Interaction Designs (Buttons, Speech, Visual) for Human-Car communication, in the past and currently present. And, all related studies suggest that driver distraction level is still high and there is a need for a better design. Multimodal Interaction is a design approach, which relies on using multiple modes for humans to interact with the car & hence reducing driver distraction by allowing the driver to choose the most suitable mode with minimum distraction. Additionally, combining multiple modes simultaneously provides more natural interaction, which could lead to less distraction. The main goal of MMI is to enable the driver to be more attentive to driving tasks and spend less time fiddling with distractive tasks. Engineering based method is used to measure driver distraction. This method uses metrics like Reaction time, Acceleration, Lane Departure obtained from test cases.
ContributorsJahagirdar, Tanvi (Author) / Gaffar, Ashraf (Thesis advisor) / Ghazarian, Arbi (Committee member) / Gray, Robert (Committee member) / Arizona State University (Publisher)
Created2015
Description
Driving is already a complex task that demands a varying level of cognitive and physical load. With the advancement in technology, the car has become a place for media consumption, a communications center and an interconnected workplace. The number of features in a car has also increased. As a result, the user interaction inside the car has become overcrowded and more complex. This has increased the amount of distraction while driving and has also increased the number of accidents due to distracted driving. This thesis focuses on the critical analysis of today’s in-car environment covering two main aspects, Multi Modal Interaction (MMI), and Advanced Driver Assistance Systems (ADAS), to minimize the distraction. It also provides deep market research on future trends in the smart car technology. After careful analysis, it was observed that an infotainment screen cluttered with lots of small icons, a center stack with a plethora of small buttons and a poor Voice Recognition (VR) results in high cognitive load, and these are the reasons for the increased driver distraction. Though the VR has become a standard technology, the current state of technology is focused on features oriented design and a sales driven approach. Most of the automotive manufacturers are focusing on making the VR better but attaining perfection in VR is not the answer as there are inherent challenges and limitations in respect to the in-car environment and cognitive load. Accordingly, the research proposed a novel in-car interaction design solution: Multi-Modal Interaction (MMI). The MMI is a new term when used in the context of vehicles, but it is widely used in human-human interaction. The approach offers a non-intrusive alternative to the driver to interact with the features in the car. With the focus on user-centered design, the MMI and ADAS can potentially help to reduce the distraction. To support the discussion, an experiment was conducted to benchmark a minimalist UI design. An engineering based method was used to test and measure distraction of four different UIs with varying numbers of icons and screen sizes. Lastly, in order to compete with the market, the basic features that are provided by all the other competitors cannot be eliminated, but the hard work can be done to improve the HCaI and to make driving safer.
ContributorsNakrani, Paresh Keshubhai (Author) / Gaffar, Ashraf (Thesis advisor) / Sohoni, Sohum (Committee member) / Ghazarian, Arabi (Committee member) / Arizona State University (Publisher)
Created2015
ContributorsSchumann, Robert, 1810-1856 (Composer)
ContributorsSchumann, Robert, 1810-1856 (Composer)
ContributorsSchumann, Robert, 1810-1856 (Composer)
Description
Text Classification is a rapidly evolving area of Data Mining while Requirements Engineering is a less-explored area of Software Engineering which deals the process of defining, documenting and maintaining a software system's requirements. When researchers decided to blend these two streams in, there was research on automating the process of classification of software requirements statements into categories easily comprehensible for developers for faster development and delivery, which till now was mostly done manually by software engineers - indeed a tedious job. However, most of the research was focused on classification of Non-functional requirements pertaining to intangible features such as security, reliability, quality and so on. It is indeed a challenging task to automatically classify functional requirements, those pertaining to how the system will function, especially those belonging to different and large enterprise systems. This requires exploitation of text mining capabilities. This thesis aims to investigate results of text classification applied on functional software requirements by creating a framework in R and making use of algorithms and techniques like k-nearest neighbors, support vector machine, and many others like boosting, bagging, maximum entropy, neural networks and random forests in an ensemble approach. The study was conducted by collecting and visualizing relevant enterprise data manually classified previously and subsequently used for training the model. Key components for training included frequency of terms in the documents and the level of cleanliness of data. The model was applied on test data and validated for analysis, by studying and comparing parameters like precision, recall and accuracy.
ContributorsSwadia, Japa (Author) / Ghazarian, Arbi (Thesis advisor) / Bansal, Srividya (Committee member) / Gaffar, Ashraf (Committee member) / Arizona State University (Publisher)
Created2016