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Articles 2461 - 2490 of 2925
Full-Text Articles in Computer Sciences
Developing A Kinect Based Holoportation System, Soumya Chiday
Developing A Kinect Based Holoportation System, Soumya Chiday
Browse all Theses and Dissertations
Holographic communication and distributed collaboration offer great potential for empathic computing to help remove the cost, distance, language and expertise barriers in many social and economic activities. Recent advances in AR-enhanced communication as evident by Microsoft Holoportation technology demonstrate the progress toward fully immersive collaborations distributed and remotely. Current holoportation system requires the use of extensive camera-arrays and powerful server system due to the computation demand and sensory needs to capture and reconstruct the subject of interests Thus, they suffer in mobility and applicability in real-world scenarios. In this thesis, we present an ultra-portable holoportation system design that requires only …
Using Natural Language Processing And Machine Learning For Analyzing Clinical Notes In Sickle Cell Disease Patients, Shufa Khizra
Using Natural Language Processing And Machine Learning For Analyzing Clinical Notes In Sickle Cell Disease Patients, Shufa Khizra
Browse all Theses and Dissertations
Sickle Cell Disease (SCD) is a hereditary disorder in red blood cells that can lead to excruciating pain episodes. SCD causes the normal red blood cells to distort its shape and turn into sickle shape. The distorted shape makes the hemoglobin inflexible and stick to the walls of the vessels thereby obstructing the free flow of blood and eventually making the tissues suffer from lack of oxygen. The lack of oxygen causes serious problems including Acute Chest Syndrome (ACS), stroke, infection, organ damage, and over the lifetime an SCD can harm a persons spleen, brain, kidneys, eyes, bones. Sickling of …
Collaborative Fall Detection Using Smartphone And Kinect, Xue Li, Lanshun Nie, Hanchuan Xu, Xianzhi Wang
Collaborative Fall Detection Using Smartphone And Kinect, Xue Li, Lanshun Nie, Hanchuan Xu, Xianzhi Wang
Research Collection School Of Computing and Information Systems
Humanfall detection has attracted broad attentions as sensors and mobile devices are increasingly adopted in real-life scenarios such as smart homes. The complexity of activities in home environments pose severe challenges to the fall detection research with respect to the detection accuracy. We propose a collaborative detection platform that combines two subsystems: a threshold-based fall detection subsystem using mobile phones and a support vector machine (SVM)-based fall detection subsystem using Kinects. Both subsystems have their respective confidence models and the platform detects falls by fusing the data of both subsystems using two methods: the logical rules-based and D-S evidence fusion …
Exact And Heuristic Approaches For The Multi-Agent Orienteering Problem With Capacity Constraints, Wenjie Wang, Hoong Chuin Lau, Shih-Fen Cheng
Exact And Heuristic Approaches For The Multi-Agent Orienteering Problem With Capacity Constraints, Wenjie Wang, Hoong Chuin Lau, Shih-Fen Cheng
Research Collection School Of Computing and Information Systems
This paper introduces and addresses a new multiagent variant of the orienteering problem (OP), namely the multi-agent orienteering problem with capacity constraints (MAOPCC). Different from the existing variants of OP, MAOPCC allows a group of visitors to concurrently visit a node but limits the number of visitors simultaneously being served at each node. In this work, we solve MAOPCC in a centralized manner and optimize the total collected rewards of all agents. A branch and bound algorithm is first proposed to find an optimal MAOPCC solution. Since finding an optimal solution for MAOPCC can become intractable as the number of …
Smart Monitoring Via Participatory Ble Relaying, Meeralakshmi Radhakrishnan, Sougata Sen, Archan Misra, Youngki Lee, Rajesh Krishna Balan
Smart Monitoring Via Participatory Ble Relaying, Meeralakshmi Radhakrishnan, Sougata Sen, Archan Misra, Youngki Lee, Rajesh Krishna Balan
Research Collection School Of Computing and Information Systems
We espouse the vision of a smart object/campus architecture where sensors attached to smart objects use BLE as communication interface, and where smartphones act as opportunistic relays to transfer the data. We explore the feasibility of the vision with real-world Wi-Fi based location traces from our university campus. Our feasibility studies establish that redundancy exists in user movement within the indoor spaces, and that this redundancy can be exploited for collecting sensor data in an opportunistic, yet fair manner. We develop a couple of alternative heuristics that address the BLE energy asymmetry challenge by intelligently duty-cycling the scanning actions of …
Secure Smart Metering Based On Lora Technology, Yao Cheng, Hendra Saputra, Leng Meng Goh, Yongdong Wu
Secure Smart Metering Based On Lora Technology, Yao Cheng, Hendra Saputra, Leng Meng Goh, Yongdong Wu
Research Collection School Of Computing and Information Systems
Smart metering allows Substation Automation System (SAS) to remotely and timely read smart meters. Despite its advantages, smart metering brings some challenges. a) It introduces cyber attack risks to the metering system, which may lead to user privacy leakage or even the compromise of smart metering systems. b) Although the majority of meters are located within a regional power supply area, some hard-to-reach nodes are geographically far from the clustered area, which account for a big portion of the entire smart metering operation cost. Facing the above challenges, we propose a secure smart metering infrastructure based on LoRa technology which …
Securing Display Path For Security-Sensitive Applications On Mobile Devices, Jinhua Cui, Yuanyuan Zhang, Zhiping Cai, Anfeng Liu, Yangyang Li
Securing Display Path For Security-Sensitive Applications On Mobile Devices, Jinhua Cui, Yuanyuan Zhang, Zhiping Cai, Anfeng Liu, Yangyang Li
Research Collection School Of Computing and Information Systems
While smart devices based on ARM processor bring us a lot of convenience, they also become an attractive target of cyber-attacks. The threat is exaggerated as commodity OSes usually have a large code base and suffer from various software vulnerabilities. Nowadays, adversaries prefer to steal sensitive data by leaking the content of display output by a security-sensitive application. A promising solution is to exploit the hardware visualization extensions provided by modern ARM processors to construct a secure display path between the applications and the display device. In this work, we present a scheme named SecDisplay for trusted display service, it …
Divine Vulpine: 3d Simulation Of Colorations Of The Wild And Domesticated Red Fox, Alyssa Newsome
Divine Vulpine: 3d Simulation Of Colorations Of The Wild And Domesticated Red Fox, Alyssa Newsome
Senior Honors Theses and Projects
Vulpes vulpes, the red fox, has been domesticated for hundreds of years. Through the continued breeding of the red fox in captivity, there has been an explosion of variations in color, size, and temperament. With the rise of interest in domesticated foxes as pets and educational animals, there is a dire need for education of the public on these animals and their history. Fur farming also remains a lucrative industry, an industry engaged in continuous and broad academic research. Aimed at these audiences, this academic presentation allows users to view a 30 animated fox, and select its coloration, animation, view, …
Deep Learning Based Recommendation Systems, Nishanth Reddy Pinnapareddy
Deep Learning Based Recommendation Systems, Nishanth Reddy Pinnapareddy
Master's Projects
The usage of Internet applications, such as social networking and e-commerce is increasing exponentially, which leads to an increased offered content. Recommender systems help users filter out relevant content from a large pool of available content. The recommender systems play a vital role in today’s internet applications. Collaborative Filtering (CF) is one of the popular technique used to design recommendation systems. This technique recommends new content to users based on preferences that the user and similar users have. However, there are some shortcomings to current CF techniques, which affects negatively the performance of the recommendation models. In recent years, deep …
Self-Image Multimedia Technologies For Feedforward Observational Learning, Nkiruka M. A. Uzuegbunam
Self-Image Multimedia Technologies For Feedforward Observational Learning, Nkiruka M. A. Uzuegbunam
Theses and Dissertations--Electrical and Computer Engineering
This dissertation investigates the development and use of self-images in augmented reality systems for learning and learning-based activities. This work focuses on self- modeling, a particular form of learning, actively employed in various settings for therapy or teaching. In particular, this work aims to develop novel multimedia systems to support the display and rendering of augmented self-images. It aims to use interactivity (via games) as a means of obtaining imagery for use in creating augmented self-images. Two multimedia systems are developed, discussed and analyzed. The proposed systems are validated in terms of their technical innovation and their clinical efficacy in …
High-Order Integral Equation Methods For Quasi-Magnetostatic And Corrosion-Related Field Analysis With Maritime Applications, Robert Pfeiffer
High-Order Integral Equation Methods For Quasi-Magnetostatic And Corrosion-Related Field Analysis With Maritime Applications, Robert Pfeiffer
Theses and Dissertations--Electrical and Computer Engineering
This dissertation presents techniques for high-order simulation of electromagnetic fields, particularly for problems involving ships with ferromagnetic hulls and active corrosion-protection systems.
A set of numerically constrained hexahedral basis functions for volume integral equation discretization is presented in a method-of-moments context. Test simulations demonstrate the accuracy achievable with these functions as well as the improvement brought about in system conditioning when compared to other basis sets.
A general method for converting between a locally-corrected Nyström discretization of an integral equation and a method-of-moments discretization is presented next. Several problems involving conducting and magnetic-conducting materials are solved to verify the accuracy …
Uncertainty Estimation Of Deep Neural Networks, Chao Chen
Uncertainty Estimation Of Deep Neural Networks, Chao Chen
Theses and Dissertations
Normal neural networks trained with gradient descent and back-propagation have received great success in various applications. On one hand, point estimation of the network weights is prone to over-fitting problems and lacks important uncertainty information associated with the estimation. On the other hand, exact Bayesian neural network methods are intractable and non-applicable for real-world applications. To date, approximate methods have been actively under development for Bayesian neural networks, including but not limited to: stochastic variational methods, Monte Carlo dropouts, and expectation propagation. Though these methods are applicable for current large networks, there are limits to these approaches with either underestimation …
Authenticating Users With 3d Passwords Captured By Motion Sensors, Jing Tian
Authenticating Users With 3d Passwords Captured By Motion Sensors, Jing Tian
Theses and Dissertations
Authentication plays a key role in securing various resources including corporate facilities or electronic assets. As the most used authentication scheme, knowledgebased authentication is easy to use but its security is bounded by how much a user can remember. Biometrics-based authentication requires no memorization but ‘resetting’ a biometric password may not always be possible. Thus, we propose study several behavioral biometrics (i.e., mid-air gestures) for authentication which does not have the same privacy or availability concerns as of physiological biometrics.
In this dissertation, we first propose a user-friendly authentication system Kin- Write that allows users to choose arbitrary, short and …
Quantitative Forecasting Of Risk For Ptsd Using Ecological Factors: A Deep Learning Application, Nuriel S. Mor, Kathryn L. Dardeck
Quantitative Forecasting Of Risk For Ptsd Using Ecological Factors: A Deep Learning Application, Nuriel S. Mor, Kathryn L. Dardeck
Journal of Social, Behavioral, and Health Sciences
Forecasting the risk for mental disorders from early ecological information holds benefits for the individual and society. Computational models used in psychological research, however, are barriers to making such predictions at the individual level. Preexposure identification of future soldiers at risk for posttraumatic stress disorder (PTSD) and other individuals, such as humanitarian aid workers and journalists intending to be potentially exposed to traumatic events, is important for guiding decisions about exposure. The purpose of the present study was to evaluate a machine learning approach to identify individuals at risk for PTSD using readily collected ecological risk factors, which makes scanning …
A Systematic Approach To Rna-Associated Motif Discovery, Tian Gao, Jiang Shu, Juan Cui
A Systematic Approach To Rna-Associated Motif Discovery, Tian Gao, Jiang Shu, Juan Cui
School of Computing: Faculty Publications
Background: Sequencing-based large screening of RNA-protein and RNA-RNA interactions has enabled the mechanistic study of post-transcriptional RNA processing and sorting, including exosome-mediated RNA secretion. The downstream analysis of RNA binding sites has encouraged the investigation of novel sequence motifs, which resulted in exceptional new challenges for identifying motifs from very short sequences (e.g., small non-coding RNAs or truncated messenger RNAs), where conventional methods tend to be ineffective. To address these challenges, we propose a novel motif-finding method and validate it on a wide range of RNA applications.
Results: We first perform motif analysis on microRNAs and longer RNA fragments from …
Crop Height Estimation With Unmanned Aerial Vehicles, Carrick Detweiler, David Anthony, Sebastian Elbaum
Crop Height Estimation With Unmanned Aerial Vehicles, Carrick Detweiler, David Anthony, Sebastian Elbaum
School of Computing: Faculty Publications
An unmanned aerial vehicle (UAV) can be configured for crop height estimation. In some examples, the UAV includes an aerial propulsion system, a laser scanner configured to face downwards while the UAV is in flight, and a control system. The laser scanner is configured to scan through a two-dimensional scan angle and is characterized by a maxi mum range. The control system causes the UAV to fly over an agricultural field and maintain, using the aerial propulsion system and the laser scanner, a distance between the UAV and a top of crops in the agricultural field to within a programmed …
Utilizing Hypervisor To Enhance Trustzone’S Introspection Capabilities On Non-Secure World, Zhang-Kai Zhang, Zhou-Jun Li, Chun-He Xia, Jin-Xin Ma, Jinhua Cui
Utilizing Hypervisor To Enhance Trustzone’S Introspection Capabilities On Non-Secure World, Zhang-Kai Zhang, Zhou-Jun Li, Chun-He Xia, Jin-Xin Ma, Jinhua Cui
Research Collection School Of Computing and Information Systems
Widely used on the Android phones, the technology of ARM TrustZone divides the hardware resources of Android phones into two worlds:non-secure world and secure world. The Android operating system used by user is running in the non-secure world, while the non-secure world's introspection systems (e.g., KNOX, Hypervisor) that are based on TrustZone are running in the secure world. These introspection systems have the high privilege. They can dynamically check Android kernel integrity and perform memory management of non-secure world instead of Android kernel. But TrustZonecan can not completely introspect the hardware resources (e.g., Cache) of non-secure world because of the …
A Comparison Of Information Technology Mediated Customer Services Between The U.S. And China, Suhong Li, Hal Records, Robert Behling
A Comparison Of Information Technology Mediated Customer Services Between The U.S. And China, Suhong Li, Hal Records, Robert Behling
Information Systems and Analytics Department Faculty Journal Articles
Information technology mediated customer service is a reality of the 21st century. More and more companies have moved their customer services from in store and in person to online through computer or mobile devices. Using 442 responses collected from one USA university (234 responses) and two Chinese universities (208 responses), the study investigates customer preferences over two service delivery models (either in store or online) on five types of purchasing (retail, eating-out, banking, travel and entertainment) and their perception difference in customer service quality between those two delivery models in the U.S. and China. The results show that the majority …
Predicting Happiness - Comparison Of Supervised Machine Learning Techniques Performance On A Multiclass Classification Problem, Dorota Nieciecka
Predicting Happiness - Comparison Of Supervised Machine Learning Techniques Performance On A Multiclass Classification Problem, Dorota Nieciecka
Dissertations
In the modern world, especially in contemporary economies and politics, a population's subjective well-being is a frequent subject of the public debate. As comparisons of happiness levels in different countries are published, different circumstances and their effect on the value of the subjective well-being reported by people are also analysed. However, a significant amount of the research related to subjective well-being and its determinants is still based upon survey answers and employing conventional statistical methods providing details regarding correlations and causality between different factors and subjective well-being. Application of Supervised Machine Learning techniques for prediction of subjective well-being may provide …
Skylens: Visual Analysis Of Skyline On Multi-Dimensional Data, Xun Zhao, Yanhong Wu, Weiwei Cui, Xinnan Du, Yuan Chen, Yong Wang, Dik Lun Lee, Huamin Qu
Skylens: Visual Analysis Of Skyline On Multi-Dimensional Data, Xun Zhao, Yanhong Wu, Weiwei Cui, Xinnan Du, Yuan Chen, Yong Wang, Dik Lun Lee, Huamin Qu
Research Collection School Of Computing and Information Systems
Skyline queries have wide-ranging applications in fields that involve multi-criteria decision making, including tourism, retail industry, and human resources. By automatically removing incompetent candidates, skyline queries allow users to focus on a subset of superior data items (i.e.. the skyline), thus reducing the decision-making overhead. However, users are still required to interpret and compare these superior items manually before making a successful choice. This task is challenging because of two issues. First, people usually have fuzzy, unstable, and inconsistent preferences when presented with multiple candidates. Second, skyline queries do not reveal the reasons for the superiority of certain skyline points …
Hybrid Privacy-Preserving Clinical Decision Support System In Fog-Cloud Computing, Ximeng Liu, Robert H. Deng, Yang Yang, Ngoc Hieu Tran, Shangping Zhong
Hybrid Privacy-Preserving Clinical Decision Support System In Fog-Cloud Computing, Ximeng Liu, Robert H. Deng, Yang Yang, Ngoc Hieu Tran, Shangping Zhong
Research Collection School Of Computing and Information Systems
In this paper, we propose a framework for hybrid privacy-preserving clinical decision support system in fog cloud computing, called HPCS. In HPCS, a fog server uses a lightweight data mining method to securely monitor patients' health condition in real-time. The newly detected abnormal symptoms can be further sent to the cloud server for high-accuracy prediction in a privacy-preserving way. Specifically, for the fog servers, we design a new secure outsourced inner-product protocol for achieving secure lightweight single-layer neural network. Also, a privacy-preserving piecewise polynomial calculation protocol allows cloud server to securely perform any activation functions in multiple-layer neural network. Moreover, …
Management Strategies For Adopting Agile Methods Of Software Development In Distributed Teams, Igor A. Schtein
Management Strategies For Adopting Agile Methods Of Software Development In Distributed Teams, Igor A. Schtein
Walden Dissertations and Doctoral Studies
Between 2003 and 2015, more than 61% of U.S. software development teams failed to satisfy project requirements, budgets, or timelines. Failed projects cost the software industry an estimated 60 billion dollars. Lost opportunities and misused resources are often the result of software development leaders failing to implement appropriate methods for managing software projects. The purpose of this qualitative multiple case study was to explore strategies software development managers use in adopting Agile methodology in the context of distributed teams. The tenets of Agile approach are individual interaction over tools, working software over documentation, and collaboration over a contract. The conceptual …
Reducing Internal Theft And Loss In Small Businesses, Eric L. Luster
Reducing Internal Theft And Loss In Small Businesses, Eric L. Luster
Walden Dissertations and Doctoral Studies
Every year, several documented data breaches happen in the United States, resulting in the exposure of millions of electronic records. The purpose of this single-case study was to explore strategies some information technology managers used to monitor employees and reduce internal theft and loss. The population for this study consisted of 5 information technology managers who work within the field of technology in the southwestern region of the United States. Participants were selected using purposeful sampling. The conceptual framework for this study included elements from information and communication boundary theories. Data were collected from semistructured interviews, company standard operating procedures, …
Strategies For E-Commerce Adoption In A Travel Agency, Anita Smith
Strategies For E-Commerce Adoption In A Travel Agency, Anita Smith
Walden Dissertations and Doctoral Studies
In 2016, online travel sales increased 8%, resulting in profits increasing to over 565 billion U.S. dollars. Traditional travel agencies in brick-and-mortar storefronts are facing challenges related to competing with online travel agencies (OTAs), attracting new customers, and retaining existing customers. The purpose of this qualitative case study was to explore the e-commerce processes, business models, and strategies that leaders of traditional travel agencies use to compete with OTAs. The study sample consisted of 8 travel professionals from 3 small travel agencies located in the mid-Atlantic region of the United States. The conceptual framework for this study was Rogers's diffusion …
Development Of A Locomotion And Balancing Strategy For Humanoid Robots, Emile Bahdi
Development Of A Locomotion And Balancing Strategy For Humanoid Robots, Emile Bahdi
Electronic Theses and Dissertations
The locomotion ability and high mobility are the most distinguished features of humanoid robots. Due to the non-linear dynamics of walking, developing and controlling the locomotion of humanoid robots is a challenging task. In this thesis, we study and develop a walking engine for the humanoid robot, NAO, which is the official robotic platform used in the RoboCup Spl. Aldebaran Robotics, the manufacturing company of NAO provides a walking module that has disadvantages, such as being a black box that does not provide control of the gait as well as the robot walk with a bent knee. The latter disadvantage, …
An Investigation Of The Impact Of A Social Constructivist Teaching Approach, Based On Trigger Questions, Through Measures Of Mental Workload And Efficiency, Federico Gobbo, Luca Longo, Declan O'Sullivan, Giuliano Orru
An Investigation Of The Impact Of A Social Constructivist Teaching Approach, Based On Trigger Questions, Through Measures Of Mental Workload And Efficiency, Federico Gobbo, Luca Longo, Declan O'Sullivan, Giuliano Orru
Conference papers
Social constructivism is grounded on the construction of information with a focus on collaborative learning through social interactions. However, it tends to ignore the human mental architecture, pillar of cognitivism. A characteristic of cognitivism is that instructional designs built upon it are generally explicit, contrarily to constructivism. This position paper proposes a novel learning task that is aimed at combining both the approaches through the use of trigger questions in a collaborative activity executed after a traditional delivery of instructions. To evaluate this new task, a metric of efficiency based upon a measure of mental workload and a measure of …
การลดสัญญาณรบกวนภาพชนิดเกาส์เซียนด้วยวิธีการเรียนรู้เชิงลึกและเส้นแบ่งระหว่างวัตถุกับพื้นหลัง, ศุภกร ชูประภาวรรณ
การลดสัญญาณรบกวนภาพชนิดเกาส์เซียนด้วยวิธีการเรียนรู้เชิงลึกและเส้นแบ่งระหว่างวัตถุกับพื้นหลัง, ศุภกร ชูประภาวรรณ
Chulalongkorn University Theses and Dissertations (Chula ETD)
การลดสัญญาณรบกวนภาพเป็นปัญหาพื้นฐานในงานด้านคอมพิวเตอร์วิชันและได้รับความสนใจในด้านงานวิจัยเป็นอย่างมากในช่วงหลายปีที่ผ่านมาเพื่อที่จะหาวิธีในการลดสัญญาณรบกวนภาพแบบต่าง ๆ โดยในงานวิทยานิพนธ์นี้มุ่งเน้นไปที่งานด้านการลดสัญญาณรบกวนภาพสำหรับสัญญาณรบกวนแบบเกาส์เซียน โดยในปัจจุบันการเรียนรู้เชิงลึกได้ถูกนำมาประยุกต์ใช้กับงานด้านการลดสัญญาณรบกวนภาพแต่ทว่ายังมีข้อจำกัดอยู่คือการเรียนรู้เชิงลึกจะสร้างสิ่งแปลกปลอมขึ้นมาบนภาพ วิทยานิพนธ์นี้เสนอวิธีการใช้การเรียนรู้เชิงลึกร่วมกับเส้นแบ่งระหว่างวัตถุกับพื้นหลัง โดยเส้นแบ่งระหว่างวัตถุกับพื้นหลังนั้นจะได้รับจากอัลกอริทึมแคนนี เอ็จ ดีเท็กชัน (Canny edge detection) เพื่อทำให้โมเดลสามารถกำจัดสิ่งแปลกปลอมได้ สำหรับชุดข้อมูลที่ใช้งานวิจัยคือชุดข้อมูลภาพเบิร์กลีย์ 400 ภาพ (BSD400) สำหรับฝึกสอนโมเดลของผู้วิจัย และชุดข้อมูลทดสอบสำหรับทดสอบคือชุดข้อมูลภาพเบิร์กลีย์ 68 ภาพ (BSD68) และชุดข้อมูลภาพ 12 ภาพ (Set12) โดยจากการทดลองของผู้วิจัยบนชุดข้อมูลทดสอบที่มีระดับความเข้มข้นของสัญญาณรบกวนเกาส์เซียนที่ระดับ 15 25 และ 50 พบว่าโมเดลของผู้วิจัยสามารถทำประสิทธิผลได้ดีบนระดับความเข้มข้นที่ 15 และระดับความเข้มข้นที่ 25 แต่ทว่าบนระดับความเข้มข้นที่ 50 นั้นโมเดลของผู้วิจัยทำประสิทธิผลได้เทียบเท่ากับอัลกอริทึมอื่น และการลดสัญญาณรบกวนภาพจริงนั้นโมเดลของผู้วิจัยสามารถลดสัญญาณรบกวนภาพจริงได้ดีกว่าอัลกอริทึมอื่น
Vulnerability Analysis: Protecting Information In The Iot, Brian Cusack, Feiqiu Zhuang
Vulnerability Analysis: Protecting Information In The Iot, Brian Cusack, Feiqiu Zhuang
Australian Information Security Management Conference
The research was designed to study IoT security vulnerabilities and how to better protect IoT communications. By researching the system a Fitbit uses for communications, this research analyzes and reveals security defects in the IoT architecture. The research first uses a man-in the middle (MITM) attack to intercept and analyze the Fitbit system traffic to identify security weakness. Then uses a replay attack to further validate these flaws. Finally, countermeasures against these security threats are proposed. The research findings show the Fitbit’s IoT communication architecture has serious information security risks. Firstly, the Fitbit tested does not encrypt the raw data …
Mitigating Man-In-The-Middle Attacks On Mobile Devices By Blocking Insecure Http Traffic Without Using Vpn, Kevin Chong, Muhammad Imran Malik, Peter Hannay
Mitigating Man-In-The-Middle Attacks On Mobile Devices By Blocking Insecure Http Traffic Without Using Vpn, Kevin Chong, Muhammad Imran Malik, Peter Hannay
Australian Information Security Management Conference
Mobile devices are constantly connected to the Internet, making countless connections with remote services. Unfortunately, many of these connections are in cleartext, visible to third-parties while in transit. This is insecure and opens up the possibility for man-in-the-middle attacks. While there is little control over what kind of connection running apps can make, this paper presents a solution in blocking insecure HTTP packets from leaving the device. Specifically, the proposed solution works on the device, without the need to tunnel packets to a remote VPN server, and without special privileges such as root access. Speed tests were performed to quantify …
Bringing Defensive Artificial Intelligence Capabilities To Mobile Devices, Kevin Chong, Ahmed Ibrahim
Bringing Defensive Artificial Intelligence Capabilities To Mobile Devices, Kevin Chong, Ahmed Ibrahim
Australian Information Security Management Conference
Traditional firewalls are losing their effectiveness against new and evolving threats today. Artificial intelligence (AI) driven firewalls are gaining popularity due to their ability to defend against threats that are not fully known. However, a firewall can only protect devices in the same network it is deployed in, leaving mobile devices unprotected once they leave the network. To comprehensively protect a mobile device, capabilities of an AI-driven firewall can enhance the defensive capabilities of the device. This paper proposes porting AI technologies to mobile devices for defence against today’s ever-evolving threats. A defensive AI technique providing firewall-like capability is being …