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Articles 2611 - 2640 of 20641
Full-Text Articles in Entire DC Network
Toward Effective Secure Code Reviews: An Empirical Study Of Security-Related Coding Weaknesses, Wachiraphan Charoenwet, Patanamon Thongtanunam, Thuan Pham, Christoph Treude
Toward Effective Secure Code Reviews: An Empirical Study Of Security-Related Coding Weaknesses, Wachiraphan Charoenwet, Patanamon Thongtanunam, Thuan Pham, Christoph Treude
Research Collection School Of Computing and Information Systems
Identifying security issues early is encouraged to reduce the latent negative impacts on software systems. Code review is a widely-used method that allows developers to manually inspect modified code, catching security issues during a software development cycle. However, existing code review studies often focus on known vulnerabilities, neglecting coding weaknesses, which can introduce real-world security issues that are more visible through code review. The practices of code reviews in identifying such coding weaknesses are not yet fully investigated. To better understand this, we conducted an empirical case study in two large open-source projects, OpenSSL and PHP. Based on 135,560 code …
Reinforcement Learning Based Proactive Entanglement Swapping For Quantum Networks, Tasdiqul Islam, Md Arifuzzaman, Engin Arslan
Reinforcement Learning Based Proactive Entanglement Swapping For Quantum Networks, Tasdiqul Islam, Md Arifuzzaman, Engin Arslan
Computer Science Faculty Research & Creative Works
Entanglement generation and swapping is a difficult process due to probabilistic nature of quantum mechanics. To overcome this issue, existing quantum routing algorithms try to create entanglement on multiple paths between source and destination. Although it is possible to save entangled qubits on unused links using quantum memories, the quantum routing algorithms discard them and try creating new entanglement in each time slot. In this work, we leverage the longevity of entanglement and introduce two enhancements to improve the performance of existing routing algorithms: (i) The generation and caching of entanglements across multiple time slots, and (ii) the proactively executing …
Predicting Iot Distributed Ledger Fraud Transactions With A Lightweight Gan Network, Charles Rawlins, Jagannathan Sarangapani
Predicting Iot Distributed Ledger Fraud Transactions With A Lightweight Gan Network, Charles Rawlins, Jagannathan Sarangapani
Electrical and Computer Engineering Faculty Research & Creative Works
Decision-making and consensus in traditional blockchain protocols is formulated as a repeated Bernoulli trial that solves a computationally intense lottery puzzle, called Proof-of-Work (PoW) in Bitcoin. This approach has shown robustness through practice but does not scale with increasing network size and generation of new transactions. Resource constrained Internet of Things (IoT) networks are incompatible with full computation of schemes like Bitcoin's PoW. Our effort proposes a first step towards an alternative consensus using machine learning-based decision-making with prediction of fraud transactions to alleviate need for intense computation. To improve base approval probabilities for fraud detection in an ideal security …
Effective Data Sharing In An Edge-Cloud Model: Security Challenges And Solutions, Arijit Karati, Sajal K. Das
Effective Data Sharing In An Edge-Cloud Model: Security Challenges And Solutions, Arijit Karati, Sajal K. Das
Computer Science Faculty Research & Creative Works
The proposed protocol offers privacy-preserving authentication across several cloud platforms, flexible key management for consumer data protection, and effective user revocation. Performance evaluation demonstrates that the proposed framework supports low latency, safe unified remote access, and data privacy in the contemporary edge-enabled environment.
Transformer Models With Explainability For It Telemetry And Business Events, Shiau Hong Lim, Laura Wynter
Transformer Models With Explainability For It Telemetry And Business Events, Shiau Hong Lim, Laura Wynter
Research Collection School Of Computing and Information Systems
Temporal event data are commonly encountered in software applications across a wide range of domains, from IT telemetry and system logs to business process automation. Temporal event data in software applications carry information in various forms: both structured and unstructured, and with both regular and irregular occurrence frequency, making the representation of temporal event data challenging. Further chal-lenges come from the diversity in terms of the scale and volume of events that need to be summarized by the representation. We propose a general and unified approach to handle temporal event data for the purpose of learning a predictive transformer model. …
Reproducibility Debt: Challenges And Future Pathways, Zara Hassan, Christoph Treude, Michael Norrish, Graham Williams, Alex Potanin
Reproducibility Debt: Challenges And Future Pathways, Zara Hassan, Christoph Treude, Michael Norrish, Graham Williams, Alex Potanin
Research Collection School Of Computing and Information Systems
Reproducibility of scientic computation is a critical factor in validating its underlying process, but it is often elusive. Complexity and continuous evolution in software systems have introduced new challenges for reproducibility across a myriad of computational sciences, resulting in growing debt. This requires a comprehensive domain-agnostic study to dene and asses Reproducibility Debt (RpD) in scientic software, thus uncovering and classifying all underlying factors attributed towards its emergence and identication i.e., causes and eects. Moreover, an organised map of prevention strategies is imperative to guide researchers for its proactive management. This vision paper highlights the challenges that hinder eective management …
Generalization Analysis Of Deep Nonlinear Matrix Completion, Antoine Ledent, Rodrigo Alves
Generalization Analysis Of Deep Nonlinear Matrix Completion, Antoine Ledent, Rodrigo Alves
Research Collection School Of Computing and Information Systems
We provide generalization bounds for matrix completion with Schatten $p$ quasi-norm constraints, which is equivalent to deep matrix factorization with Frobenius constraints. In the uniform sampling regime, the sample complexity scales like $\widetilde{O}\left( rn\right)$ where $n$ is the size of the matrix and $r$ is a constraint of the same order as the ground truth rank in the isotropic case. In the distribution-free setting, the bounds scale as $\widetilde{O}\left(r^{1-\frac{p}{2}}n^{1+\frac{p}{2}}\right)$, which reduces to the familiar $\sqrt{r}n^{\frac{3}{2}}$ for $p=1$. Furthermore, we provide an analogue of the weighted trace norm for this setting which brings the sample complexity down to $\widetilde{O}(nr)$ in all …
Secure And Flexible Wildcard Queries, Qing Wang, Donghui Hu, Meng Li, Guomin Yang
Secure And Flexible Wildcard Queries, Qing Wang, Donghui Hu, Meng Li, Guomin Yang
Research Collection School Of Computing and Information Systems
Wildcard Keyword Searchable Encryption (WKSE) enables users to search desired encrypted files with wildcard queries. Previous schemes only enabled single-character wildcard queries or restricted multi-character wildcard queries. Even if the two types of queries are supported by several schemes, they are vulnerable to correlation attacks and composition attacks. In this paper, we propose a WKSE scheme Secure Flexible Wildcard Queries (SFWQ) that supports highly flexible wildcard queries and resists correlation and composition attacks. Specifically, we adopt the interval matching method instead of traditional position matching, so that SFWQ supports a variety of queries, including single-character wildcard queries, multi-character wildcard queries, …
Evilscreen Attack: Smart Tv Hijacking Via Multi-Channel Remote Control Mimicry, Yiwei Zhang, Siqi Ma, Tiancheng Chen, Juanru Li, Robert H. Deng, Elisa Bertino
Evilscreen Attack: Smart Tv Hijacking Via Multi-Channel Remote Control Mimicry, Yiwei Zhang, Siqi Ma, Tiancheng Chen, Juanru Li, Robert H. Deng, Elisa Bertino
Research Collection School Of Computing and Information Systems
Modern smart TVs often communicate with their remote controls (including the smartphone simulated ones) using multiple wireless channels (e.g., Infrared, Bluetooth, and Wi-Fi). However, this multi-channel remote control communication introduces a new attack surface. An inherent security flaw is that remote controls of most smart TVs are designed to work in a benign environment rather than an adversarial one, and thus wireless communications between a smart TV and its remote controls are not strongly protected. Attackers can leverage such a flaw to abuse the remote control communication and compromise smart TV systems. In this paper, we propose EvilScreen, a novel …
Mtdscout : Complementing The Identification Of Insecure Methods In Android Apps Via Source-To-Bytecode Signature Generation And Tree-Based Layered Search, Zicheng Zhang, Haoyu Ma, Daoyuan Wu, Debin Gao, Xiao Yi, Yufan Chen, Yan Wu, Lingxiao Jiang
Mtdscout : Complementing The Identification Of Insecure Methods In Android Apps Via Source-To-Bytecode Signature Generation And Tree-Based Layered Search, Zicheng Zhang, Haoyu Ma, Daoyuan Wu, Debin Gao, Xiao Yi, Yufan Chen, Yan Wu, Lingxiao Jiang
Research Collection School Of Computing and Information Systems
Modern Android apps consist of both host app code and third-party libraries. Traditional static analysis tools conduct taint analysis for API misuses on the entire app code, while third-party library (TPL) detection tools focus solely on library code. Both approaches, however, are prone to some inherent false negatives: taint analysis tools may neglect third-party libraries or face timeouts/errors in whole app-based analysis, and TPL detection tools are not designed for pinpointing specific vulnerable methods. These challenges underscore the need for enhanced identification of insecure methods in Android apps, particularly for app markets addressing open-source security incidents. In this paper, we …
Fine-Grained Passenger Load Prediction Inside Metro Network Via Smart Card Data, Xiancai Tian, Chen Zhang, Baihua Zheng
Fine-Grained Passenger Load Prediction Inside Metro Network Via Smart Card Data, Xiancai Tian, Chen Zhang, Baihua Zheng
Research Collection School Of Computing and Information Systems
Metro system serves as the backbone for urban public transportation. Accurate passenger load prediction for the metro system plays a crucial role in metro service quality improvement, such as helping operators schedule train timetables and passengers plan their trips. However, existing works can only predict low-grained passenger flows of origin-destination (O-D) paths or inflows/outflows of each station but cannot predict passenger load distribution over the whole metro network. To this end, this paper proposes an end-to-end inference framework, PIPE, for passenger load prediction of every metro segment between two adjacent stations, by only utilizing smart card data. In particular, PIPE …
Verifiable Outsourced Attribute-Based Encryption Scheme For Cloud-Assisted Mobile E-Health System, Yinbin Miao, Feng Li, Xinghua Li, Jianting Ning, Hongwei Li, Kim-Kwang Raymond Choo, Robert H. Deng
Verifiable Outsourced Attribute-Based Encryption Scheme For Cloud-Assisted Mobile E-Health System, Yinbin Miao, Feng Li, Xinghua Li, Jianting Ning, Hongwei Li, Kim-Kwang Raymond Choo, Robert H. Deng
Research Collection School Of Computing and Information Systems
The cloud-assisted mobile electronic health (e-health) system facilitates e-health data sharing between healthcare providers and patients, but also raises the security and privacy concerns of e-health data. Although Ciphertext-Policy Attribute-Based Encryption (CP-ABE) has been a promising technique to achieve fine-grained access control over encrypted e-health data, it still incurs high encryption and decryption burdens on mobile users such as smartphones and sensors. In addition, malicious cloud servers may conduct incorrect operations due to various interest incentives (e.g., leaking sensitive information to illegal users, saving computation and storage costs). To solve the above issues, in this paper we first propose an …
Privacy-Preserved Data Trading Via Verifiable Data Disturbance, Man Zhang, Xinghua Li, Yanbing Ren, Bin Luo, Yinbin Miao, Ximeng Liu, Robert H. Deng
Privacy-Preserved Data Trading Via Verifiable Data Disturbance, Man Zhang, Xinghua Li, Yanbing Ren, Bin Luo, Yinbin Miao, Ximeng Liu, Robert H. Deng
Research Collection School Of Computing and Information Systems
To motivate data owner (DO) to trade data, the existing data trading allows DO to sell the disturbed data to the data consumer (DC), where the disturbance parameter and the data price are negotiated by them, and DO independently adds the disturbance noise to data (usually continuous type) following the negotiation result. However, DOs may violate the negotiated parameter and add more noise to data while obtaining the negotiated price, which damages DC's disturbed data availability. This deficiency is rooted in the absence of supervision and verifiability on DOs’ independent disturbances. Aiming at the above problem, we devise a privacy-preserved …
Diffusion Models For Generative Outfit Recommendation, Yiyan Xu, Wenjie Wang, Fuli Feng, Yunshan Ma, Jizhi Zhang, Xiangnan He
Diffusion Models For Generative Outfit Recommendation, Yiyan Xu, Wenjie Wang, Fuli Feng, Yunshan Ma, Jizhi Zhang, Xiangnan He
Research Collection School Of Computing and Information Systems
Outfit Recommendation (OR) in the fashion domain has evolved through two stages: Pre-defined Outfit Recommendation and Personalized Outfit Composition. However, both stages are constrained by existing fashion products, limiting their effectiveness in addressing users' diverse fashion needs. Recently, the advent of AI-generated content provides the opportunity for OR to transcend these limitations, showcasing the potential for personalized outfit generation and recommendation.To this end, we introduce a novel task called Generative Outfit Recommendation (GOR), aiming to generate a set of fashion images and compose them into a visually compatible outfit tailored to specific users. The key objectives of GOR lie in …
Towards Automated Slide Augmentation To Discover Credible And Relevant Links, Dilan Dinushka Senarath Arachchige, Christopher M. Poskitt, Kwan Chin (Xu Guangjin) Koh, Heng Ngee Mok, Hady Wirawan Lauw
Towards Automated Slide Augmentation To Discover Credible And Relevant Links, Dilan Dinushka Senarath Arachchige, Christopher M. Poskitt, Kwan Chin (Xu Guangjin) Koh, Heng Ngee Mok, Hady Wirawan Lauw
Research Collection School Of Computing and Information Systems
Learning from concise educational materials, such as lecture notes and presentation slides, often prompts students to seek additional resources. Newcomers to a subject may struggle to find the best keywords or lack confidence in the credibility of the supplementary materials they discover. To address these problems, we introduce Slide++, an automated tool that identifies keywords from lecture slides, and uses them to search for relevant links, videos, and Q&As. This interactive website integrates the original slides with recommended resources, and further allows instructors to 'pin' the most important ones. To evaluate the effectiveness of the tool, we trialled the system …
Microkarta: Visualising Microservice Architectures, Oscar Manglaras, Alex Farkas, Peter Fule, Christoph Treude, Markus Wagner
Microkarta: Visualising Microservice Architectures, Oscar Manglaras, Alex Farkas, Peter Fule, Christoph Treude, Markus Wagner
Research Collection School Of Computing and Information Systems
Conceptualising and debugging a microservice architecture can be a challenge for developers due to the complex topology of inter-service communication, which may only apparent when viewing the architecture as a whole. In this paper, we present MicroKarta, a dashboard containing three types of network diagram that visualise complex microservice architectures, and that are designed to address problems faced by developers of these architectures. Initial feedback from industry developers has been positive. This dashboard can be used by developers to explore and debug microservice architectures, and can be used to compare the effectiveness of different types of network visualisation for assisting …
Partial Solution Based Constraint Solving Cache In Symbolic Execution, Ziqi Shuai, Zhenbang Chen, Kelin Ma, Kunlin Liu, Yufeng Zhang, Jun Sun, Ji Wang
Partial Solution Based Constraint Solving Cache In Symbolic Execution, Ziqi Shuai, Zhenbang Chen, Kelin Ma, Kunlin Liu, Yufeng Zhang, Jun Sun, Ji Wang
Research Collection School Of Computing and Information Systems
Constraint solving is one of the main challenges for symbolic execution. Caching is an effective mechanism to reduce the number of the solver invocations in symbolic execution and is adopted by many mainstream symbolic execution engines. However, caching can not perform well on all programs. How to improve caching’s effectiveness is challenging in general. In this work, we propose a partial solution-based caching method for improving caching’s effectiveness. Our key idea is to utilize the partial solutions inside the constraint solving to generate more cache entries. A partial solution may satisfy other constraints of symbolic execution. Hence, our partial solution-based …
A Bottom-Up Multi-Disciplinary Approach For Sustainability Education: Un-Sdg 13.3, Benjamin Gan, Thomas Menkhoff, Eng Lieh Ouh, Kevin Cheong
A Bottom-Up Multi-Disciplinary Approach For Sustainability Education: Un-Sdg 13.3, Benjamin Gan, Thomas Menkhoff, Eng Lieh Ouh, Kevin Cheong
Research Collection School Of Computing and Information Systems
Teaching both information systems and business undergraduates to break the current inertia in sustainability action requires innovative teaching & learning approaches as well as inter-disciplinary knowledge inputs. This study presents a bottom-up T&L approach delivered by a group of educators from different disciplines aimed at addressing UN-SDG Goal 13 ‘Climate Action’ with a novel approach. Integrating a problem-centric community project assignment into existing courses, our students worked on different disciplinary elements such as persuasive technologies and awareness campaigns to help to address local sustainability initiatives by community partners. We collected data to measure how students’ motivation, engagement, teamwork, and community …
Exploring The Market Impact Of Web3 Identity Imitation In Ethereum Name Service, Ping Fan Ke, Yi Meng Lau
Exploring The Market Impact Of Web3 Identity Imitation In Ethereum Name Service, Ping Fan Ke, Yi Meng Lau
Research Collection School Of Computing and Information Systems
Digital identities are paramount in today’s digital landscape. However, in the Web3 ecosystem, the absence of a central governing body leaves digital identities, such as domain names, vulnerable to cybersquatting and identity imitation. This study examines the market impact of identity imitation in the Web3 ecosystem. By scrutinizing trading activities within Web3 domain names from Ethereum Name Service (ENS) and its imitator, "Ether Name Service," we found that the presence of a newly imitating domain name increases the subsequent resale value of the authentic domain name. Additionally, we find a positive correlation between the resale value of the imitating domain …
Jigsaw: Edge-Based Streaming Perception Over Spatially Overlapped Multi-Camera Deployments, Ila Gokarn, Yigong Hu, Tarek Abdelzaher, Archan Misra
Jigsaw: Edge-Based Streaming Perception Over Spatially Overlapped Multi-Camera Deployments, Ila Gokarn, Yigong Hu, Tarek Abdelzaher, Archan Misra
Research Collection School Of Computing and Information Systems
We present JIGSAW, a novel system that performs edge-based streaming perception over multiple video streams, while additionally factoring in the redundancy offered by the spatial overlap often exhibited in urban, multi-camera deployments. To assure high streaming throughput, JIGSAW extracts and spatially multiplexes multiple regions-of-interest from different camera frames into a smaller canvas frame. Moreover, to ensure that perception stays abreast of evolving object kinematics, JIGSAW includes a utility-based weighted scheduler to preferentially prioritize and even skip object-specific tiles extracted from an incoming stream of camera frames. Using the CityflowV2 traffic surveillance dataset, we show that JIGSAW can simultaneously process 25 …
Cloud Computation & Beyond, Yassine Chahid, Patrick Slattery
Cloud Computation & Beyond, Yassine Chahid, Patrick Slattery
Publications and Research
This research aims to explore the advancements in cloud computing and their potential influences on other technologies, and which advancements in computer networking facilitate them. These technologies are rapidly progressing in power and complexity, thereby altering how institutions and the public access information. Cloud computing provides a service that enables hardware with limited capabilities to overcome the limitations of on-device components. Due to its reliance on device connections, networking technology serves as the backbone of its operation. The research method encompasses reviewing various publications to understand how networking infrastructure facilitates cloud solutions, and how improvements in relevant hardware can expand …
Empowering Informed Decision-Making In Mental Health Care: A Web-Based Recommendation System For Mobile App Selection, Md Romael Haque
Empowering Informed Decision-Making In Mental Health Care: A Web-Based Recommendation System For Mobile App Selection, Md Romael Haque
Dissertations (1934 -)
In 2022, 23.1% of adults in the United States (77 million individuals) were affected by mental health (MH) concerns. Due to the inaccessibility and high cost of traditional treatment, around 55% of people with severe mental illnesses do not receive treatment. Mental health concerns are prevalent, affecting a significant portion of the population in the United States. Traditional treatment options are often inaccessible and expensive, leaving many people without essential mental healthcare. However, the rise of mobile technologies has given rise to a promising solution: mobile mental health applications (MMHAs). These apps offer greater accessibility and affordability, potentially expanding mental …
Hyper-Dimensional Computing And Its Applications In Tinyml, Ellis A. Weglewski
Hyper-Dimensional Computing And Its Applications In Tinyml, Ellis A. Weglewski
Scholarly Horizons: University of Minnesota, Morris Undergraduate Journal
As computing systems enter the realm of nano form levels, new fields of computational development have spawned, each posing their own set of challenges. Amongst these fields is Tiny Machine Learning (tinyML), which aims to install machine learning on tiny embedded systems. The restrictions imposed upon algorithms by the limited hardware of nano-scale tiny systems make contemporary approaches to machine learning non-contenders. Hyperdimensional computing is an approach to representing data as high-dimensional vectors which allows for one-pass encoding and quick all-encompassing comparison operations via an associative memory. This approach is power-efficient, robust, and can be done in-memory, all of which …
Application Of Driving Simulation Technology In Calibration Of Traffic Simulation Parameters, Shikun Liu, Yi Tang, Yonghong Liu
Application Of Driving Simulation Technology In Calibration Of Traffic Simulation Parameters, Shikun Liu, Yi Tang, Yonghong Liu
Journal of System Simulation
Abstract: To address the insufficient accuracy in traffic simulation modeling due to the lack of in-depth consideration of complex driving behaviors, a calibration method for traffic simulation parameters based on driving simulation technology is proposed. The reconstruction and expansion project of Shenzhen Bao'an International Airport Expressway is selected as the case. Using VISSIM simulation software, a comprehensive traffic simulation model of the entire route is constructed, and UC-winRoad software is employed to create the highly realistic driving simulation scenarios. Driving simulation experiments are conducted to extract the typical driving behavior characteristics in complex scenarios. Calibration functions for simulation parameters are …
The Confluence, Volume3, Issue 2, Full Issue
An Inference-Centric Approach To Natural Language Processing And Cognitive Modeling, Animesh Nighojkar
An Inference-Centric Approach To Natural Language Processing And Cognitive Modeling, Animesh Nighojkar
USF Tampa Graduate Theses and Dissertations
Reasoning over natural text is highly nuanced, and interpretations can vary widely depending on cultural background, financial status, age, gender, or even mood. This doctoral dissertation seeks to not only mimic human reasoning behaviors but also improve the task used in natural language processing (NLP) to capture naturalistic reasoning, known as the Natural Language Inference (NLI) task. NLI involves determining whether a hypothesis is true (entailment), false (contradiction), or indeterminate (neutral) based on a given premise. Initially, we will investigate the extent to which NLP systems designed to capture semantic equivalence actually measure meaning equivalence. After establishing that they do …
Reimagining Web Design: Empowering Agency Of Specialized Audiences Through User-Centered Heuristics, Haley Jones
Reimagining Web Design: Empowering Agency Of Specialized Audiences Through User-Centered Heuristics, Haley Jones
USF Tampa Graduate Theses and Dissertations
This research seeks to create an alternative model for website design that interrogates standardized, linear ways of knowing and being by placing the audience at the center of the web design process. This research contributed a reimagined approach to traditional and standardized web design heuristics by considering an audience-centric methodology that was practical and applicable for web design praxis to create equitable user experiences which can empower audiences to recall their own knowledge and experience to make meaning for themselves through a reimagining of knowledge-making processes in a network of digitized information. In perceiving the rhetorical choice in design of …
How Do Preservice Teachers Learn To Teach Integrated Computational Thinking?: Evidence From Planning, Enactment, And Reflection, Rachael Dektor, Samuel Severance, Kip Téllez
How Do Preservice Teachers Learn To Teach Integrated Computational Thinking?: Evidence From Planning, Enactment, And Reflection, Rachael Dektor, Samuel Severance, Kip Téllez
Journal of Computer Science Integration
This study examines pre-service teachers’ (PSTs) beliefs and understandings about computational thinking (CT) integration and lesson implementation over time. Utilizing a design-based research approach, 3 PSTs led the co-design of integrated CT lessons with support from researchers and enacted these CT integrated lessons with K-5 students. All PSTs participated in a whole-group CT workshop and engaged in one-on-one lesson design sessions with a researcher. We utilized a grounded theory approach to qualitatively analyze pre-surveys, semi-structured interviews, and video data of three PSTs enacting their lessons. We found that PSTs’ initial beliefs about CT instruction – including the importance of it …
Improving Flextype: Ambiguous Text Input For Users With Visual Impairments, Dylan Gaines, Keith Vertanen
Improving Flextype: Ambiguous Text Input For Users With Visual Impairments, Dylan Gaines, Keith Vertanen
Michigan Tech Publications
We present an improved version of the FlexType interface for nonvisual text input. FlexType enables nonvisual text input on mobile touchscreen devices by allowing users to select from a small number of character groups with gestures instead of targeting letters at specific screen locations. Based on an interview with users who are blind or low vision, we added a letter-entry mode to enable easier entry of difficult words such as proper nouns. We conducted a longitudinal study with users who are legally blind to compare FlexType to users' typical text input methods. While we found FlexType was significantly slower than …
Specification, Enforcement, And Measurement Of Integrity Policies, Kevin Dennis
Specification, Enforcement, And Measurement Of Integrity Policies, Kevin Dennis
USF Tampa Graduate Theses and Dissertations
The first step to improving an organization's security posture is to define the organization's security goals. At a technical level, these goals are expressed as security policies. Security policies are predicates over programs, that return true or false if the program adheres to the policy. Defining these policies correctly is thus essential to ensuring the overarching security goals are met, but it is often quite difficult to translate human-oriented goals into their technical policy counterparts. In addition, these policies must be specified so that they are enforceable while minimizing false positives and false negatives. Integrity policies, which specify how data …