Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 28 for “"Data Leakage"”.
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Preventing data leakage in web services
… using these applications can cause sensitive data leakage both on the server and client. On the server-side, applications collect and analyze sensitive user data to monetize it. Consequently, this sensitive data can leak through data breaches or can be accessed by malicious service providers. …
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Appropriate Methods for Automating the Detection of Data Leakage Prevention Events
In Data Leakage Prevention (DLP), human analysts inspect the legitimacy of suspicious file transfers, which are called alerts. First, the data in question is classified. Then, the transfer context is assessed. After this, the analyst decides whether the alert is classified as an incident or a False …
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Detection of data leakage and disruption of covert timing channel in secure drone communication using machine and deep learning
… timing channels in drones. A comprehensive dataset was meticulously generated from covert channels utilizing the secure Parrot Anafi Ai drone across varying distances, stream sizes, and interarrival times. Machine learning and deep learning models were employed to classify covert and …
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PARTE : automatic program partitioning for efficient computation over encrypted data
Many modern applications outsource their data storage and computation needs to third parties. Although this lifts many infrastructure burdens from the application developer, he must deal with an increased risk of data leakage (i.e. there are more distributed copies of the data, the third party may …
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Images in motion?: a first look into video leakage in federated learning
… as gradients, and never their raw, sensitive data. This approach is fundamental for applications in domains where privacy and confidentiality are important. However, the security of this very mechanism is threatened by gradient inversion attacks, which can reverse-engineer private training …
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Randomized encoding of combinational and sequential logic for resistance to hardware Trojans
… reducing performance or even capturing sensitive data. To date, defensive methods have focused on detection of the Trojan circuitry or prevention through design for security methods.</p><p>This dissertation presents a shift away from prevention and detection to a design methodology wherein one no …
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PassDB : parser for password dump database
… When the hackers are finished using the stolen data, they dump it on the internet in so-called data dumps. The project consisted of building a system that can be used to parse passwords and emails from most data dumps given (i.e., data leakage after security breach) and store them in some …
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Evaluation, Interpretation, and Maintenance of Machine Learning Models for IT Operations
… IT Operations) solutions leverage the massive data generated during the operation of large-scale systems and machine learning models to assist in managing system operations. While prior studies focus on innovative modeling techniques to improve the performance of AIOps models, how to smoothly …
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On the Role of the Source Dataset in Transfer Learning
… in transfer learning including more pre-training data translates into better performance. However, recent evidence suggests that removing data from the source dataset can actually help too. In this work, we take a closer look at the role of the source dataset's composition in transfer learning and …
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Prevention of personally identifiable information leakage in ecommerce using offline data minimization and online pseudonymisation.
… Information (PII) hence making their personal data susceptible to leakage. Despite several solutions being already in use to protect PII, data leakage persists. To enhance PII protection and user privacy, the research proposes employing Offline Data minimization and Pseudonymisation using …
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Prevention of personally identifiable information leakage in ecommerce using offline data minimization and online pseudonymisation.
… Information (PII) hence making their personal data susceptible to leakage. Despite several solutions being already in use to protect PII, data leakage persists. To enhance PII protection and user privacy, the research proposes employing Offline Data minimization and Pseudonymisation using …
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AI-Driven Pig Monitoring System: Behavior and Weight Analysis
… a preprocessing framework that addresses data leakage in time series analysis through non-class-based windowing and chronological sampling, achieving up to 15% improvement in accuracy over conventional methods. For current weight prediction, we develop an automated pipeline using the …
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Machine learning for well rate estimation : integrated imputation and stacked ensemble modeling
… distributed (IID), and exhibit missing data with a not missing at random (MNAR) classification from three different oil fields. This research introduces a novel integrated imputation procedure that combines the imputation model selection with the cross-validation procedure for downstream …
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SMARTPHONE-BASED COMPRESSION-INDUCED IMAGING SYSTEM DATA SECURITY
… app, we obtain tactile images, and we developed data security methodology in this thesis. The first version of the system (SCIS V1) is developed using the symmetric key encryption, which protects all medical data from hackers. AES (Advanced Encryption Standard) encryption method is used to …
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File Tracking For Mobile Devices
… individual user increases, so does the risk of data leakage and loss. This problem has started to draw attention because the data contained on smart devices tends to be personal or sensitive in nature. Many people have so much data on their devices that they have no idea as to what they are …
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Mining Security Risks from Massive Datasets
… confidentiality, integrity, and availability of data and programs. However, new challenges are emerging as the amount of data grows rapidly in the big data era. On one hand, attacks are becoming stealthier by concealing their behaviors in massive datasets. One the other hand, it is becoming more …
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Sneak-peek: high speed covert channels in data center networks
With the advent of big data, modern businesses face an increasing need to store and process large volumes of sensitive customer information on the cloud. In these environments, resources are shared across a multitude of mutually untrusting tenants increasing propensity for data leakage. With the …
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Statistical Evaluation of Deep Learning for Event Detection in Time Series: Quantifying Uncertainty, Efficiency, and Adaptation with Applications to Seismic Data
… a few performance metrics computed on benchmark datasets, which ignores important questions about how predictive performance varies with data availability, how uncertainty is communicated in both predictions and aggregate metrics, and how shifting data distributions impact model reliability. …
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SWE-Bench+: Enhanced Coding Benchmark for LLMs
… contexts, Carlos et al. introduced the SWE-bench dataset, which comprises 2,294 real-world GitHub issues. Several impressive LLM-based toolkits have recently been developed and evaluated on this dataset. However, a systematic evaluation of the quality of SWE-bench remains missing. In this thesis, …
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Variation-Derived Chip Security And Accelerated Simulation Of Variations
… the key.</p> <p>Finally, the anticipated use of leakage-free nonvolatile caches presents a disruption to the processing security assumption that memory values are not retained upon power loss or system reset. To prevent against data leakage, we propose the use of truly random, single boot keys, …
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