Leveraging Stacks of Predictors for Efficient Inference and Uncertainty Estimation

Given the ever growing neural networks being developed and the abundant empirical evidence that model/data scale play an important role in enabling high-quality models of data, inference cost becomes a bottleneck to the deployment of state-of-the-art automated predictors. To address that, this research project aims to develop algorithms that can predict outcomes by combining predictions […]

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Building Security Controls Catalogue for SMEs

Fraud prevention tools play a critical role in real estate transactions. Even though digital fraudsters employ all newly available tools to find loopholes in the existing technological ecosystem, the information systems involved in real estate transactions typically lag behind in terms of digital identity verification and management. In order to facilitate industry adoption of the […]

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Threat actor group profiling

Understanding the current panorama of threat actor groups worldwide is critical to building efficient cybersecurity programs. Information about threat actor groups’ motivations, tools, tactics and techniques they use to attack, and the type of targets they have in their sights provide valuable information to cybersecurity teams. To achieve this goal is essential to generate intelligence […]

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Mining Event Tracing for Windows (ETW)

As cyber adversaries are becoming more creative, analysts are required to figure out more innovative ways to detect them to be able to respond before it’s too late. To detect any underlying threat inside a system, data logs are collected showing events and activities occurring inside the system. Adversaries nowadays are capable of evading detection […]

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Proportion-Based Hypergraph Burning

Graph burning is a mathematical game or process that has applications in financial cyber security, as it can be used to model “dirty money” spreading throughout a network of accounts. Hypergraph burning is a similar process that is played on a more complex network-like structure called a hypergraph. We investigate an alternative rule set for […]

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A framework to enhance deep learning systems’ trustworthiness against Out of Distribution examples

In the past decade, deep learning models have demonstrated their highest performance for a variety of tasks. These models outperformed classical machine learning models and even humans in terms of performance and accuracy. However, previous research indicated that these models are vulnerable to out-of-distribution and adversarial inputs. Ideally, these inputs should be rejected by the […]

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Tiresias: Client Private Malware Protection

Tiresias is a client private solution to malware protection and threat intelligence. Tiresias allows a user to put all their incoming files in a cryptographically secure Data Chest locally. After sending the Data Chest to our cloud environment, our AI scans and infers if it is malicious without seeing the actual file content from the […]

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A novel phishing detection approach using Fuzzy Logic and Deep Learning

People are switching from traditional shopping to internet commerce as Internet access increases quickly. So nowadays people are becoming more dependent on e-commerce-based websites. On the other hand, instead of robbing businesses like banks and stores, modern thieves now use the anonymous internet architecture to track down their victims online. Hackers are employing new strategies, […]

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Anonymous Age Verification Using Electrocardiogram (ECG) Obtained from Smart Wearables

Age-verification mandatory procedure for delivering certain services and products. Traditionally, identification documents have been a common mechanism of age-verification. However, this current strategy is subject to certain risks regarding privacy protection and online forgery. This demonstrates the value in anonymous age verification schemes using biometrics. Considering its age-dependent attributes, Electrocardiogram (ECG) is a potential solution. […]

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Development of a research prototype user interface for secure data sharing

In this project, we are trying to expose our existing core system functionalities to a public user interface. We will design, implement and test a research prototype user interface that can provide simple and flexible content sharing over a web-based user interface (UI) for organizations such as healthcare or surveillance systems that require a mechanism […]

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Improving predictive maintenance of marine vessels based on digital twin’s remote real-time monitoring system in the maritime 4.0 era

The master’s degree thesis will be on developing digital twin remote real-time monitoring systems to improve the predictive maintenance of in-service equipment on marine/offshore vessels. This will result in safer sailing because it will be possible to predict when and where failures occur, so that the appropriate corrective actions are initiated in time.

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Preserving Privacy at Edge Devices

The aim of this project is to develop an application that can proactively protect users from identity theft and create awareness around safe digital practices. For this, we will be developing novel ways of extracting utility out of data and helping users to maintain a least-risk profile score. Most of the computations will be done […]

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