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01/24/2023
XRP-NDN Overlay: Improving the Communication Efficiency of Consensus-Validation based Blockchains with an NDN Overlay
With the growing adoption of Distributed Ledger Technologies and the sub...
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06/21/2022
Deep dive into Interledger: Understanding the Interledger ecosystem
At the technical level, the goal of Interledger is to provide an archite...
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06/08/2022
A Flash(bot) in the Pan: Measuring Maximal Extractable Value in Private Pools
The rise of Ethereum has lead to a flourishing decentralized marketplace...
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05/02/2022
Topology Analysis of the XRP Network
XRP is one of the oldest, well-established cryptocurrencies. Despite the...
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10/18/2021
SPON: Enabling Resilient Inter-Ledgers Payments with an Intrusion-Tolerant Overlay
Payment systems are a critical component of everyday life in our society...
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08/23/2021
Elysium: Automagically Healing Vulnerable Smart Contracts Using Context-Aware Patching
Smart contracts are programs that are deployed and executed on the block...
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05/31/2021
Know Your Model (KYM): Increasing Trust in AI and Machine Learning
The widespread utilization of AI systems has drawn attention to the pote...
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02/05/2021
Frontrunner Jones and the Raiders of the Dark Forest: An Empirical Study of Frontrunning on the Ethereum Blockchain
Ethereum prospered the inception of a plethora of smart contract applica...
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01/15/2021
The Eye of Horus: Spotting and Analyzing Attacks on Ethereum Smart Contracts
In recent years, Ethereum gained tremendously in popularity, growing fro...
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05/25/2020
Towards Smart Hybrid Fuzzing for Smart Contracts
Smart contracts are Turing-complete programs that are executed across a ...
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05/07/2020
Minority Class Oversampling for Tabular Data with Deep Generative Models
In practice, data scientists are often confronted with imbalanced data. ...
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03/20/2020
Blockchain Governance: An Overview and Prediction of Optimal Strategies using Nash Equilibrium
Blockchain governance is a subject of ongoing research and an interdisci...
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10/03/2019
A Data Science Approach for Honeypot Detection in Ethereum
Ethereum smart contracts have recently drawn a considerable amount of at...
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08/26/2019
SynGAN: Towards Generating Synthetic Network Attacks using GANs
The rapid digital transformation without security considerations has res...
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05/23/2019
PHom-GeM: Persistent Homology for Generative Models
Generative neural network models, including Generative Adversarial Netwo...
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05/23/2019
User-Device Authentication in Mobile Banking using APHEN for Paratuck2 Tensor Decomposition
The new financial European regulations such as PSD2 are changing the ret...
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05/23/2019
Non-Negative PARATUCK2 Tensor Decomposition Combined to LSTM Network For Smart Contracts Profiling
Smart contracts are programs stored and executed on a blockchain. The Et...
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02/28/2019
Infer Your Enemies and Know Yourself, Learning in Real-Time Bidding with Partially Observable Opponents
Real-time bidding, as one of the most popular mechanisms for selling onl...
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02/27/2019
Improving Missing Data Imputation with Deep Generative Models
Datasets with missing values are very common on industry applications, a...
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07/03/2018
Generating Multi-Categorical Samples with Generative Adversarial Networks
We propose a method to train generative adversarial networks on mutivari...
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03/02/2018
Impact of Biases in Big Data
The underlying paradigm of big data-driven machine learning reflects the...
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01/17/2018
On the Reduction of Biases in Big Data Sets for the Detection of Irregular Power Usage
In machine learning, a bias occurs whenever training sets are not repres...
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09/09/2017
Identifying Irregular Power Usage by Turning Predictions into Holographic Spatial Visualizations
Power grids are critical infrastructure assets that face non-technical l...
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07/28/2017
Human in the Loop: Interactive Passive Automata Learning via Evidence-Driven State-Merging Algorithms
We present an interactive version of an evidence-driven state-merging (E...
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03/29/2017
The Top 10 Topics in Machine Learning Revisited: A Quantitative Meta-Study
Which topics of machine learning are most commonly addressed in research...
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02/13/2017
Is Big Data Sufficient for a Reliable Detection of Non-Technical Losses?
Non-technical losses (NTL) occur during the distribution of electricity ...
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11/21/2016
Interpreting Finite Automata for Sequential Data
Automaton models are often seen as interpretable models. Interpretabilit...
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07/04/2016
Neighborhood Features Help Detecting Non-Technical Losses in Big Data Sets
Electricity theft is a major problem around the world in both developed ...
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02/26/2016
