References of "State, Radu 50003137"
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See detailPHom-GeM: Persistent Homology for Generative Models
Charlier, Jérémy Henri J. UL; State, Radu UL; Hilger, Jean UL

in The 6th Swiss Conference on Data Science (2019)

Generative neural network models, including Generative Adversarial Network (GAN) and Auto-Encoders (AE), are among the most popular neural network models to generate adversarial data. The GAN model is ... [more ▼]

Generative neural network models, including Generative Adversarial Network (GAN) and Auto-Encoders (AE), are among the most popular neural network models to generate adversarial data. The GAN model is composed of a generator that produces synthetic data and of a discriminator that discriminates between the generator’s output and the true data. AE consist of an encoder which maps the model distribution to a latent manifold and of a decoder which maps the latent manifold to a reconstructed distribution. However, generative models are known to provoke chaotically scattered reconstructed distribution during their training, and consequently, incomplete generated adversarial distributions. Current distance measures fail to address this problem because they are not able to acknowledge the shape of the data manifold, i.e. its topological features, and the scale at which the manifold should be analyzed. We propose Persistent Homology for Generative Models, PHom-GeM, a new methodology to assess and measure the distribution of a generative model. PHom-GeM minimizes an objective function between the true and the reconstructed distributions and uses persistent homology, the study of the topological features of a space at different spatial resolutions, to compare the nature of the true and the generated distributions. Our experiments underline the potential of persistent homology for Wasserstein GAN in comparison to Wasserstein AE and Variational AE. The experiments are conducted on a real-world data set particularly challenging for traditional distance measures and generative neural network models. PHom-GeM is the first methodology to propose a topological distance measure, the bottleneck distance, for generative models used to compare adversarial samples in the context of credit card transactions. [less ▲]

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See detailMint Centrality: A Centrality Measure for the Bitcoin Transaction Graph
Fiz Pontiveros, Beltran UL; Steichen, Mathis UL; State, Radu UL

Poster (2019, May 17)

In this work, we consider the graph of confirmed transactions in Bitcoin. Understanding this graph is essential to discern the different economic activities conducted by the pseudonymous actors. In ... [more ▼]

In this work, we consider the graph of confirmed transactions in Bitcoin. Understanding this graph is essential to discern the different economic activities conducted by the pseudonymous actors. In addition to traditional graph analysis methods, new metrics need to be engineered specifically for the bitcoin transaction graph. Hence, we propose a new centrality measure named mint centrality. The measure uses the inherent tree structure of transactions in bitcoin and their relation to the corresponding set of coinbase transactions, and can be evaluated with linear complexity. We evaluate the mint centrality on the first 200,000 blocks of the public bitcoin blockchain. [less ▲]

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See detailDemo: Blockchain for the Simplification and Automation of KYC Result Sharing
Norvill, Robert UL; Steichen, Mathis UL; Shbair, Wazen UL et al

in IEEE International Conference on Blockchain and Cryptocurrency (ICBC 2019) (2019, May 14)

Know Your Customer (KYC) processes performed by banks on their customers are redundant, cumbersome and costly. Therefore, a system is proposed to automate menial tasks and allow sharing of data related to ... [more ▼]

Know Your Customer (KYC) processes performed by banks on their customers are redundant, cumbersome and costly. Therefore, a system is proposed to automate menial tasks and allow sharing of data related to KYC. A blockchain dictates the collaboration between different participants and several services are built around it to support the functionality of the system as a whole. An access control system is used to share data legitimately. [less ▲]

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See detailBlockZoom: Large-Scale Blockchain Testbed
Shbair, Wazen UL; Steichen, Mathis UL; Francois, Jerome et al

in IEEE International Conference on Blockchain and Cryptocurrency (ICBC 2019) (2019, May 14)

Future blockchain applications are anticipated to serve millions of users. Thus the evaluation of new blockchain applications have to consider large-scale assessment of the technologies behind the scene ... [more ▼]

Future blockchain applications are anticipated to serve millions of users. Thus the evaluation of new blockchain applications have to consider large-scale assessment of the technologies behind the scene. Most of current testing approaches have been done either on simulators or via local small blockchain networks. Hence, the performance in real world conditions is unpredictable. This demonstration introduces BlockZoom, a large-scale blockchain testbed that runs on top of a highly reconfigurable and controllable HPC platform. BlockZoom presents a reproducible environment for experimenting distributed ledgers technologies and smart contract applications. Through different configuration scenarios developers can evaluate the applications performance and the blockchain behavior at a scale comparable to the production environment. The target audience of this demonstration includes researchers and developers in blockchain technology. [less ▲]

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See detailPredicting Sparse Clients' Actions with CPOPT-Net in the Banking Environment
Charlier, Jérémy Henri J. UL; State, Radu UL; Hilger, Jean UL

in 32nd Canadian Conference on Artificial Intelligence Proceedings (2019, May)

The digital revolution of the banking system with evolving European regulations have pushed the major banking actors to innovate by a newly use of their clients' digital information. Given highly sparse ... [more ▼]

The digital revolution of the banking system with evolving European regulations have pushed the major banking actors to innovate by a newly use of their clients' digital information. Given highly sparse client activities, we propose CPOPT-Net, an algorithm that combines the CP canonical tensor decomposition, a multidimensional matrix decomposition that factorizes a tensor as the sum of rank-one tensors, and neural networks. CPOPT-Net removes efficiently sparse information with a gradient-based resolution while relying on neural networks for time series predictions. Our experiments show that CPOPT-Net is capable to perform accurate predictions of the clients' actions in the context of personalized recommendation. CPOPT-Net is the first algorithm to use non-linear conjugate gradient tensor resolution with neural networks to propose predictions of financial activities on a public data set. [less ▲]

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See detailROS-Defender: SDN-based Security Policy Enforcement for Robotic Applications
Rivera, Sean UL; Lagraa, Sofiane UL; State, Radu UL et al

in IEEE Workshop on the Internet of Safe Things, Co-located with IEEE Security and Privacy 2019 (2019, May)

Abstract—In this paper we propose ROS-Defender, a holistic approach to secure robotics systems, which integrates a Security Event Management System (SIEM), an intrusion prevention system (IPS) and a ... [more ▼]

Abstract—In this paper we propose ROS-Defender, a holistic approach to secure robotics systems, which integrates a Security Event Management System (SIEM), an intrusion prevention system (IPS) and a firewall for a robotic system. ROS-Defender combines anomaly detection systems at application (ROS) level and network level, with dynamic policy enforcement points using software defined networking (SDN) to provide protection against a large class of attacks. Although SIEMs, IPS, and firewall have been previously used to secure computer networks, ROSDefender is applying them for the specific use case of robotic systems, where security is in many cases an afterthought. [less ▲]

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See detailTime Series Modeling of Market Price in Real-Time Bidding
Du, Manxing UL; Hammerschmidt, Christian UL; Varisteas, Georgios UL et al

in 27th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (2019, April)

Real-Time-Bidding (RTB) is one of the most popular online advertisement selling mechanisms. Modeling the highly dynamic bidding environment is crucial for making good bids. Market prices of auctions ... [more ▼]

Real-Time-Bidding (RTB) is one of the most popular online advertisement selling mechanisms. Modeling the highly dynamic bidding environment is crucial for making good bids. Market prices of auctions fluctuate heavily within short time spans. State-of-the-art methods neglect the temporal dependencies of bidders’ behaviors. In this paper, the bid requests are aggregated by time and the mean market price per aggregated segment is modeled as a time series. We show that the Long Short Term Memory (LSTM) neural network outperforms the state-of-the-art univariate time series models by capturing the nonlinear temporal dependencies in the market price. We further improve the predicting performance by adding a summary of exogenous features from bid requests. [less ▲]

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See detailEvaluation of End-To-End Learning for Autonomous Driving: The Good, the Bad and the Ugly
Varisteas, Georgios UL; Frank, Raphaël UL; Sajadi Alamdari, Seyed Amin UL et al

in 2nd International Conference on Intelligent Autonomous Systems, Singapore, Feb. 28 to Mar. 2, 2019 (2019, March 01)

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See detailA Tale of Location-Based User Authentication
Falk, Eric UL; Toth, Vendel; Knaff, Alexandre et al

in IEEE BigComp2019 - The 6th IEEE International Conference on Big Data and Smart Computing (2019)

The attitude towards passwords has drastically changed over the past years. Although they protected workstations from illicit access for decades, with today’s increased computational power, simple ... [more ▼]

The attitude towards passwords has drastically changed over the past years. Although they protected workstations from illicit access for decades, with today’s increased computational power, simple passwords became easy targets for attacks, whereas complex passwords are difficult to remember for the users. It appears as if the classical password protection has become obsolete and has to give way to similarly secured schemes, which are seamless for users. Novel methodologies may be sound and secure from a technical point of view, their success will be challenged by the simple question whether a user feels secure or not. In this work, we propose a proximity based login and session locking scheme, based on bluetooth beacons. We describe the big data architecture required to implement secured location-based services in smart buildings. To round our contribution out, we describe a medium scale user study with 40 participants, conducted to answer the question: Do users feel secure? [less ▲]

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See detailReal-time attack detection on robot cameras: A self-driving car application
Lagraa, Sofiane UL; Cailac, Maxime; Rivera, Sean UL et al

in International Conference on Robotic Computing (2019, February)

The Robot Operating System (ROS) are being deployed for multiple life critical activities such as self-driving cars, drones, and industries. However, the security has been persistently neglected ... [more ▼]

The Robot Operating System (ROS) are being deployed for multiple life critical activities such as self-driving cars, drones, and industries. However, the security has been persistently neglected, especially the image flows incoming from camera robots. In this paper, we perform a structured security assessment of robot cameras using ROS. We points out a relevant number of security flaws that can be used to take over the flows incoming from the robot cameras. Furthermore, we propose an intrusion detection system to detect abnormal flows. Our defense approach is based on images comparisons and unsupervised anomaly detection method. We experiment our approach on robot cameras embedded on a self-driving car. [less ▲]

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See detailROSploit: Cybersecurity tool for ROS
Rivera, Sean UL; Lagraa, Sofiane UL; State, Radu UL

in International Conference on Robotic Computing (2019, February)

Abstract—Robotic Operating System(ROS) security research is currently in a preliminary state, with limited research in tools or models. Considering the trend of digitization of robotic systems, this lack ... [more ▼]

Abstract—Robotic Operating System(ROS) security research is currently in a preliminary state, with limited research in tools or models. Considering the trend of digitization of robotic systems, this lack of foundational knowledge increases the potential threat posed by security vulnerabilities in ROS. In this article, we present a new tool to assist further security research in ROS, ROSploit. ROSploit is a modular two-pronged offensive tool covering both reconnaissance and exploitation of ROS systems, designed to assist researchers in testing exploits for ROS. [less ▲]

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See detailLightning Network: A Comparative Review of Transaction Fees and Data Analysis
Khan, Nida UL; State, Radu UL

in Springer Blockchain and Applications (2019)

Blockchain is a revolutionary, immutable database disrupting the finance industry with a potential to provide payments in a secure environment, unhindered by intermediaries. However, scalability and ... [more ▼]

Blockchain is a revolutionary, immutable database disrupting the finance industry with a potential to provide payments in a secure environment, unhindered by intermediaries. However, scalability and throughput issues plague the technology and prevent it's mass scale adoption. The paper focusses on Lightning Network, the off-chain, scalable and high throughput payment solution from Bitcoin. A comparison is conducted to highlight the fee incurred for payment transactions through Lightning Network, Raiden, Stellar, Bitcoin and conventional payment systems to assess its viability as a blockchain-based payment sys-tem. The paper also provides an analysis of the data of Lightning Network, to give a global overview of its usage and reachability. [less ▲]

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See detailAn Experimental Analysis of Fraud Detection Methods in Enterprise Telecommunication Data using Unsupervised Outlier Ensembles
Kaiafas, Georgios UL; Hammerschmidt, Christian UL; Lagraa, Sofiane UL et al

in Kaiafas, Georgios; Hammerschmidt, Christian; State, Radu (Eds.) 16th IFIP/IEEE Symposium on Integrated Network and Service Management (IM 2019) (2019)

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See detailThe Art of The Scam: Demystifying Honeypots in Ethereum Smart Contracts
Ferreira Torres, Christof UL; Steichen, Mathis UL; State, Radu UL

in USENIX Security Symposium, Santa Clara, 14-16 August 2019 (2019)

Modern blockchains, such as Ethereum, enable the execution of so-called smart contracts - programs that are executed across a decentralised network of nodes. As smart contracts become more popular and ... [more ▼]

Modern blockchains, such as Ethereum, enable the execution of so-called smart contracts - programs that are executed across a decentralised network of nodes. As smart contracts become more popular and carry more value, they become more of an interesting target for attackers. In the past few years, several smart contracts have been exploited by attackers. However, a new trend towards a more proactive approach seems to be on the rise, where attackers do not search for vulnerable contracts anymore. Instead, they try to lure their victims into traps by deploying seemingly vulnerable contracts that contain hidden traps. This new type of contracts is commonly referred to as honeypots. In this paper, we present the first systematic analysis of honeypot smart contracts, by investigating their prevalence, behaviour and impact on the Ethereum blockchain. We develop a taxonomy of honeypot techniques and use this to build HoneyBadger - a tool that employs symbolic execution and well defined heuristics to expose honeypots. We perform a large-scale analysis on more than 2 million smart contracts and show that our tool not only achieves high precision, but is also highly efficient. We identify 690 honeypot smart contracts as well as 240 victims in the wild, with an accumulated profit of more than $90,000 for the honeypot creators. Our manual validation shows that 87% of the reported contracts are indeed honeypots. [less ▲]

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See detailA Proposal for Security Assessment of Trustzone-M based Software
Iannillo, Antonio Ken UL; State, Radu UL

in 2019 IEEE 30th International Symposium on Software Reliability Engineering (ISSRE) (2019)

With the advent of the Internet of Things (IoT) paradigm, computing and networking capabilities are extending to devices that are not considered as computers, enabling them to interact with the physical ... [more ▼]

With the advent of the Internet of Things (IoT) paradigm, computing and networking capabilities are extending to devices that are not considered as computers, enabling them to interact with the physical world or other software entities with minimal or no human input. This fast abstract proposes a methodology for the security assessment of software based on TrustZone-M, the ARM hardware security extension for microcontrollers. The methodology consists of the exploitation of a verification and validation framework to automatically test TrustZone-M based software. [less ▲]

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See detailGraph-based malicious login events investigation
Amrouche, Faouzi UL; Lagraa, Sofiane UL; Kaiafas, Georgios UL et al

in Amrouche, Faouzi; Lagraa, Sofiane; Kaiafas, Georgios (Eds.) et al 16th IFIP/IEEE Symposium on Integrated Network and Service Management (IM 2019) (2019)

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See detailBlockchain-based Micropayment Systems: Economic Impact
Khan, Nida UL; Ahmad, Tabrez; State, Radu UL

in ACM IDEAS '19 Proceedings of the 23rd International Database Engineering & Applications Symposium (2019)

The inception of blockchain catapulted the development of innovative use cases utilizing the trustless, decentralized environment, empowered by cryptocurrencies. The envisaged benefits of the technology ... [more ▼]

The inception of blockchain catapulted the development of innovative use cases utilizing the trustless, decentralized environment, empowered by cryptocurrencies. The envisaged benefits of the technology includes the divisible nature of a cryptocurrency, that can facilitate payments in fractions of a cent, enabling micropayments through the blockchain. Micropayments are a critical tool to enable financial inclusion and to aid in global poverty alleviation. The paper conducts a study on the economic impact of blockchain-based micropayment systems, emphasizing their significance for socioeconomic benefit and financial inclusion. The paper also highlights the contribution of blockchain-based micropayments to the cybercrime economy, indicating the critical need of economic regulations to curtail the growing threat posed by the digital payment mechanism. [less ▲]

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See detailKnow Your Enemies and Know Yourself in the Real-Time Bidding Function Optimisation
Du, Manxing UL; Cowen-Rivers, Alexander I.; Wen, Ying et al

in Proceedings of the 19th IEEE International Conference on Data Mining Workshops (ICDMW 2019) (2019)

Detailed reference viewed: 317 (0 UL)