References of "Francois, Jerome"
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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 detailDeep mining port scans from darknet
Lagraa, Sofiane UL; Chen, Yutian; François, Jérôme

in International Journal of Network Management (2019)

TCP/UDP port scanning or sweeping is one of the most common technique used 3 by attackers to discover accessible and potentially vulnerable hosts and applications. Although extracting and distinguishing ... [more ▼]

TCP/UDP port scanning or sweeping is one of the most common technique used 3 by attackers to discover accessible and potentially vulnerable hosts and applications. Although extracting and distinguishing different port scanning strategies is a challenging task, the identification of dependencies among probed ports is primordial for profiling attacker behaviors, with a final goal of better mitigating them. In this paper, we propose an approach that allows to track port scanning behavior patterns among multiple probed ports and identify intrinsic properties of observed group of orts. Our method is fully automated based on graph modeling and data mining techniques, including text mining. It provides to security analysts and operators relevant information about services that are jointly targeted by attackers. This is helpful to assess the strategy of the attacker by understanding the types of applications or environment he or she targets. We applied our method to data collected through a large Internet telescope (or darknet). [less ▲]

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See detailTowards a Management Plane for Smart Contracts: Ethereum Case Study
Khan, Nida UL; Lahmadi, Abdelkader; Francois, Jerome et al

in NOMS 2018 - 2018 IEEE/IFIP Network Operations and Management Symposium (2018)

Blockchain is an emerging foundational technology with the potential to create a novel economic and social system. The complexity of the technology poses many challenges and foremost amongst these are ... [more ▼]

Blockchain is an emerging foundational technology with the potential to create a novel economic and social system. The complexity of the technology poses many challenges and foremost amongst these are monitoring and management of blockchain-based decentralized applications. In this paper, we design, implement and evaluate a novel system to enable management operations in smart contracts. A key aspect of our system is that it facilitates the integration of these operations through dedicated ’managing’ smart contracts to provide data filtering as per the role of the smart contract-based application user. We evaluate the overhead costs of such data filtering operations after post-deployment analyses of five categories of smart contracts on the Ethereum public testnet, Rinkeby. We also build a monitoring tool to display public blockchain data using a dashboard coupled with a notification mechanism of any changes in private data to the administrator of the monitored decentralized application. [less ▲]

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See detailAdvanced Interest Flooding Attacks in Named-Data Networking
Signorello, Salvatore UL; Marchal, Samuel; François, Jérôme et al

Scientific Conference (2017, October 30)

The Named-Data Networking (NDN) has emerged as a clean-slate Internet proposal on the wave of Information-Centric Networking. Although the NDN’s data-plane seems to offer many advantages, e.g., native ... [more ▼]

The Named-Data Networking (NDN) has emerged as a clean-slate Internet proposal on the wave of Information-Centric Networking. Although the NDN’s data-plane seems to offer many advantages, e.g., native support for multicast communications and flow balance, it also makes the network infrastructure vulnerable to a specific DDoS attack, the Interest Flooding Attack (IFA). In IFAs, a botnet issuing unsatisfiable content requests can be set up effortlessly to exhaust routers’ resources and cause a severe performance drop to legitimate users. So far several countermeasures have addressed this security threat, however, their efficacy was proved by means of simplistic assumptions on the attack model. Therefore, we propose a more complete attack model and design an advanced IFA. We show the efficiency of our novel attack scheme by extensively assessing some of the state-of-the-art countermeasures. Further, we release the software to perform this attack as open source tool to help design future more robust defense mechanisms. [less ▲]

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See detailProfiling Smart Contracts Interactions Tensor Decomposition and Graph Mining.
Charlier, Jérémy Henri J. UL; Lagraa, Sofiane UL; State, Radu UL et al

in Proceedings of the Second Workshop on MIning DAta for financial applicationS (MIDAS 2017) co-located with the 2017 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2017), Skopje, Macedonia, September 18, 2017. (2017, September)

Smart contracts, computer protocols designed for autonomous execution on predefined conditions, arise from the evolution of the Bitcoin’s crypto-currency. They provide higher transaction security and ... [more ▼]

Smart contracts, computer protocols designed for autonomous execution on predefined conditions, arise from the evolution of the Bitcoin’s crypto-currency. They provide higher transaction security and allow economy of scale through the automated process. Smart contracts provides inherent benefits for financial institutions such as investment banking, retail banking, and insurance. This technology is widely used within Ethereum, an open source block-chain platform, from which the data has been extracted to conduct the experiments. In this work, we propose an multi-dimensional approach to find and predict smart contracts interactions only based on their crypto-currency exchanges. This approach relies on tensor modeling combined with stochastic processes. It underlines actual exchanges between smart contracts and targets the predictions of future interactions among the community. The tensor analysis is also challenged with the latest graph algorithms to assess its strengths and weaknesses in comparison to a more standard approach. [less ▲]

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See detailBotGM: Unsupervised Graph Mining to Detect Botnets in Traffic Flows
Lagraa, Sofiane UL; François, Jérôme; Lahmadi, Abdelkader et al

in CSNet 2017 Conference Proceedings (2017)

Botnets are one of the most dangerous and serious cybersecurity threats since they are a major vector of large-scale attack campaigns such as phishing, distributed denial-of-service (DDoS) attacks ... [more ▼]

Botnets are one of the most dangerous and serious cybersecurity threats since they are a major vector of large-scale attack campaigns such as phishing, distributed denial-of-service (DDoS) attacks, trojans, spams, etc. A large body of research has been accomplished on botnet detection, but recent security incidents show that there are still several challenges remaining to be addressed, such as the ability to develop detectors which can cope with new types of botnets. In this paper, we propose BotGM, a new approach to detect botnet activities based on behavioral analysis of network traffic flow. BotGM identifies network traffic behavior using graph-based mining techniques to detect botnets behaviors and model the dependencies among flows to traceback the root causes then. We applied BotGM on a publicly available large dataset of Botnet network flows, where it detects various botnet behaviors with a high accuracy without any prior knowledge of them. [less ▲]

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See detailNDN.p4: Programming Information-Centric data-planes
Signorello, Salvatore UL; State, Radu UL; François, Jérôme et al

in Proceedings of the IEEE International Workshop on Open-Source Software Networking at NetSoft2016 (2016)

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See detailA Generic Framework to Support Application-Level Flow Management in Software-Defined Networks
Dolberg, Lautaro UL; François, Jérôme; Chowdhury, Shihabur Rahman et al

in Conference on Network Softwarization (Netsoft) (2016)

Detailed reference viewed: 98 (4 UL)