KHAN, N., Ahmad, T., Patel, A., & STATE, R. (In press). Blockchain Governance: An Overview and Prediction of Optimal Strategies Using Nash Equilibrium. In 3rd AUE International Research Conference. Springer. Peer reviewed |
SCHEIDT DE CRISTO, F., EISENBARTH, J.-P., MEIRA, J. A., & STATE, R. (November 2024). Causal AI for XRPL/GossipSub network configuration [Paper presentation]. 20th International Conference on Network and Service Management, Prague, Czechia. Peer reviewed |
PANTIUKHOV, P., KORIAKOV, D., PETROVA, T., HONORIO ALVES, J., Gurbani, V. K., & STATE, R. (2024). Enhanced DeFi Security on XRPL with Zero-Knowledge Proofs and Speaker Verification. IEEE International Conference and Expo on Real Time Communications at IIT (RTC), 23-30. doi:10.1109/rtc62204.2024.10739262 Peer reviewed |
TRESTIOREANU, L. A., SCHEIDT DE CRISTO, F., SHBAIR, W., FRANCOIS, J., Magoni, D., & STATE, R. (2024). To Squelch or not to Squelch: Enabling Improved Message Dissemination on the XRP Ledger. IEEE/IFIP Network Operations and Management Symposium. doi:10.1109/NOMS59830.2024.10575886 Peer reviewed |
SCHEIDT DE CRISTO, F., MEIRA, J. A., EISENBARTH, J.-P., & STATE, R. (2024). A 9-dimensional Analysis of GossipSub over the XRP Ledger Consensus Protocol. IEEE/IFIP Network Operations and Management Symposium. Peer reviewed |
PARHIZKARI, B., IANNILLO, A. K., FERREIRA TORRES, C., Xu, J., Banescu, S., & STATE, R. (2024). Beyond the Public Mempool: Catching DeFi Attacks Before They Happen with Real-Time Smart Contract Analysis [Paper presentation]. 20th EAI International Conference on Security and Privacy in Communication Networks, Dubai, United Arab Emirates. Peer reviewed |
SCHEIDT DE CRISTO, F., SHBAIR, W., TRESTIOREANU, L. A., & STATE, R. (2023). Pub/sub Dissemination on the XRP Ledger. 2023 IEEE Latin-American Conference on Communications (LATINCOM), 6. Peer reviewed |
SCHEIDT DE CRISTO, F., GEIMER, A. M. D., & STATE, R. (2023). NLAC: A Self-Maintained Trust Overlay for the XRP Ledger. Proceedings of 2023 IEEE Latin-American Conference on Communications (LATINCOM). Peer reviewed |
WANG, Y., HUANG, H., & STATE, R. (2023). Early Crop Mapping Using Dynamic Ecoregion Clustering: A USA-Wide Study. Remote Sensing. doi:10.3390/rs15204962 Peer Reviewed verified by ORBi |
ROSZEL, M., FIZ PONTIVEROS, B., & STATE, R. (2023). FLAIRS: Federated Learning AI Regulatory Sandbox. In D. Koutra, C. Plant, M. Gomez Rodriguez, E. Baralis, ... F. Bonchi, ECML PKDD 2023 Workshops. Springer Nature. Peer reviewed |
PARHIZKARI, B., IANNILLO, A. K., FERREIRA TORRES, C., Banescu, S., Xu, J., & STATE, R. (2023). Timely Identification of Victim Addresses in DeFi Attacks. In Timely Identification of Victim Addresses in DeFi Attacks. Springer. doi:10.1007/978-3-031-54204-6_24 Peer reviewed |
TRESTIOREANU, L. A., SHBAIR, W., SCHEIDT DE CRISTO, F., & STATE, R. (2023). XRP-NDN overlay: Improving the Communication Efficiency of Consensus-Validation based Blockchains with an NDN Overlay. IEEE/IFIP Network Operations and Management Symposium. doi:10.1109/NOMS56928.2023.10154402 Peer reviewed |
DAMOUN, F., Seba, H., HILGER, J., & STATE, R. (2023). G-HIN2Vec: Distributed Heterogeneous Graph Representations for Cardholder Transactions. In Proceedings of the 38th ACM/SIGAPP Symposium on Applied Computing (pp. 528–535). New York, Unknown/unspecified: Association for Computing Machinery. doi:10.1145/3555776.3577740 Peer reviewed |
ROSZEL, M., NORVILL, R., FIZ PONTIVEROS, B., HILGER, J., & STATE, R. (13 February 2023). Know Your Model (KYM): Increasing Trust in AI and Machine Learning [Paper presentation]. Deployable AI (DAI) Workshop at AAAI-2023. Peer reviewed |
HUANG, H., XU, Y., Zhang, J., & STATE, R. (2023). NIRWatchdog: Cross-Domain Product Quality Assessment Using Miniaturized Near-Infrared Sensors. IEEE Internet of Things Journal, 1-1. doi:10.1109/jiot.2023.3331948 Peer Reviewed verified by ORBi |
TRESTIOREANU, L. A., SHBAIR, W., SCHEIDT DE CRISTO, F., & STATE, R. (2023). Blockly2Hooks: Smart Contracts for Everyone with the XRP Ledger and Google Blockly. International Conference on Decentralized Applications and Infrastructures (DAPPS). Peer reviewed |
TUMAS, V., RIVERA, S., Magoni, D., & STATE, R. (12 October 2022). Topology Analysis of the XRP Ledger [Paper presentation]. The 38th ACM/SIGAPP Symposium On Applied Computing, Tallinn, Estonia. doi:10.1145/3555776.3577611 |
ROSZEL, M., NORVILL, R., & STATE, R. (2022). An Analysis of Byzantine-Tolerant Aggregation Mechanisms on Model Poisoning in Federated Learning. In V. Torra (Ed.), Modeling Decisions for Artificial Intelligence - 19th International Conference, MDAI 2022, Proceedings. Springer Science and Business Media Deutschland GmbH. doi:10.1007/978-3-031-13448-7_12 Peer reviewed |
FERREIRA TORRES, C., Jonker, H., & STATE, R. (2022). Elysium: Context-Aware Bytecode-Level Patching to Automatically Heal Vulnerable Smart Contracts. In International Symposium on Research in Attacks, Intrusions and Defenses, Limassol, Cyprus 26-28 October 2022. Peer reviewed |
Ota, F. K. C., DAMOUN, F., Lagraa, S., Becerra-Sanchez, P., HILGER, J., & STATE, R. (2022). Event-Driven Interest Detection for Task-Oriented Mobile Apps. In F. K. C. Ota & F. DAMOUN, Mobile and Ubiquitous Systems: Computing, Networking and Services (pp. 582--598). Cham, Unknown/unspecified: Springer International Publishing. doi:10.1007/978-3-030-94822-1_38 Peer reviewed |
Weintraub, B., FERREIRA TORRES, C., Nita-Rotaru, C., & STATE, R. (2022). A Flash(bot) in the Pan: Measuring Maximal Extractable Value in Private Pools. In ACM Internet Measurement Conference, Nice, France 25-27 October 2022. Peer reviewed |
SCHEIDT DE CRISTO, F., SHBAIR, W., TRESTIOREANU, L. A., STATE, R., & Malhotra, A. (2021). Self-Sovereign Identity for the Financial Sector: A Case Study of PayString Service. IEEE International Conference on Blockchain. doi:10.1109/Blockchain53845.2021.00036 Peer reviewed |
TRESTIOREANU, L. A., Nita-Rotaru, C., Malhotra, A., & STATE, R. (2021). SPON: Enabling Resilient Inter-Ledgers Payments with an Intrusion-Tolerant Overlay. IEEE Conference on Communications and Network Security. doi:10.1109/CNS53000.2021.9705048 Peer reviewed |
FERREIRA TORRES, C., IANNILLO, A. K., Gervais, A., & STATE, R. (2021). ConFuzzius: A Data Dependency-Aware Hybrid Fuzzer for Smart Contracts. In European Symposium on Security and Privacy, Vienna 7-11 September 2021. Peer reviewed |
SHBAIR, W., Gavrilov, E., & STATE, R. (2021). HSM-based Key Management Solution for Ethereum Blockchain. In IEEE International Conference on Blockchain and Cryptocurrency, 3-6 May 2021. doi:10.1109/ICBC51069.2021.9461136 Peer reviewed |
SCHEIDT DE CRISTO, F., SHBAIR, W., TRESTIOREANU, L. A., Malhotra, A., & STATE, R. (May 2021). Privacy-Preserving PayString Service [Poster presentation]. IEEE International Conference on Blockchain and Cryptocurrency. |
FERREIRA TORRES, C., Camino, R., & STATE, R. (2021). Frontrunner Jones and the Raiders of the Dark Forest: An Empirical Study of Frontrunning on the Ethereum Blockchain. In USENIX Security Symposium, Virtual 11-13 August 2021. Peer reviewed |
FERREIRA TORRES, C., IANNILLO, A. K., Gervais, A., & STATE, R. (2021). The Eye of Horus: Spotting and Analyzing Attacks on Ethereum Smart Contracts. In International Conference on Financial Cryptography and Data Security, Grenada 1-5 March 2021. Peer reviewed |
CARVALHO OTA, F. K., MEIRA, J. A., FRANK, R., & STATE, R. (2020). Towards Privacy Preserving Data Centric Super App. In F. K. CARVALHO OTA, J. A. MEIRA, R. FRANK, ... R. STATE, 2020 Mediterranean Communication and Computer Networking Conference, Arona 17-19 June 2020. Arona, Italy: IEEE. doi:10.1109/MedComNet49392.2020.9191550 Peer reviewed |
CAMINO, R. D., FERREIRA TORRES, C., BADEN, M., & STATE, R. (2020). A Data Science Approach for Honeypot Detection in Ethereum. In 2020 IEEE International Conference on Blockchain and Cryptocurrency (ICBC). Peer reviewed |
RIVERA, S., Gurbani, V., LAGRAA, S., IANNILLO, A. K., & STATE, R. (2020). Leveraging eBPF to preserve user privacy for DNS, DoT, and DoH queries. Proceedings of the 15th International Conference on Availability, Reliability and Security. doi:10.1145/3407023.3407041 Peer reviewed |
CAMINO, R. D., HAMMERSCHMIDT, C., & STATE, R. (17 July 2020). Working with Deep Generative Models and Tabular Data Imputation [Paper presentation]. First Workshop on the Art of Learning with Missing Values (Artemiss), Vienna, Austria. |
CASSAGNES, C., TRESTIOREANU, L. A., JOLY, C., & STATE, R. (2020). The rise of eBPF for non-intrusive performance monitoring. IEEE Xplore, 7. doi:10.1109/NOMS47738.2020.9110434 Peer reviewed |
KHAN, N., KCHOURI, B., Yatoo, N. A., KRÄUSSL, Z., Patel, A., & STATE, R. (2020). Tokenization of Sukuk: Ethereum Case Study. Global Finance Journal. doi:10.1016/j.gfj.2020.100539 Peer reviewed |
CAMINO, R. D., HAMMERSCHMIDT, C., & STATE, R. (2020). Minority Class Oversampling for Tabular Data with Deep Generative Models. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/43194. |
CARVALHO OTA, F. K., MEIRA, J. A., CASSAGNES, C., & STATE, R. (2020). Mobile App to SGX Enclave Secure Channel. In 2019 IEEE International Symposium on Software Reliability Engineering Workshops. doi:10.1109/ISSREW.2019.00081 Peer reviewed |
TRESTIOREANU, L. A., CASSAGNES, C., & STATE, R. (2020). Deep dive into Interledger: Understanding the Interledger ecosystem - Part 4. (Unilu - University of Luxembourg, Luxembourg). |
YAKUBOV, A., SHBAIR, W., KHAN, N., STATE, R., Medinger, C., & Hilger, J. (05 January 2020). BlockPGP: A Blockchain-based Framework for PGP Key Servers. International Journal of Networking and Computing, 10 (1), 1-24. Peer reviewed |
FERREIRA TORRES, C., STEICHEN, M., & STATE, R. (2020). Towards Usable Protection Against Honeypots. In IEEE International Conference on Blockchain and Cryptocurrency, Toronto, Canada 3-6 May 2020. Peer reviewed |
AMROUCHE, F., LAGRAA, S., FRANK, R., & STATE, R. (2020). Intrusion detection on robot cameras using spatio-temporal autoencoders: A self-driving car application. In 91st IEEE Vehicular Technology Conference, VTC Spring 2020, Antwerp, Belgium, May 25-28, 2020. Peer reviewed |
LAGRAA, S., & STATE, R. (2020). Process mining-based approach for investigating malicious login events. In IEEE/IFIP Network Operations and Management Symposium, Budapest, Hungary, April 20-24, 2020. Peer reviewed |
Khramtsova, E., Hammerschmidt, C., LAGRAA, S., & STATE, R. (2020). Federated Learning For Cyber Security: SOC Collaboration For Malicious URL Detection. IEEE International Conference on Distributed Computing Systems (ICDCS). doi:10.1109/ICDCS47774.2020.00171 Peer reviewed |
KHAN, N., Ahmad, T., & STATE, R. (2019). Feasibility of Stellar as a Blockchain-based Micropayment System. In Springer SmartBlock 2019 - 2nd International Conference on Smart Blockchain. Springer. doi:10.1007/978-3-030-34083-4_6 Peer reviewed |
RIVERA, S., LAGRAA, S., IANNILLO, A. K., & STATE, R. (2019). Auto-encoding Robot State against Sensor Spoofing Attacks. International Symposium on Software Reliability Engineering. doi:10.1109/ISSREW.2019.00080 Peer reviewed |
CHARLIER, J. H. J., Ormazabal, G., STATE, R., & HILGER, J. (2019). MQLV: Optimal Policy of Money Management in Retail Banking with Q-Learning. Proceedings of the Fourth Workshop on MIning DAta for financial applicationS (MIDAS 2019) co-located with the 2019 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2019). doi:10.1007/978-3-030-37720-5_1 Peer reviewed |
CHARLIER, J. H. J., PETIT, F., Ormazabal, G., STATE, R., & HILGER, J. (2019). Visualization of AE's Training on Credit Card Transactions with Persistent Homology. Proceedings of the International Workshop on Applications of Topological Data Analysis In conjunction with ECML PKDD 2019. Peer reviewed |
TRESTIOREANU, L. A., CASSAGNES, C., & STATE, R. (2019). Deep dive into Interledger: Understanding the Interledger ecosystem - Part 3. (Unilu - University of Luxembourg). |
TRESTIOREANU, L. A., CASSAGNES, C., & STATE, R. (2019). Deep dive into Interledger: Understanding the Interledger ecosystem - Part 2. (Unilu - University of Luxembourg, Luxembourg). |
TRESTIOREANU, L. A., CASSAGNES, C., & STATE, R. (2019). Deep dive into Interledger: Understanding the Interledger ecosystem - Part 1. (Unilu - University of Luxembourg, Luxembourg). |
NORVILL, R., FIZ PONTIVEROS, B., STATE, R., & Cullen, A. (2019). Standardising smart contracts: Automatically inferring ERC standards. Proceedings of 2019 IEEE International Conference on Blockchain and Cryptocurrency. doi:10.1109/BLOC.2019.8751350 Peer reviewed |
STEICHEN, M., FERREIRA TORRES, C., FIZ PONTIVEROS, B., & STATE, R. (2019). Whispering Botnet Command and Control Instructions. In 2nd Crypto Valley Conference on Blockchain Technology, Zug 24-26 June 2019. Peer reviewed |
TRESTIOREANU, L. A., CASSAGNES, C., & STATE, R. (2019). Deep dive into Interledger: Understanding the Interledger ecosystem. (Unilu - University of Luxembourg, Luxembourg). |
CHARLIER, J. H. J., STATE, R., & HILGER, J. (2019). PHom-GeM: Persistent Homology for Generative Models. The 6th Swiss Conference on Data Science. doi:10.1109/SDS.2019.000-1 Peer reviewed |
FIZ PONTIVEROS, B., STEICHEN, M., & STATE, R. (17 May 2019). Mint Centrality: A Centrality Measure for the Bitcoin Transaction Graph [Poster presentation]. IEEE International Conference on Blockchain and Cryptocurrency. |
SHBAIR, W., STEICHEN, M., Francois, J., & STATE, R. (2019). BlockZoom: Large-Scale Blockchain Testbed. In IEEE International Conference on Blockchain and Cryptocurrency (ICBC 2019). IEEE Xplore. doi:10.1109/BLOC.2019.8751230 Peer reviewed |
NORVILL, R., STEICHEN, M., SHBAIR, W., & STATE, R. (2019). Demo: Blockchain for the Simplification and Automation of KYC Result Sharing. In IEEE International Conference on Blockchain and Cryptocurrency (ICBC 2019). IEEE Xplore. doi:10.1109/BLOC.2019.8751480 Peer reviewed |
RIVERA, S., LAGRAA, S., STATE, R., Nita-Rotaru, C., & BECKER, S. (2019). ROS-Defender: SDN-based Security Policy Enforcement for Robotic Applications. In IEEE Workshop on the Internet of Safe Things, Co-located with IEEE Security and Privacy 2019. Peer reviewed |
CHARLIER, J. H. J., STATE, R., & HILGER, J. (2019). Predicting Sparse Clients' Actions with CPOPT-Net in the Banking Environment. 32nd Canadian Conference on Artificial Intelligence Proceedings. doi:10.1007/978-3-030-18305-9_59 Peer reviewed |
DU, M., HAMMERSCHMIDT, C., VARISTEAS, G., STATE, R., BRORSSON, M. H., & Zhang, Z. (2019). Time Series Modeling of Market Price in Real-Time Bidding. In 27th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. Peer reviewed |
VARISTEAS, G., FRANK, R., SAJADI ALAMDARI, S. A., VOOS, H., & STATE, R. (2019). Evaluation of End-To-End Learning for Autonomous Driving: The Good, the Bad and the Ugly. In 2nd International Conference on Intelligent Autonomous Systems, Singapore, Feb. 28 to Mar. 2, 2019. IEEE. Peer reviewed |
FALK, E., Toth, V., Knaff, A., & STATE, R. (2019). A Tale of Location-Based User Authentication. IEEE BigComp2019 - The 6th IEEE International Conference on Big Data and Smart Computing. Peer reviewed |
CAMINO, R. D., HAMMERSCHMIDT, C., & STATE, R. (2019). Improving Missing Data Imputation with Deep Generative Models. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/43196. |
RIVERA, S., LAGRAA, S., & STATE, R. (2019). ROSploit: Cybersecurity tool for ROS. In International Conference on Robotic Computing. doi:10.1109/IRC.2019.00077 Peer reviewed |
LAGRAA, S., Cailac, M., RIVERA, S., Beck, F., & STATE, R. (2019). Real-time attack detection on robot cameras: A self-driving car application. In International Conference on Robotic Computing. doi:10.1109/IRC.2019.00023 Peer reviewed |
KAIAFAS, G., HAMMERSCHMIDT, C., LAGRAA, S., & STATE, R. (2019). An Experimental Analysis of Fraud Detection Methods in Enterprise Telecommunication Data using Unsupervised Outlier Ensembles. In G. KAIAFAS, C. HAMMERSCHMIDT, ... R. STATE, 16th IFIP/IEEE Symposium on Integrated Network and Service Management (IM 2019). Piscataway, United States - New York: Institute of Electrical and Electronics Engineers. Peer reviewed |
AMROUCHE, F., LAGRAA, S., KAIAFAS, G., & STATE, R. (2019). Graph-based malicious login events investigation. In F. AMROUCHE, S. LAGRAA, G. KAIAFAS, ... R. STATE, 16th IFIP/IEEE Symposium on Integrated Network and Service Management (IM 2019). Peer reviewed |
KAIAFAS, G., HAMMERSCHMIDT, C., LAGRAA, S., & STATE, R. (2019). Auto Semi-supervised Outlier Detection for Malicious Authentication Events. ECML PKDD 2019 Workshops. doi:10.1007/978-3-030-43887-6_14 Peer reviewed |
KHAN, N., Ahmad, T., & STATE, R. (2019). Blockchain-based Micropayment Systems: Economic Impact. ACM IDEAS '19 Proceedings of the 23rd International Database Engineering & Applications Symposium. doi:10.1145/3331076.3331096 Peer reviewed |
KHAN, N., & STATE, R. (2019). Lightning Network: A Comparative Review of Transaction Fees and Data Analysis. In Springer Blockchain and Applications (pp. 11-18). Springer. doi:10.1007/978-3-030-23813-1_2 Peer reviewed |
IANNILLO, A. K., & STATE, R. (2019). A Proposal for Security Assessment of Trustzone-M based Software. In 2019 IEEE 30th International Symposium on Software Reliability Engineering (ISSRE). Peer reviewed |
DU, M., Cowen-Rivers, A. I., Wen, Y., Sakulwongtana, P., Wang, J., BRORSSON, M. H., & STATE, R. (2019). Know Your Enemies and Know Yourself in the Real-Time Bidding Function Optimisation. In Proceedings of the 19th IEEE International Conference on Data Mining Workshops (ICDMW 2019). Peer reviewed |
FERREIRA TORRES, C., STEICHEN, M., & STATE, R. (2019). The Art of The Scam: Demystifying Honeypots in Ethereum Smart Contracts. In USENIX Security Symposium, Santa Clara, 14-16 August 2019. Peer reviewed |
FERREIRA TORRES, C., Schütte, J., & STATE, R. (2018). Osiris: Hunting for Integer Bugs in Ethereum Smart Contracts. In 34th Annual Computer Security Applications Conference (ACSAC ’18), San Juan, Puerto Rico, USA, December 3-7, 2018. doi:10.1145/3274694.3274737 Peer reviewed |
YAKUBOV, A., SHBAIR, W., & STATE, R. (2018). BlockPGP: A Blockchain-based Framework for PGP Key Servers. In The Sixth International Symposium on Computing and Networking (November 27-30, 2018). Hida Takayama, Japan: IEEE Xplore. doi:10.1109/CANDARW.2018.00065 Peer reviewed |
Mund, S., FRANK, R., VARISTEAS, G., & STATE, R. (2018). Visualizing the Learning Progress of Self-Driving Cars. In 21st International Conference on Intelligent Transportation Systems (pp. 2358-2363). IEEE. Peer reviewed |
CHARLIER, J. H. J., FALK, E., STATE, R., & HILGER, J. (2018). User-Device Authentication in Mobile Banking using APHEN for Paratuck2 Tensor Decomposition. Proceedings of 2018 IEEE International Conference on Data Mining Workshops (ICDMW). doi:10.1109/ICDMW.2018.00130 Peer reviewed |
LAGRAA, S., CHARLIER, J. H. J., & STATE, R. (20 August 2018). Knowledge Discovery Approach from Blockchain, Crypto-currencies, and Financial Stock Exchanges [Poster presentation]. 2018 ACM SIGKDD International Conference on Knowledge Discovery and Data mining conference (KDD 2018). |
STEICHEN, M., FIZ PONTIVEROS, B., NORVILL, R., SHBAIR, W., & STATE, R. (2018). Blockchain-Based, Decentralized Access Control for IPFS. In The 2018 IEEE International Conference on Blockchain (Blockchain-2018) (pp. 1499-1506). Halifax, Canada: IEEE. doi:10.1109/Cybermatics_2018.2018.00253 Peer reviewed |
NORVILL, R., FIZ PONTIVEROS, B., STATE, R., & Cullen, A. (2018). Visual emulation for Ethereum's virtual machine. NOMS 2018 - 2018 IEEE/IFIP Network Operations and Management Symposium. doi:10.1109/NOMS.2018.8406332 Peer reviewed |
CAMINO, R. D., HAMMERSCHMIDT, C., & STATE, R. (July 2018). Generating Multi-Categorical Samples with Generative Adversarial Networks [Paper presentation]. ICML 2018 workshop on Theoretical Foundations and Applications of Deep Generative Models, Stockholm, Sweden. |
CHARLIER, J. H. J., & STATE, R. (April 2018). Non-Negative Paratuck2 Tensor Decomposition Combined to LSTM Network for Smart Contracts Profiling. International Journal of Computer & Software Engineering, 3 (1). doi:10.15344/2456-4451/2018/132 |
FIZ PONTIVEROS, B., NORVILL, R., & STATE, R. (2018). Recycling Smart Contracts: Compression of the Ethereum Blockchain. Proceedings of 9th IFIP International Conference on New Technologies, Mobility and Security (NTMS) 2018. doi:10.1109/NTMS.2018.8328742 Peer reviewed |
GLAUNER, P., & STATE, R. (2018). Introduction to Machine Learning for Power Engineers [Paper presentation]. 10th IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC 2018), Kota Kinabalu, Malaysia. |
GLAUNER, P., Valtchev, P., & STATE, R. (2018). Impact of Biases in Big Data. In Proceedings of the 26th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2018). Peer reviewed |
SHBAIR, W., STEICHEN, M., FRANÇOIS, J., & STATE, R. (2018). Blockchain Orchestration and Experimentation Framework: A Case Study of KYC. In The First IEEE/IFIP International Workshop on Managing and Managed by Blockchain (Man2Block) colocated with IEEE/IFIP NOMS 2018. Peer reviewed |
FIZ PONTIVEROS, B., NORVILL, R., & STATE, R. (2018). Monitoring the transaction selection policy of Bitcoin mining pools. NOMS 2018 - 2018 IEEE/IFIP Network Operations and Management Symposium. doi:10.1109/NOMS.2018.8406328 Peer reviewed |
VARISTEAS, G., AVANESOV, T., & STATE, R. (2018). Distributed C++-Python embedding for fast predictions and fast prototyping. In Proceedings of the Second Workshop on Distributed Infrastructures for Deep Learning. Peer reviewed |
KHAN, N., Lahmadi, A., Francois, J., & STATE, R. (2018). Towards a Management Plane for Smart Contracts: Ethereum Case Study. NOMS 2018 - 2018 IEEE/IFIP Network Operations and Management Symposium. doi:10.1109/NOMS.2018.8406326 Peer reviewed |
YAKUBOV, A., SHBAIR, W., Wallbom, A., Sanda, D., & STATE, R. (2018). A Blockchain-Based PKI Management Framework. In The First IEEE/IFIP International Workshop on Managing and Managed by Blockchain (Man2Block) colocated with IEEE/IFIP NOMS 2018, Tapei, Tawain 23-27 April 2018. Peer reviewed |
CHARLIER, J. H. J., STATE, R., & Hilger, J. (2018). Non-Negative Paratuck2 Tensor Decomposition Combined to LSTM Network For Smart Contracts Profiling. In J. Charlier, R. STATE, ... J. Hilger, 2018 IEEE International Conference on Big Data and Smart Computing Proceedings (pp. 74-81). IEEE Computer Society Conference Publishing Services (CPS). doi:10.1109/BigComp.2018.00020 Peer reviewed |
GLAUNER, P., STATE, R., Valtchev, P., & Duarte, D. (2018). On the Reduction of Biases in Big Data Sets for the Detection of Irregular Power Usage. In Proceedings 13th International FLINS Conference on Data Science and Knowledge Engineering for Sensing Decision Support (FLINS 2018). Peer reviewed |
GLAUNER, P., MEIRA, J. A., & STATE, R. (2018). Detection of Irregular Power Usage using Machine Learning [Paper presentation]. IEEE Conference on Innovative Smart Grid Technologies, Asia (ISGT Asia 2018), Singapore. |
GLAUNER, P., MEIRA, J. A., & STATE, R. (2018). Machine Learning for Data-Driven Smart Grid Applications [Paper presentation]. IEEE Conference on Innovative Smart Grid Technologies, Asia (ISGT Asia 2018), Singapore. |
KAIAFAS, G., VARISTEAS, G., LAGRAA, S., & STATE, R. (2018). Detecting Malicious Authentication Events Trustfully. In G. KAIAFAS, G. VARISTEAS, S. LAGRAA, ... R. STATE, IEEE/IFIP Network Operations and Management Symposium, 23-27 April 2018, Taipei, Taiwan Cognitive Management in a Cyber World. Peer reviewed |
FALK, E., FIZ PONTIVEROS, B., Repcek, S., HOMMES, S., STATE, R., & Sasnauskas, R. (2017). VSOC - A Virtual Security Operating Center. Global Communications. doi:10.1109/GLOCOM.2017.8254427 Peer reviewed |
CHARLIER, J. H. J., STATE, R., & Hilger, J. (2017). Modeling Smart Contracts Activities: A Tensor based Approach. In J. Charlier, R. STATE, ... J. Hilger, Proceedings of 2017 Future Technologies Conference (FTC), 29-30 November 2017, Vancouver, Canada (pp. 49-55). IEEE. Peer reviewed |
DU, M., SASSIOUI, R., VARISTEAS, G., STATE, R., Brorsson, M., & Cherkaoui, O. (2017). Improving Real-Time Bidding Using a Constrained Markov Decision Process. In Proceedings of the 13th International Conference on Advanced Data Mining and Applications (pp. 711-726). Springer. doi:10.1007/978-3-319-69179-4_50 Peer reviewed |
FALK, E., CHARLIER, J. H. J., & STATE, R. (2017). Your Moves, Your Device: Establishing Behavior Profiles Using Tensors. In Advanced Data Mining and Applications - 13th International Conference, ADMA 2017 (pp. 460-474). Peer reviewed |
HOMMES, S., Valtchev, P., Blaiech, K., Hamadi, S., Cherkaoui, O., & STATE, R. (2017). Optimising Packet Forwarding in Multi-Tenant Networks using Rule Compilation. In Optimising Packet Forwarding in Multi-Tenant Networks using Rule Compilation. IEEE. Peer reviewed |
SIGNORELLO, S., Marchal, S., François, J., Festor, O., & STATE, R. (30 October 2017). Advanced Interest Flooding Attacks in Named-Data Networking [Paper presentation]. The 16th IEEE International Symposium on Network Computing and Applications (NCA 2017), Cambridge, MA, United States. |
HAMMERSCHMIDT, C., Garcia, S., Verwer, S., & STATE, R. (October 2017). Reliable Machine Learning for Networking: Key Concerns and Approaches [Poster presentation]. The 42nd IEEE Conference on Local Computer Networks (LCN), Singapore, Singapore. |
GLAUNER, P., MEIRA, J. A., STATE, R., & Mano, R. (September 2017). Introduction to Detection of Non-Technical Losses using Data Analytics [Paper presentation]. 7th IEEE Conference on Innovative Smart Grid Technologies, Europe (ISGT Europe 2017), Torino, Italy. |
GLAUNER, P., MIGLIOSI, A., MEIRA, J. A., VALTCHEV, P., STATE, R., & Bettinger, F. (2017). Is Big Data Sufficient for a Reliable Detection of Non-Technical Losses? In Proceedings of the 19th International Conference on Intelligent System Applications to Power Systems (ISAP 2017). Peer reviewed |
CHARLIER, J. H. J., LAGRAA, S., STATE, R., & Francois, J. (2017). Profiling Smart Contracts Interactions Tensor Decomposition and Graph Mining. 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 (pp. 31-42). Peer reviewed |
FALK, E., Gurbani, V. K., & STATE, R. (August 2017). Query-able Kafka: An agile data analytics pipeline for mobile wireless networks. Proceedings of the 43rd International Conference on Very Large Data Bases 2017, 10, 1646-1657. Peer reviewed |
HAMMERSCHMIDT, C., STATE, R., & Verwer, S. (August 2017). Human in the Loop: Interactive Passive Automata Learning via Evidence-Driven State-Merging Algorithms [Poster presentation]. Human in the Loop Machine Learning Workshop at the International Conference on Machine Learning, Sydney, Australia. |
Blaiech, K., Hamadi, S., HOMMES, S., VALTCHEV, P., Cherkaoui, O., & STATE, R. (2017). Rule Compilation in Multi-Tenant Networks. In Rule Compilation in Multi-Tenant Networks (pp. 97-98). Beijing, China: IEEE. doi:10.1109/ANCS.2017.34 Peer reviewed |
Gurbani, V. K., Kushnir, D., Mendiratta, V. B., Phadke, C., FALK, E., & STATE, R. (2017). Detecting and predicting outages in mobile networks with log data. In IEEE International Conference on Communications, ICC 2017 (pp. 1-7). doi:10.1109/ICC.2017.7996706 Peer reviewed |
FALK, E., CAMINO, R. D., STATE, R., & Gurbani, V. K. (2017). On non-parametric models for detecting outages in the mobile network. In Integrated Network and Service Management 2017 (pp. 1139-1142). doi:10.23919/INM.2017.7987448 Peer reviewed |
GLAUNER, P., MEIRA, J. A., VALTCHEV, P., STATE, R., & Bettinger, F. (2017). The Challenge of Non-Technical Loss Detection using Artificial Intelligence: A Survey. International Journal of Computational Intelligence Systems, 10 (1), 760-775. doi:10.2991/ijcis.2017.10.1.51 Peer reviewed |
ANTONELO, E. A., & STATE, R. (2017). Recurrent Dynamical Projection for Time series-based Fraud detection. In ICANN 2017, Part II, LNCS 10614. Peer reviewed |
GLAUNER, P., Dahringer, N., Puhachov, O., MEIRA, J. A., Valtchev, P., STATE, R., & Duarte, D. (2017). Identifying Irregular Power Usage by Turning Predictions into Holographic Spatial Visualizations. In Proceedings of the 17th IEEE International Conference on Data Mining Workshops (ICDMW 2017). Peer reviewed |
MEIRA, J. A., GLAUNER, P., STATE, R., VALTCHEV, P., DOLBERG, L., Bettinger, F., & Duarte, D. (2017). Distilling Provider-Independent Data for General Detection of Non-Technical Losses. In Power and Energy Conference, Illinois 23-24 February 2017. Peer reviewed |
GLAUNER, P., DU, M., Paraschiv, V., BOYTSOV, A., Lopez Andrade, I., MEIRA, J. A., VALTCHEV, P., & STATE, R. (2017). The Top 10 Topics in Machine Learning Revisited: A Quantitative Meta-Study. In Proceedings of the 25th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2017). Peer reviewed |
LAGRAA, S., François, J., Lahmadi, A., Minier, M., HAMMERSCHMIDT, C., & STATE, R. (2017). BotGM: Unsupervised Graph Mining to Detect Botnets in Traffic Flows. In CSNet 2017 Conference Proceedings. Peer reviewed |
NORVILL, R., FIZ PONTIVEROS, B., STATE, R., Awan, I., & Cullen, A. (2017). Automated labeling of unknown contracts in Ethereum. In Computer Communication and Networks (ICCCN), 2017 26th International Conference on. doi:10.1109/ICCCN.2017.8038513 Peer reviewed |
STEICHEN, M., HOMMES, S., & STATE, R. (2017). ChainGuard - A Firewall for Blockchain Applications using SDN with OpenFlow. In ChainGuard - A Firewall for Blockchain Applications using SDN with OpenFlow. Peer reviewed |
CAMINO, R. D., STATE, R., MONTERO, L., & VALTCHEV, P. (2017). Finding Suspicious Activities in Financial Transactions and Distributed Ledgers. In Proceedings of the 17th IEEE International Conference on Data Mining Workshops (ICDMW 2017). Peer reviewed |
FIZ PONTIVEROS, B., HOMMES, S., & STATE, R. (2017). Confirmation Delay Prediction of Transactions in the Bitcoin Network. Lecture Notes in Electrical Engineering. doi:10.1007/978-981-10-7605-3_88 Peer reviewed |
GLAUNER, P., & STATE, R. (09 December 2016). Deep Learning on Big Data Sets in the Cloud with Apache Spark and Google TensorFlow [Paper presentation]. 9th IEEE/ACM International Conference on Utility and Cloud Computing (UCC 2016), Shanghai, China. |
HAMMERSCHMIDT, C., Verwer, S., Lin, Q., & STATE, R. (2016). Interpreting Finite Automata for Sequential Data. Interpretable Machine Learning for Complex Systems: NIPS 2016 workshop proceedings. Peer reviewed |
DU, M., STATE, R., Brorsson, M., & Avanesov, T. (2016). Behavior Profiling for Mobile Advertising. In Proceedings of the 3rd IEEE/ACM International Conference on Big Data Computing, Applications and Technologies (pp. 302-307). ACM. doi:10.1145/3006299.3006339 Peer reviewed |
HAMMERSCHMIDT, C., Marchal, S., Pellegrino, G., STATE, R., & Verwer, S. (November 2016). Efficient Learning of Communication Profiles from IP Flow Records [Poster presentation]. The 41st IEEE Conference on Local Computer Networks (LCN). |
GLAUNER, P., & STATE, R. (09 October 2016). Load Forecasting with Artificial Intelligence on Big Data [Paper presentation]. Sixth IEEE Conference on Innovative Smart Grid Technologies, Europe (ISGT Europe 2016), Ljubljana, Slovenia. |
HAMMERSCHMIDT, C., Marchal, S., STATE, R., & Verwer, S. (October 2016). Behavioral Clustering of Non-Stationary IP Flow Record Data [Poster presentation]. 12th International Conference on Network and Service Management. |
HAMMERSCHMIDT, C., LOOS, B. L., Verwer, S., & STATE, R. (October 2016). Flexible State-Merging for learning (P)DFAs in Python [Paper presentation]. The 13th International Conference on Grammatical Inference. |
Hamadi, S., Blaiech, K., VALTCHEV, P., Cherkaoui, O., & STATE, R. (2016). Compiling packet forwarding rules for switch pipelined architecture. In IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications. Peer reviewed |
SIGNORELLO, S., STATE, R., François, J., & Festor, O. (2016). NDN.p4: Programming Information-Centric data-planes. Proceedings of the IEEE International Workshop on Open-Source Software Networking at NetSoft2016. doi:10.1109/NETSOFT.2016.7502472 Peer reviewed |
GLAUNER, P., & STATE, R. (19 January 2016). Deep Learning Concepts from Theory to Practice [Paper presentation]. FinTech R&D Innovation Conference, Luxembourg, Luxembourg. |
GLAUNER, P., Boechat, A., Dolberg, L., STATE, R., Bettinger, F., Rangoni, Y., & Duarte, D. (2016). Large-Scale Detection of Non-Technical Losses in Imbalanced Data Sets. In Proceedings of the Seventh IEEE Conference on Innovative Smart Grid Technologies (ISGT 2016). Peer reviewed |
GLAUNER, P., MEIRA, J. A., Dolberg, L., STATE, R., Bettinger, F., Rangoni, Y., & Duarte, D. (2016). Neighborhood Features Help Detecting Non-Technical Losses in Big Data Sets. In Proceedings of the 3rd IEEE/ACM International Conference on Big Data Computing Applications and Technologies (BDCAT 2016). doi:10.1145/3006299.3006310 Peer reviewed |
SIGNORELLO, S., STATE, R., & Festor, O. (2015). Exploring IoT Protocols Through the Information-Centric Networking's Lens. In Intelligent Mechanisms for Network Configuration and Security (Lecture Notes in Computer Science). Springer. doi:10.1007/978-3-319-20034-7_6 Peer reviewed |
ALLIX, K., BISSYANDE, T. F. D. A., JEROME, Q., KLEIN, J., STATE, R., & LE TRAON, Y. (2014). Empirical assessment of machine learning-based malware detectors for Android: Measuring the Gap between In-the-Lab and In-the-Wild Validation Scenarios. Empirical Software Engineering, 1-29. doi:10.1007/s10664-014-9352-6 Peer Reviewed verified by ORBi |
MARCHAL, S., FRANÇOIS, J., STATE, R., & ENGEL, T. (December 2014). PhishStorm: Detecting Phishing With Streaming Analytics. IEEE Transactions on Network and Service Management, 11 (December), 458-471. doi:10.1109/TNSM.2014.2377295 Peer Reviewed verified by ORBi |
MARCHAL, S., FRANÇOIS, J., STATE, R., & ENGEL, T. (2014). PhishScore: Hacking Phishers' Minds. Proceedings of the 10th International Conference on Network and Service Management, 46-54. doi:10.1109/CNSM.2014.7014140 Peer reviewed |
MARCHAL, S., Jiang, X., STATE, R., & ENGEL, T. (2014). A Big Data Architecture for Large Scale Security Monitoring. In Proceedings of the 3rd IEEE Congress on Big Data (pp. 56-63). IEEE. doi:10.1109/BigData.Congress.2014.18 Peer reviewed |
ALLIX, K., JEROME, Q., BISSYANDE, T. F. D. A., KLEIN, J., STATE, R., & LE TRAON, Y. (2014). A Forensic Analysis of Android Malware -- How is Malware Written and How It Could Be Detected? In Proceedings of the 2014 IEEE 38th Annual Computer Software and Applications Conference (pp. 384--393). Washington, DC, USA, Unknown/unspecified: IEEE Computer Society. doi:10.1109/COMPSAC.2014.61 Peer reviewed |
JEROME, Q., ALLIX, K., STATE, R., & ENGEL, T. (2014). Using opcode-sequences to detect malicious Android applications. In IEEE International Conference on Communications, ICC 2014, Sydney Australia, June 10-14, 2014. Sydney, Australia: IEEE. doi:10.1109/ICC.2014.6883436 Peer reviewed |
ALLIX, K., BISSYANDE, T. F. D. A., JEROME, Q., KLEIN, J., STATE, R., & LE TRAON, Y. (2014). Large-scale Machine Learning-based Malware Detection: Confronting the "10-fold Cross Validation" Scheme with Reality. In Proceedings of the 4th ACM Conference on Data and Application Security and Privacy (pp. 163--166). New York, NY, USA, Unknown/unspecified: ACM. doi:10.1145/2557547.2557587 Peer reviewed |
HERMANN, F., HOMMES, S., STATE, R., & ENGEL, T. (2014). Correctness of source code extension for fault detection in openflow based networks. (TR-SnT-2014-2). Luxembourg, Luxembourg: SnT. https://orbilu.uni.lu/handle/10993/15749 |
HOMMES, S., STATE, R., & ENGEL, T. (2014). Implications and Detection of DoS Attacks in OpenFlow-based Networks. In 2014 IEEE Global Communications Conference (pp. 537-543). doi:10.1109/GLOCOM.2014.7036863 Peer reviewed |
GOERGEN, D., Gurbani, V., & STATE, R. (15 October 2013). Of maps and costs: Aggregating large-scale broadband measurements for the Application Layer Traffic Optimization (ALTO) protocol [Paper presentation]. IIT RTC Conference, Chicago, United States. |
HOMMES, S., HERMANN, F., STATE, R., & ENGEL, T. (2013). Automated Source Code Extension for Debugging of OpenFlow based Networks. In Proc. 9th International Conference on Network and Service Management (CNSM) (pp. 105-108). doi:10.1109/CNSM.2013.6727816 Peer reviewed |
HOMMES, S., STATE, R., & ENGEL, T. (2013). Classification of Log Files with Limited Labeled Data. In Proceedings of IPTComm 2013. doi:10.1145/2554666.2554668 Peer reviewed |
GOERGEN, D., Mendiratta, V., STATE, R., & ENGEL, T. (2013). Identifying abnormal pattern in cellular communication flows. In Proceedings of IPTComm 2013. ACM. doi:10.1145/2554666.2554671 Peer reviewed |
JEROME, Q., MARCHAL, S., STATE, R., & ENGEL, T. (2013). Advanced Detection Tool for PDF Threats. In Proceedings of the sixth International Workshop on Autonomous and Spontaneous Security, RHUL, Egham, U.K., 12th-13th September 2013. Springer. Peer reviewed |
GOERGEN, D., STATE, R., & Gurbani, V. (July 2013). Aggregating large-scale measurements for Application Layer Traffic Optimization (ALTO) Protocol [Paper presentation]. 87th IETF Meeting, Berlin, Germany. |
WAGNER, C., FRANÇOIS, J., STATE, R., DULAUNOY, A., ENGEL, T., & Massen, G. (2013). ASMATRA: Ranking ASs Providing Transit Service to Malware Hosters. IFIP/IEEE International Symposium on Integrated Network Management IM2013, 1-9. Peer reviewed |
MARCHAL, S., FRANÇOIS, J., STATE, R., & ENGEL, T. (2012). Semantic based DNS Forensics. In Proceedings of the IEEE International Workshop on Information Forensics and Security (pp. 91 - 96). IEEE. doi:10.1109/WIFS.2012.6412631 Peer reviewed |
MARCHAL, S., FRANÇOIS, J., STATE, R., & ENGEL, T. (2012). Proactive Discovery of Phishing Related Domain Names. In Proceedings of the 15th International Symposium on Research in Attacks, Intrusions and Defenses, Amsterdam 12-14 September 2012 (pp. 190-209). Springer Berlin Heidelberg. doi:10.1007/978-3-642-33338-5_10 Peer reviewed |
HOMMES, S., STATE, R., & ENGEL, T. (2012). A Distance-Based Method to Detect Anomalous Attributes in Log Files. In Proceedings of IEEE/IFIP NOMS 2012 (pp. 498-501). doi:10.1109/NOMS.2012.6211940 Peer reviewed |
MARCHAL, S., FRANÇOIS, J., WAGNER, C., STATE, R., DULAUNOY, A., ENGEL, T., & Festor, O. (2012). DNSSM: A large-scale Passive DNS Security Monitoring Framework. IEEE/IFIP Network Operations and Management Symposium, 988 - 993. doi:10.1109/NOMS.2012.6212019 Peer reviewed |
HOMMES, S., STATE, R., & ENGEL, T. (2012). Detecting Stealthy Backdoors with Association Rule Mining. In IFIP Networking 2012 (pp. 161-171). Springer. Peer reviewed |
RIES, T., STATE, R., & ENGEL, T. (2012). Instant Degradation of Anonymity in Low-Latency Anonymisation Systems. In R. Sadre, J. Novotny, P. Celeda, M. Waldburger, ... B. Stiller (Eds.), Dependable Networks and Services, LNCS 7279 (pp. 98-108). Heidelberg. Peer reviewed |
HOMMES, S., STATE, R., ZINNEN, A., & ENGEL, T. (2011). Detection of Abnormal Behaviour in a Surveillance Environment Using Control Charts. In 8th IEEE International Conference on Advanced Video and Signal-Based Surveillance, 2011 (pp. 113-118). doi:10.1109/AVSS.2011.6027304 Peer reviewed |
RIES, T., STATE, R., & ENGEL, T. (2011). Measuring anonymity using network coordinate systems. In International Symposium on Communications and Information Technologies (ISCIT), 2011 (pp. 366-371). doi:10.1109/ISCIT.2011.6089954 Peer reviewed |
RIES, T., PANCHENKO, A., STATE, R., & ENGEL, T. (2011). Comparison of Low-Latency Anonymous Communication Systems - Practical Usage and Performance. In Ninth Australasian Information Security Conference (pp. 77-86). ACS. Peer reviewed |
BECKER, S., Abdelnur, H. J., STATE, R., & ENGEL, T. (2010). An Autonomic Testing Framework for IPv6 Configuration Protocols. In Lecture Notes in Computer Science 6155 (pp. 65 - 76). Springer. doi:10.1007/978-3-642-13986-4_7 Peer reviewed |
FRANÇOIS, J., Abdelnur, H. J., STATE, R., & Festor, O. (2010). Machine Learning Techniques for Passive Network Inventory. IEEE Transactions on Network and Service Management, 7 (4), 244 - 257. doi:10.1109/TNSM.2010.1012.0352 Peer Reviewed verified by ORBi |
BECKER, S., STATE, R., & ENGEL, T. (2009). Defensive configuration with game theory. The 11th IFIP/IEEE International Symposium on Integrated Network Management. doi:10.1109/INM.2009.5188848 Peer reviewed |
BECKER, S., STATE, R., & ENGEL, T. (2009). Using Game Theory to configure P2P SIP. Lecture Notes in Computer Science. doi:10.1145/1595637.1595645 Peer reviewed |
Abdelnur, H. J., AVANESOV, T., Rusinowitch, M., & STATE, R. (2009). Abusing SIP authentication. Journal of Information Assurance and Security, 4, 311–318. Peer Reviewed verified by ORBi |