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Δρ. Μιλτιάδης Σιάββας -
Δημοσιεύσεις

Δημοσιεύσεις Σε Περιοδικά

  1. I. Kalouptsoglou, M. Siavvas, A. Ampatzoglou, D. Kehagias, A. Chatzigeorgiou, "Software vulnerability prediction: A systematic mapping study.", Information and Software Technology, Volume 164, 2023, 107303, ISSN 0950-5849. https://doi.org/10.1016/j.infsof.2023.107303
  2. M. Siavvas, D. Tsoukalas, I. Kalouptsoglou, E. Manganopoulou, G. Manolis, D. Kehagias, D. Tzovaras, "Security Monitoring during Software Development: An Industrial Case Study.", Applied Sciences. 2023; 13(12):6872. https://doi.org/10.3390/app13126872
  3. D. Tsoukalas, M. Siavvas, D. Kehagias, A. Chatzigeorgiou, A. Ampatzoglou, "A practical approach for technical debt prioritization based on class-level forecasting.", In Journal of Software: Evolution and Process (JSME), Wiley, 2023;e2564. DOI: 10.1002/smr.2564
  4. M. Siavvas, D. Tsoukalas, M. Jankovic, D. Kehagias, D. Tzovaras, "Technical debt as an indicator of software security risk: a machine learning approach for software development enterprises", Enterprise Information Systems. 16(5):1824017, 2022.
  5. I. Kalouptsoglou, M. Siavvas, D. Kehagias, A. Chatzigeorgiou, A. Ampatzoglou, "Examining the Capacity of Text Mining and Software Metrics in Vulnerability Prediction", Entropy. 5;24(5):651, 2022.
  6. I. Kalouptsoglou, D. Tsoukalas, M. Siavvas, D. Kehagias, A. Chatzigeorgiou, A. Ampatzoglou, "Time Series Forecasting of Software Vulnerabilities Using Statistical and Deep Learning Models", . Electronics. 11(18):2820, 2022.
  7. C. Lamprakos, C. Marantos, M. Siavvas, L. Papadopoulos, A. Tsintzira, A.Ampatzoglou, A. Chatzigeorgiou, D. Kehagias, D. Soudris, "TranslatingQuality-Driven Code Change Selection to an Instance of Multiple-CriteriaDecision Making", Information and Software Technology, Elsevier, 2022.
  8. E. Gelenbe, M. Siavvas, "Minimizing energy and computation in long-running software.", Applied Sciences. 2021. (Impact Factor: 2.838)
  9. K. Filus, P. Boryszko, J. Domańska, M. Siavvas, E. Gelenbe,, "Efficient feature selection for static analysis vulnerability prediction.", Sensors. 2021. (Impact Factor: 3.847)
  10. D. Tsoukalas, M. Mathioudaki, M. Siavvas, D. Kehagias, A. Chatzigeorgiou, "A clustering approach towards cross-project technical debt forecasting.", SN Computer Science, 2(1), 1-30. (2021)
  11. D. Kehagias, M. Jankovic, M. Siavvas, E. Gelenbe, "Investigating the interaction between energy consumption, quality of service, reliability, security, and maintainability of computer systems and networks.", SN Computer Science, 2(1), 1-6. (2021)
  12. M. Siavvas, D. Kehagias, D. Tzovaras, E. Gelenbe, "A hierarchical model for quantifying software security based on static analysis alerts and software metrics.", Software Quality Journal, 29(2), 431-507. (2021)
  13. D. Tsoukalas, D. Kehagias, M. Siavvas, A. Chatzigeorgiou, "Technical Debt Forecasting: An empirical study on open-source repositories", In: Journal of Systems and Software, vol. 170, p. 110777 (2020). DOI https://doi.org/10.1016/j.jss.2020.110777
  14. M. Siavvas, D. Tsoukalas, M. Jankovic, D. Kehagias, D. Tzovaras, "Technical debt as an indicator of software security risk: a machine learning approach for software development enterprises", Enterprise Information Systems 0(0), 1{43 (2020). DOI 10.1080/17517575.2020.1824017
  15. M. Siavvas, E. Gelenbe, "Optimum Checkpoints for Programs with Loops", Simulation Modelling Practice and Theory, Elsevier, vol. 97, 2019. (Impact Factor: 4.199)
  16. M. Siavvas, K. Chatzidimitriou, A. Symeonidis, "QATCH - An adaptive framework for software product quality assessment.", Expert Systems with Applications, Elsevier, vol. 86, p. 350-366, 2017. (Impact Factor: 8.665)

Δημοσιεύσεις Σε Συνέδρια

  1. I. Kalouptsoglou, M. Siavvas, A. Ampatzoglou, D. Kehagias, A. Chatzigeorgiou, "An empirical comparison of Transformer-based models in Vulnerability Prediction.",The 23rd International Conference on Computational Science and Its Applications, May 2023.
  2. M. Mathioudaki, D. Tsoukalas, M. Siavvas, D. Kehagias, "Comparing Univariate and Multivariate Time Series Models for Technical Debt Forecasting", in 22nd International Conference on Computational Science and Its Applications (ICCSA 2022), July 4 - 7, 2022, Malaga, Spain
  3. M. Siavvas, E. Gelenbe, D. Tsoukalas, I. Kalouptsoglou, M. Mathioudaki, M. Nakip, D. Kehagias, D. Tzovaras, "The IoTAC Software Security-by-Design Platform: Concept, Challenges, and Preliminary Overview", . In 2022 18th International Conference on the Design of Reliable Communication Networks (DRCN) 2022 Mar 28 (pp. 1-6). IEEE.
  4. C. Marantos, M. Siavvas, D. Tsoukalas, C. Lamprakos, L. Papadopoulos, P. Boryszko, K. Filus, J. Domanska, A. Ampatzoglou, A. Chatzigeorgiou, E.Gelenbe, D. Kehagias, D. Soudris, "SDK4ED: One-click platform forEnergy-aware, Maintainable and Dependable Applications", 25th Design,Automation and Test in Europe Conference (DATE '22), Belgium, 2022.
  5. M. A. Siddiqi, A. A. Tsintzira, G. Digkas, M. Siavvas, C. Strydis, "Adding Security to Implantable Medical Devices: Can We Afford It?", Proceedings of the 2021 International Conference on Embedded Wireless Systems and Networks, 67–78.
  6. K. Filus, M. Siavvas, J. Domanska, E. Gelenbe, "The Random Neural Network as a Bonding Model for Software Vulnerability Prediction", Proceedings of the Symposium on the Interaction between Energy Consumption, Quality of Service, Reliability and Security, Maintainability of Computer Systems and Networks (EQSEM), 2020.
  7. E. Gelenbe, P. Boryszko, M. Siavvas, J. Domanska, "Optimum Checkpoints for Time and Energy", In 2020 IEEE 28th International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS), IEEE, 2020.
  8. M. Siavvas, I. Kalouptsoglou, D. Tsoukalas, D. Kehagias, "A self-adaptive approach for assessing thecriticality of security-related static analysis alerts", 21st International Conference on Computational Science and Applications (ICCSA 2021)
  9. M. Mathioudaki, D. Tsoukalas, M. Siavvas, D. Kehagias, "Technical Debt Forecasting based on Deep Learning Techniques", in 21st International Conference on Computational Science and Its Applications (ICCSA 2021)
  10. I. Kalouptsoglou, M. Siavvas, D. Kehagias, A. Chatzigeorgiou, A. Apostolos, "An Empirical Evaluation of the Usefulness of Word Embedding Techniques in Deep Learning-based Vulnerability Prediction", EuroCyberSec2021, Springer, LNCS, 2021
  11. E. Gelenbe, M. Nakip, I. Kalouptsoglou, M. Siavvas, D. Kehagias, "System Vulnerability Prediction using the Adversarial Random Neural Network", EuroCybersec 2021, Nice, France, 2021, Springer Cham., LNCS
  12. D. Tsoukalas, M. Siavvas, M. Mathioudaki, D. Kehagias, "An Ontology-based Approach for Automatic Specification, Verification, and Validation of Software Security Requirements: Preliminary Results", IEEE International Conference on Software Quality, Security, and Reliability, 2021, IEEE
  13. M. Jankovic, M. Siavvas, D. Tsoukalas, D. Kehagias, "Evaluating and Improving the Internal Security of OPC-UA based Software Applications", 10th International Conference on Interoperability for Enterprise Systems and Applications (I-ESA 2020),Trabes France, November 17-20 2020.
  14. I. Kalouptsoglou, M. Siavvas, D. Tsoukalas, D. Kehagias, "Cross-Project Vulnerability Prediction Based on Software Metrics and Deep Learning", In International Conference on Computational Science and Its Applications (pp. 877-893). Springer, Cham, 2020
  15. M. Siavvas, D. Tsoukalas, C. Marantos, A. Tsintzira, M. Jankovic, D. Soudris, A. Chatzigeorgiou, D. Kehagias, "The SDK4ED Platform for Embedded Software Quality Improvement-Preliminary Overview", In International Conference on Computational Science and Its Applications (pp. 1035-1050). Springer, Cham, 2020.
  16. M. Siavvas, E. Gelenbe, "Optimum Checkpointing for Long-running Programs", 15th China-Europe International Symposium on Software Engineering Education, IEEE, 2019.
  17. M. Siavvas, E. Gelenbe, "Optimum Interval for Application-level Checkpoints", 6th IEEE International Conference on Cyber Security and Cloud Computing (CSCloud), IEEE, 2019.
  18. D. Tsoukalas, M. Jankovic, M. Siavvas, D. Kehagias, A. Chatzigeorgiou, D. Tzovaras, "On the Applicability of Time Series Models for Technical Debt Forecasting",15th China-Europe International Symposium on Software Engineering Education (CEISEE). May 30 – 31, 2019.
  19. M. Jankovic, D. Kehagias, M. Siavvas, D. Tsoukalas, A. Chatzigeorgiou, "The SDK4ED Approach to Software Quality Optimization and Interplay Calculation", 15th China-Europe International Symposium on Software Engineering Education (CEISEE). May 30 – 31, 2019.
  20. M. Siavvas, C. Marantos, L. Papadopoulos, D. Kehagias, D. Soudris, D. Tzovaras, "On the Relationship between Software Security and Energy Consumption",15th China-Europe International Symposium on Software Engineering Education (CEISEE). May 30 – 31, 2019.
  21. M. Siavvas, D. Tsoukalas, M. Jankovic, D. Kehagias, A. Chatzigeorgiou, D. Tzovaras, N. Anicic, E. Gelenbe, "An Empirical Evaluation of the Relationship between Technical Debt and Software Security",9th International Conference on Information Society and Technology (ICIST2019), March, 10 – 13, 2019.
  22. D. Tsoukalas, M. Siavvas, M. Jankovic, D. Kehagias, A. Chatzigeorgiou, D. Tzovaras, "Methods and Tools for TD Estimation and Forecasting: A State-of-the-art Survey",In 2018 International Conference on Intelligent Systems (IS) (pp. 698-705). IEEE, (2018, September).
  23. M. Siavvas, M. Jankovic, D. Kehagias, D. Tzovaras, "Is Popularity an Indicator of Software Security?",In 2018 International Conference on Intelligent Systems (IS) (pp. 692-697). IEEE, (2018, September).
  24. M. Siavvas, E. Gelenbe, D. Kehagias, D. Tzovaras, "Static analysis-based approaches for secure software development", in Proceedings of the 2018 ISCIS Security Workshop: Recent Cybersecurity Research in Europe, vol. 821, Lecture Notes CCIS, Springer Verlag, London, UK, Feb. 2018.
  25. M. Siavvas, D. Kehagias, D. Tzovaras, "A Preliminary Study on the Relationship among Software Metrics and Specific Vulnerability Types", in the 2017 International Conference on Computational Science and Computational Intelligence – Symposium on Software Engineering (CSCI-ISSE), Las Vegas, USA, 14-16 Dec. 2017.
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