Ferda Ozdemir Sonmez | Smart Contract Security | Best Researcher Award

Published on by Innovation Technologist

Dr. Ferda Ozdemir Sonmez | Smart Contract Security | Best Researcher Award

University of West London at Imperial College of London, United Kingdom

Dr. Ferda Ozdemir Sonmez is an expert in cybersecurity and data visualization with a focus on enterprise security systems, security metrics, and decision support systems. With extensive experience in both academic research and practical applications, [Your Name] has contributed to various conferences, books, and journals, particularly in the areas of security visualization, big data technologies, and smart contracts for cybersecurity. [Your Name] has been involved in numerous scholarly projects aimed at enhancing security measures, predictive analytics, and system efficiency in digital environments.

Publication Profile :Β 

Scopus

Educational Background πŸŽ“

  • MIT Online (Ongoing): Micro MSc in Statistics and Data Science (2020)
  • Middle East Technical University, Ankara: PhD in Information Systems (Cybersecurity Focus, 2019)
  • Middle East Technical University, Ankara: MSc in Information Systems (Cybersecurity Focus, 2014)
  • Middle East Technical University, Ankara: BSc in Electrical & Electronic Engineering (Computer Option, 1997)

Professional Experience πŸ’Ό

University of West London, Department of Computing
Senior Lecturer of Cybersecurity – Computer Scientist
11/2024 – Present

  • Delivered courses on cybersecurity fundamentals, threat intelligence, and applied cryptography.
  • Supervised MSc and PhD students, supported by advanced research in cybersecurity.
  • Authored grant applications and collaborated on cutting-edge curriculum design.

Imperial College, Department of Computing
Research Associate – Computer Scientist
11/2022 – Present

  • Researched secure blockchain technologies, including DAOs and voting systems.
  • Published peer-reviewed papers on smart contract security and generative language modeling.
  • Developed innovative solutions for multi-chain systems and account management.

Queen Mary University, ITS
Technical Analyst
10/2022 – 08/2024

  • Solved IT issues for bespoke and vendor applications, enhancing database efficiency.
  • Supported developers through troubleshooting and scripting solutions.

Imperial College, Security Science and Technology
Research Associate – Computer Scientist
11/2020 – 09/2022

  • Designed tools for security optimization, including a penetration testing planner.
  • Published academic papers on cost optimization and attack graph detection.

YΔ±ldΔ±rΔ±m BeyazΔ±t University
Part-Time Lecturer
09/2019 – 01/2020

  • Delivered graduate-level courses in blockchain, network security, and web application standards.
  • Received positive feedback for engaging and informative lecture delivery.

Honors and Achievements

  • Royal Academy of Engineering Endorsement: Recognized for exceptional skills and achievements in computer science and engineering.
  • University Entrance Ranking: Ranked within the top 0.02% of candidates in Turkey, placing in the top 300 out of approximately 1.5 million participants.

Technical Skills

Operating Systems: Linux, Unix, Windows 10
Programming Languages: Java, C#, Python, Solidity, and more.
Data Science Tools: TensorFlow, Keras, Scikit-learn, GPT libraries, SPSS.
Cybersecurity Tools: OWASP ZAP, Wireshark, Microsoft Threat Modeling, STRIDE.
DevOps & Platforms: Docker, Kubernetes, Git, Hadoop.
Database Management: Oracle, MySQL, MS SQL Server, LDAP.
Business Intelligence: Tableau, Apache Ambari.

Publications πŸ“š

  • πŸ“š Security Visualization Extended Review Issues, Classifications, Validation Methods, Trends, Extensions (2018) – IGI Global | Security and Privacy Management, Techniques, and Protocols [DOI: 10.4018/978-1-5225-5583-4.ch006]
  • πŸ“„ Qualitative and Quantitative Results of Enterprise Security Visualization Requirements Analysis through Surveying (2019) – IVAPP | 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications [DOI: 10.5220/0007255401750182]
  • πŸ“š Big Data Technologies– Supported Generic Visualization System in an Enterprise Cyber-Physical Environment (2019) – CRC Press | Cybersecurity and Privacy in Cyber-Physical Systems [DOI: 10.1201/9780429263897]
  • πŸ“° Holistic Web Application Security Visualization for Multi-Project and Multi-Phase Dynamic Application Security Test Results (2021) – IEEE | IEEE Access [DOI: 10.1109/ACCESS.2021.3057044]
  • πŸ“„ Evaluation of Security Information and Event Management Systems for Custom Security Visualization Generation (2018) – IEEE | International Congress on Big Data, Deep Learning and Fighting Cyber Terrorism [DOI: 10.1109/IBIGDELFT.2018.8625291]
  • πŸ“° A Decision Support System for Optimal Selection of Enterprise Information Security Preventative Actions (2020) – IEEE | IEEE Transactions on Network and Service Management [DOI: 10.1109/TNSM.2020.3044865]
  • πŸ“„ Development of Automated Remote Security Prototype Base on IOT Technologies on IBM Bluemix Platform (2016) – ISCTurkey | 9th International Conference on Information Security and Cryptology [ISBN: 978-605-86904-6-2]
  • πŸ“š Prediction of Satisfaction with Life Scale Using Linguistic Features from Facebook Status Updates: Smart Life (2021) – Springer | Machine Intelligence and Data Analytics for Sustainable Future Smart Cities [DOI: 10.1007/978-3-030-72065-0_8]
  • πŸ“„ Security Qualitative Metrics for Open Web Application Security Project Compliance (2019) – Elsevier | International Symposium on Machine Learning and Big Data Analytics for Cybersecurity and Privacy (MLBDACP) [DOI: 10.1016/j.procs.2019.04.140]
  • πŸ“„ A Conceptual Model for a Metric Based Framework for the Monitoring of Information Security Tasks’ Efficiency (2019) – Elsevier | International Conference on Emerging Ubiquitous Systems and Pervasive Networks [DOI: 10.1016/j.procs.2019.09.459]