Costas Bassias

Title: Costas Bassias: Innovator in Cybersecurity Data Analysis

Introduction

Costas Bassias is a notable inventor based in San Jose, CA (US). He has made significant contributions to the field of cybersecurity through his innovative methods for data analysis. His work focuses on enhancing the detection of cyber threats by analyzing behavioral features derived from log data.

Latest Patents

Costas Bassias holds 1 patent for his invention titled "Method and system for learning representations for log data in cybersecurity." This patent discloses a data analysis and cybersecurity method that forms a time-based series of behavioral features. The method analyzes these features for attack detection, new feature derivation, and features evaluation. The analysis may involve various advanced techniques, including Feed-Forward Neural Networks (FFNN), Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), Long Short-Term Memories (LSTMs), principal Component Analysis (PCA), Random Forest pipeline methods, and autoencoders. The behavioral features can include both human-engineered and machine-learned features, allowing the method to learn new features from historical data.

Career Highlights

Throughout his career, Costas has demonstrated a strong commitment to advancing cybersecurity technologies. His innovative approach to data analysis has positioned him as a key figure in the field. His work not only addresses current cybersecurity challenges but also paves the way for future advancements.

Collaborations

Costas Bassias has collaborated with talented individuals such as Ignacio Arnaldo and Ankit Arun. These collaborations have contributed to the development and refinement of his innovative methods in cybersecurity.

Conclusion

Costas Bassias is a pioneering inventor whose work in cybersecurity data analysis is making a significant impact. His innovative methods for analyzing log data are essential for enhancing security measures against cyber threats.