Oresteban Carabeo

Dedicated and knowledgeable Computer Science Instructor with extensive experience in higher education and a Ph.D. candidate in Artificial Intelligence. Proven expertise in distance education, AI, and machine learning, with a strong commitment to fostering diverse learning environments and student success. Demonstrated ability to adapt instructional methods to meet individual student needs and enhance learning outcomes.

• Collaborated with team of inventors in the development of a patent titled: Methods, System and Point-to-Point Encryption Device Microchip for AES-SEA 512-Bit Key Using Identity Access Management Utilizing Blockchain Ecosystem to Improve Cybersecurity.

• Deep Learning Onramp (MathWorks, Issued May 2024)
• Skills: Deep Learning, Natural Language Processing (NLP)
• Computer Vision Onramp (MathWorks, Issued Apr 2024)
• Skills: Computer Vision

• Zero Knowledge Proof (ZKP) is a cryptographic protocol that allows one party (the prover) to prove to another party (the verifier) the validity of a statement without revealing any additional information. It ensures that sensitive data remains confidential while still enabling verification of its authenticity. ZKP can be applied in various scenarios, such as authentication processes, identity verification, and secure communication channels. In the context of cybersecurity, ZKP can be utilized to establish trust between entities and enhance the privacy of sensitive information. ZKP can be utilized in autonomous vehicles to establish trust and verify the authenticity of various interactions within the vehicle's ecosystem. For instance, ZKP can be employed to prove the integrity of software updates, ensuring that they have not been tampered with and are coming from trusted sources. This prevents malicious actors from injecting harmful code into the vehicle's systems, safeguarding against potential cyber attacks.
• Quantum computing, on the other hand, leverages the principles of quantum mechanics to perform complex computations at an unprecedented scale. Unlike classical computers that use bits to represent information as either 0 or 1, quantum computers utilize quantum bits or qubits, which can exist in multiple states simultaneously due to the phenomena of superposition and entanglement. This enables quantum computers to solve problems exponentially faster than classical computers, including breaking certain cryptographic algorithms widely used for securing data. However, quantum computing also presents an opportunity for developing post-quantum cryptographic algorithms that resist attacks from quantum computers. Quantum computing can contribute to the security of autonomous vehicles by enabling the development of post-quantum cryptographic algorithms. As quantum computers advance, traditional cryptographic algorithms used to secure communications and data may become vulnerable. By leveraging the power of quantum computing, new encryption methods can be devised that withstand attacks from quantum computers. This ensures that the sensitive data transmitted within autonomous vehicles remains secure throughout its lifecycle.
• Artificial intelligence (AI) plays a crucial role in analyzing vast amounts of data and identifying patterns, thus enabling proactive defense against cyber attacks. By utilizing machine learning algorithms, AI systems can learn from historical attack data, network traffic patterns, and system vulnerabilities to detect and prevent potential cyber threats. AI can also automate the process of identifying and responding to attacks in real-time, reducing the time and effort required for human intervention. Additionally, AI can assist in anomaly detection, user behavior analysis, and risk assessment, thereby strengthening overall cybersecurity measures. AI plays a vital role in the functionality and security of autonomous vehicles. AI algorithms can analyze and interpret vast amounts of sensor data, including visual inputs, radar readings, and communication signals, to make real-time decisions and ensure safe driving. Additionally, AI can detect anomalies in the vehicle's behavior or network traffic, identifying potential cyber threats or attempts to manipulate the vehicle's systems. By continuously learning from patterns and historical data, AI systems in autonomous vehicles can adapt and become more resilient against emerging cyber threats.
• The combination of these technologies enhances the overall security and integrity of autonomous vehicles. Zero Knowledge Proof establishes trust and integrity in the vehicle's ecosystem, quantum computing ensures robust encryption methods that resist attacks from quantum computers, and artificial intelligence provides real-time threat detection and response capabilities. By integrating these technologies, autonomous vehicles can operate with enhanced security, minimizing the risk of cyber attacks and ensuring the safety of passengers and the surrounding environment.