My Ph.D. thesis mainly focused on decentralized security solutions to attest, recover and update IoT networks. We designed and evaluated a decentralized scheme that distributes attestation among devices for systems that work in swarms. Our approach assures system resilience to node compromise/failure while guaranteeing only devices that execute genuine code remain part of the group. This decentralized approach was then extended to a scalable, efficient and secure mechanism of recovering a network of heterogeneous low-end devices in the presence of self-propagating malware. We demonstrated that swarm can be scaled up to thousands of devices, ensuring guaranteed update of the entire network. Finally, we explored and proposed a data-flow verification based decentralized swarm attestation mechanism for embedded devices. This technique focused on verifying runtime attacks that corrupt the underlying application’s security critical data without hijacking its control flow. Towards making embedded devices’ attestation complete, we combined both static and runtime verifications, assuring that the prover device executes the correct and unmodified program (i.e., checking if application is benign). I am currently focusing on integrating machine learning (ML) and Blockchain-based communication and security solutions into cyber-physical systems. For example, I am working on ”Fusion of Blockchain and Machine Learning: A case of Secure Smart Grid.”, AI-Powered Security for IoT: A Blockchain Enabled Device Twin Approach and Property-based attestation in device swarms: a machine learning approach. These approaches aim to optimize, control, and secure systems such as power distribution and smart grids. After implementation, I test them on real-time hardware, simi- lar to what I did during my Ph.D using actual Smart IoT devices. These methods are valuable for establishing secure learning-based communications and creating resilient distributed systems, addressing power grid control problems, and cybersecurity challenges. In summary, these approaches and the verification methods mentioned above help guarantee reliable communication, data privacy, security, efficient energy distribution, governance, resiliency, robustness, and automation for Autonomous Robotic Systems, Internet of Things, embedded systems security, hardware security, Multi-Robot Systems, Autonomous Unmanned Systems, Human-Robot Interaction, power grid control problems, and cybersecurity applications. I am confident that my research experience would be a good fit for the Institute. My expertise and experience in research activities in the area of Cyber-Security, Advanced Scientific Computing, IoT, Networked Embedded Systems and Blockchain, publishing research papers as a lead researcher, Conducting Lectures and guiding students in Ethiopia and India, mentoring graduate students at IIT-Delhi, reviewing research papers for IIT-Delhi and the American Journal of Computer Science and Technology, and interacting with various researchers and stakeholders, along with my inherent ability to identify problems and gaps in existing technology and collaborate with stakeholders and leaders to address them, would be a valuable addition to any research team. Finally, I am capable of working in any environment that employs the following and more: C, C++, Java, C#, MATLAB, Python, Perl, HTML, Bash, Rust, UNIX/Linux, NS3, OMNeT++, MySQL, shell scripting, socket programming, OpenDSS, PyTorch, and pandas. Sincerely yours, Samuel Wedaj Kibret (Ph.D.)