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Cyber Security Summer School [Slides]
The goal of the Cyber Toaster: Research Track is to address emerging national cyber threats.
Cyber Labeling for Energy Industrial IoT
The U.S. Department of Energy’s (DOE) Office of Cybersecurity, Energy Security and Emergency Response (CESER), at the request of the Deputy National Security Advisor for Cyber and Emerging Technologies, Anne Neuberger, initiated research in 2023 to develop a cybersecurity labeling proof-of-concept for energy products to expand on the Federal Communications Commission’s (FCC) proposed U.S. Cyber Trust Mark program. DOE mobilized researchers from six National Laboratories to develop and gather feedback on a proof-of concept label for solar inverters and smart meters, which serve as representative products for market-facing energy sector Industrial Internet of Things (IIoT). This report details the research team’s process across two phases and the resulting findings, which include challenges facing cyber labeling programs and recommendations to implement an expanded IIoT cyber labeling program in the U.S.
The Chemical Management System (CMS): A Useful Tool for Inventory Management
Comprehensive inventory management is central to the efficient operation of any facility that uses and stores chemicals. There are numerous software packages available that perform this function satisfactorily. Most commercially available inventory management software is regulatory or procurement focused and usually comes with upfront or monthly fees. Finally, this report describes freely downloadable software developed at Sandia National Laboratories that delivers an effective inventory management system with an additional focus on chemical security.
Development of a Cavity Collapse Model of Cavitation Bubbles in Water in One and Two Dimensions using the Finite Volume FLAG Hydrocode at Atmospheric Pressure and 293K (Final Report)
Los Alamos National Laboratory was established in 1943 as the home of Project Y, The Manhattan Project directed by J. Robert Oppenheimer, with the aim of developing the world’s first atomic bomb. The project was successful and on the 16 th of July 1945 the first atomic bomb was detonated at Trinity Site. This development led to the creation of Little Boy and Fat Man, the two nuclear bombs dropped in Japan to end World War II. Today the laboratory has the responsibility of ensuring that the American nuclear deterrent is safe, secure and reliable. To ensure that this important responsibility is met, the laboratory carries out science in a wide range of areas. Its responsibilities are shared with Sandia National Laboratory (SNL) and Lawrence Livermore National Laboratory (LLNL). All are laboratories managed by the Department of Energy’s National Nuclear Security Administration (NNSA).
Centralized Authorization in Non-Uniform Federation: Communities of Interest [Slides]
Scientific process is based on free exchange of ideas. Scientific collaborations require us to be more open than ever, while emphasis on cyber security puts pressure to become more closed off. The role of IT is to enable exchange of ideas and data balanced with security concerns. Exchange of information happens and is necessary in many other areas of Laboratory operations.
Alliance Project: Secure Control Systems for the Energy Sector
The Alliance Project addresses Area of Interest 4: Secure Remote Access for the Energy Sector, by combining physical and cyber access under one cybersecurity access system. The Alliance Project built on the successful completion of the Lemnos and Padlock Project (DOE-Funded Project started in 2007 and 2010) and researched and developed a solution for an Ethernet Security Gateway with the functionality required to integrate the physical access control cyber system and interface with legacy and new proximity card readers used for physical access requests. This project focused on securing and enhancing the cyber system the physical access control system operates on. The team tested and demonstrated the system solution on the SEL campus. Currently the physical access cyber system is completely separate from the cyber access control cyber system. With a single system industry benefits include: (1) Single system to learn and teach employees; (2) Single system that collects and alerts on logs and events simplifying incident response plans and NERC CIP compliance; (3) Unifies trust management to a single system reducing the potential errors in privilege escalation or revocation; (4) Provides a stronger cybersecurity platform the physical access control system operates on. Today they are mostly plain text protocols and little cyber awareness; (5) Integration of physical access awareness allows the cyber system to react and adjust. In some cases, the cyber access can be enhanced with authorized physical access and other cases the cyber access can be more restricted with unauthorized physical access; and (6) Enables the utility to establish as large or as small a physical access control system as they require. One example would be when a utility shares a substation with a neighbor utility and can’t rely on the substation door for the physical access control. The Alliance technology enables them to lock equipment racks simply with no scalability issues because it stands on the cyber security infrastructure which is already highly scalable.
Blockchain based Communication Architectures with Applications to Private Security Networks
Existing communication protocols in high consequence security networks are highly centralized. While this naively makes the controls easier to physically secure, external actors require fewer resources to disrupt the system because there are fewer points in the system can be destroyed or interrupted without the entire system failing. We present a solution to this problem using a proof-of-work-based blockchain implementation built on MultiChain. We construct a test-bed network containing two types of data input: visual imagers and microwave sensor information. These data types are ubiquitous in perimeter intrusion detection security systems and allow a realistic representation of a real-world network architecture. The cameras in this system use an object detection algorithm to nd important targets in the scene. The raw data from the camera and the outputs from the detection algorithm are then placed in a transaction on the distributed ledger. Similarly, microwave data is used to detect relevant events and are placed in a transaction. These transactions are then bundled into blocks and broadcast to the rest of the network using the Bitcoin-based MultiChain protocol. We develop five tests to examine the security metrics of our network. We performed the five security metric test using different sized networks from 7 to 39 nodes to determine how the metrics scale with respect to size. We nd that when compared to a centralized architecture our implementation provides a resiliency increase that is expected from a blockchain-based protocol without slowing the system so much that a human operator would notice. Furthermore, our approach is able to detect tampering in real time. Based on these results, we theorize that security networks in general could use a blockchain-based approach in a meaningful way.
Operational and Mission Highlights. A Monthly Summary of Top Achievements, February 2021
The newsletter highlights achievements in the following areas: Nuclear Security; Science, Technology and Engineering; Mission operations; and Community Relations.
IER 500: AWE-LLNL Measurement Campaign at DAF [Slides]
Presentation Hosted at Device Assembly Facility (DAF). Joint collaboration by Atomic Weapons Establishment (AWE) and Lawrence Livermore National Laboratory (LLNL). Multiple measurements were recorded through a two-week period with 12 unique objects measured. LLNL deployed Machine learning software program for diagnostic assessments. Current status notes the dedicated DAF team LLNL maintains. Additionally, LLNL is compiling a report on the AWE-LLNL measurements and designing security benchmark experiments. The presentation concludes with future work envisioned.
Secure Data Logging and Processing with Blockchain and Machine Learning (Final Report)
Secure Data Logging and Processing with Blockchain and Machine Learning (ML) research is focused on the development of a platform to securely log and process sensor data in fossil power plants. The platform integrates two emerging technologies, blockchain and ML, and incorporates several innovative mechanisms to ensure the integrity, reliability, and resiliency of power systems. The goal is to protect the power plant from various cyberattacks such as false data injection and denial of service attacks using these technologies. The research goal was enabled by the following Research Project Objectives: 1) Secure authentication and identity verification of sensor nodes, actuators, and other equipment within a network. 2) Development of mechanisms that ensure only data sent by legitimate sensors are accepted and stored in the data repository. 3) Development of data aggregation methodologies using ML / Deep Learning (DL) algorithms to minimize noise / faulty data. 4) Implementation of the blockchain technologies to provide data security using secured IOTA framework & nodes.
Combustion-Pele: An Exascale Capability for Improving Engine Design
Combustion, the complex chemical reaction made possible by igniting a mixture of fuel and oxygen to produce heat and light, serves as the nation’s primary source of power generation and the linchpin of the transportation industry. For more than 100 years, internal combustion engines (ICEs) have been converting energy from the burning of fuel—gasoline, for example—into a mechanical process that makes vehicles move. Recently, ICEs have come under heavy scrutiny for their contribution to greenhouse gas emissions, yet combustion-based systems are projected to dominate the marketplace for decades. Exascale systems are helping researchers design new high-efficiency, low-emission combustion engines that operate at much lower temperatures to maintain the nation’s energy security and limit negative environmental impacts.
Secure Monitoring and Control of Solar Power Distribution System through Dynamic Watermarking
This report summarizes the activities of this project, which aims at design and testing a scalable, robust, and online framework that provides secure monitoring of photovoltaic generation in the face of potential cyber-attacks.
Quantum Technologies for UAS (QTech)
Recent advances in small Unmanned Aerial System (sUAS) technologies lower the barriers for use by both private and commercial entities. However, these advances are also likely to lead to greater vehicle densities, a more heterogenous mix of vehicles and equipment and greater levels of vehicle autonomy, which can increase the chance for communications disruptions. For the safe and secure operation of these vehicles, it is essential to have a robust communications network. This work is focused on harnessing the power of quantum technologies to enable this robust communications network by: (1) utilizing quantum optimization algorithms to design robust network with routing redundancy that can respond adaptively to dynamically changing real-time environment and disruptions, (2) utilize quantum optimization algorithms resource allocation for detection, localization, and tracking of mobile communication disruption agents and (3) utilize quantum key distribution (QKD) to execute secure key sharing in anti-jamming protocols for secure radio frequency (RF) communication. Efforts to map these quantum optimization algorithms to commercially available quantum annealers and soon to be available general-purpose gate-model quantum hardware architectures will be reviewed, and plans for testing the solutions to these algorithms through indoor sUAS flight tests will be discussed. Lastly, efforts to miniaturize and practically deploy Quantum Key Distribution (QKD) hardware, which could ultimately be used to securely exchange encryption keys, in sUAS networks will be reviewed.
Implementing efficient data compression and encryption in a persistent key-value store for HPC
Recently, persistent data structures, like key-value stores (KVSs), which are stored in a high-performance computing (HPC) system’s nonvolatile memory, provide an attractive solution for a number of emerging challenges like limited I/O performance. Data compression and encryption are two well-known techniques for improving several properties of such data-oriented systems. This article investigates how to efficiently integrate data compression and encryption into persistent KVSs for HPC with the ultimate goal of hiding their costs and complexity in terms of performance and ease of use. Our compression technique exploits deep memory hierarchy in an HPC system to achieve both storage reduction and performance improvement. Our encryption technique provides a practical level of security and enables sharing of sensitive data securely in complex scientific workflows with nearly imperceptible cost. We implement the proposed techniques on top of a distributed embedded KVS to evaluate the benefits and costs of incorporating these capabilities along different points in the dataflow path, illustrating differences in effective bandwidth, latency, and additional computational expense on Swiss National Supercomputing Centre’s Grand Tavé and National Energy Research Scientific Computing Center’s Cori.
Privacy-Preserving Knowledge Transfer with Bootstrap Aggregation of Teacher Ensembles
There is a need to transfer knowledge among institutions and organizations to save effort in annotation and labeling or in enhancing task performance. However, knowledge transfer is difficult because of restrictions that are in place to ensure data security and privacy. Institutions are not allowed to exchange data or perform any activity that may expose personal information. With the leverage of a differential privacy algorithm in a high-performance computing environment, we propose a new training protocol, Bootstrap Aggregation of Teacher Ensembles (BATE), which is applicable to various types of machine learning models. The BATE algorithm is based on and provides enhancements to the PATE algorithm, maintaining competitive task performance scores on complex datasets with underrepresented class labels.We conducted a proof-of-the-concept study of the information extraction from cancer pathology report data from four cancer registries and performed comparisons between four scenarios: no collaboration, no privacy-preserving collaboration, the PATE algorithm, and the proposed BATE algorithm. The results showed that the BATE algorithm maintained competitive macro-averaged F1 scores, demonstrating that the suggested algorithm is an effective yet privacy-preserving method for machine learning and deep learning solutions.
Compact FEL-driven inverse compton scattering gamma-ray source
Many research and applications areas require photon sources capable of producing gamma-ray beams in the multi-MeV energy range with reasonably high fluxes and compact footprints. Besides industrial, nuclear physics and security applications, a considerable interest comes from the possibility to assess the state of conservation of cultural assets like statues, columns etc., via visualization and analysis techniques using high energy photon beams. Computed Tomography scans, widely adopted in medicine at lower photon energies, presently provide high quality three-dimensional imaging in industry and museums. We explore the feasibility of a compact source of quasi-monochromatic, multi-MeV gamma-rays based on Inverse Compton Scattering (ICS) from a high intensity ultra-violet (UV) beam generated in a free-electron laser by the electron beam itself. This scheme introduces a stronger relationship between the energy of the scattered photons and that of the electron beam, resulting in a device much more compact than a classic ICS for a given scattered energy. As a result, the same electron beam is used to produce gamma-rays in the 10–20 MeV range and UV radiation in the 10–15 eV range, in a ~4 × 22 m 2 footprint system.
Extra-light gamma-ray imager for safeguards and homeland security
Gamma-ray imaging is the most important way to identify unknown gamma-ray emitting objects in decommissioning, security, overcoming accidents. Over the past two decades a system for producing of gamma images in these conditions became more or less portable devices. But in recent years these systems have become the hand-held devices. This is very important, especially in emergency situations, and measurements for safety reasons. We describe the first integrated hand-held instrument for emergency and security applications. The device is based on the coded aperture image formation, position sensitive gamma-ray (X-ray) detector Medipix2 (detectors produces by X-ray Imaging Europe) and tablet computer. The development was aimed at creating a very low weight system with high angular resolution. We present some sample gamma-ray images by camera. Main estimated parameters of the system are the following. The field of view video channel ∼ 490 deg. The field of view gamma channel ∼ 300 deg. The sensitivity of the system with a hexagonal mask for the source of Cs-137 (Eg = 662 keV), is in units of dose D ∼ 100 mR. This option is less then order of magnitude worse than for the heavy, non-hand-held systems (e.g., gamma-camera Cartogam, by Canberra.) The angular resolution of the gamma channel for the sources of Cs-137 (Eg = 662 keV) is about 1.20 deg. (authors)