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At least 55 records · Page 3

Holographic pseudoentanglement and the complexity of the AdS/CFT dictionary

The `quantum gravity in the lab' paradigm suggests that quantum computers might shed light on quantum gravity by simulating the CFT side of the AdS/CFT correspondence and mapping the results to the AdS side. This relies on the assumption that the duality map (the `dictionary') is efficient to compute. In this work, we show that the complexity of the AdS/CFT dictionary is surprisingly subtle: there might be cases in which one can efficiently apply operators to the CFT state (a task we call 'operator reconstruction') without being able to extract basic properties of the dual bulk state such as its geometry (which we call 'geometry reconstruction'). Geometry reconstruction corresponds to the setting where we want to extract properties of a completely unknown bulk dual from a simulated CFT boundary state. We demonstrate that geometry reconstruction may be generically hard due to the connection between geometry and entanglement in holography. In particular we construct ensembles of states whose entanglement approximately obey the Ryu-Takayanagi formula for arbitrary geometries, but which are nevertheless computationally indistinguishable. This suggests that even for states with the special entanglement structure of holographic CFT states, geometry reconstruction might be hard. This result should be compared with existing evidence that operator reconstruction is generically easy in AdS/CFT. A useful analogy for the difference between these two tasks is quantum fully homomorphic encryption (FHE): this encrypts quantum states in such a way that no efficient adversary can learn properties of the state, but operators can be applied efficiently to the encrypted state. We show that quantum FHE can separate the complexity of geometry reconstruction vs operator reconstruction, which raises the question whether FHE could be a useful lens through which to view AdS/CFT.

FOS: Physical sciences↗

Roadmap and Benchmarking: Privacy in Federated Load Forecasting

Data-driven techniques for energy demand forecasting continue to emerge with promising impacts on distribution grid planning. However, the development of robust and generalizable machine learning models requires that representative high quality training data are available. Distributed energy resources have begun to embed intelligence, gathering large amounts of data on customer demand, behavior, and household devices that are connected to the grid. Though utilities aggregate meter-level demand data for load shaping, demand response, outage management, reliability planning, and billing applications, there lies an inherent privacy concern in sharing consumption data that may identify individual consumer behavioral patterns. Hence, while sharing the data is crucial, the private sensitive customer data must be safeguarded from being exposed or manipulated. In this study, we propose a roadmap for implementing a based privacy preserving framework to support the advancement of data-driven analytics in data-sensitive distributed energy resources environments. The roadmap incorporates federated learning–a distributed training framework, differential privacy–a statistical framework that provides guarantees to safeguard the leakage of sensitive data, secure multiparty computation and homomorphic encryption– techniques for encrypting model gradients and applying secure aggregation on the server. Moreover, we perform baseline experiments on the federated short-term load forecasting (STLF) task using open-source residential load profile datasets, offering insights into the challenges of integrating differential privacy into federated learning.

Abebe, Waqwoya [Oak Ridge National Laboratory (ORN↗

Embedding security into ferroelectric FET array via in situ memory operation

Non-volatile memories (NVMs) have the potential to reshape next-generation memory systems because of their promising properties of near-zero leakage power consumption, high density and non-volatility. However, NVMs also face critical security threats that exploit the non-volatile property. Compared to volatile memory, the capability of retaining data even after power down makes NVM more vulnerable. Existing solutions to address the security issues of NVMs are mainly based on Advanced Encryption Standard (AES), which incurs significant performance and power overhead. In this paper, we propose a lightweight memory encryption/decryption scheme by exploiting in-situ memory operations with negligible overhead. To validate the feasibility of the encryption/decryption scheme, device-level and array-level experiments are performed using ferroelectric field effect transistor (FeFET) as an example NVM without loss of generality. Besides, a comprehensive evaluation is performed on a 128 × 128 FeFET AND-type memory array in terms of area, latency, power and throughput. Compared with the AES-based scheme, our scheme shows ~22.6×/~14.1× increase in encryption/decryption throughput with negligible power penalty. Furthermore, we evaluate the performance of our scheme over the AES-based scheme when deploying different neural network workloads. Our scheme yields significant latency reduction by 90% on average for encryption and decryption processes.

47 OTHER INSTRUMENTATION↗

Sensitive dependence on initial conditions in a formation of magnetic vortices

The magnetic vortex exhibits promise as a true random number generator for hardware-based encryption and probabilistic computing due to its stochastic formation of energetically equivalent fourfold degenerate states, characterized by two topologies: polarity and chirality. However, a comprehensive understanding of the stochastic formation of magnetic vortices remains elusive. In this work, we show that the magnetization relaxation in asymmetric Permalloy disks evolves along a pitchfork bifurcation, with both bifurcation paths leading to the formation of magnetic vortices with the same chirality. In the bifurcation, one formation path is always chosen under weak in-plane magnetic fields, ultimately determining the final magnetic vortex state. By delaying the in-plane magnetic field, we quantitatively investigate when the final vortex state is determined and find that it is closely associated with the initial conditions rather than the bifurcation point itself. Our findings provide valuable insights into future spintronic-based encryption and probabilistic computing.

Jeong, Suyeong↗

Regression Analysis with the Directed Infusion of Data

Integrating artificial intelligence and machine learning tools into industry necessitates large-scale collaborative efforts that ensure the robust and accurate execution of downstream analytics such as time series prediction, uncertainty quantification, grid optimization, and condition monitoring. However, concerns related to data privacy pervade the nuclear industry due to the proprietary nature of its data and the possibility of data leakage. Legacy techniques such as encryption often require the explicit transmission of data to trustworthy parties, thereby inviting data leakage concerns. The ideal collaboration scenario avoids the explicit dissemination of data/code while maintaining experimental fidelity, which is currently accomplished using various techniques such as trusted execution environments, homomorphic encryption, differential privacy, and multimatrix masking. These techniques, however, often necessitate a trade-off between trust, efficiency, and utility. This article extends a previously proposed technique called the directed infusion of data (DIOD) that ensures data privacy, allows for scalable obfuscation, and combats the risk of data leakage without compromising utility. The experiments discussed in this article examine a regression-type scenario using DIOD with the goal of preserving the inferential link between two variables. Using the point-kinetics equations, regression experiments compare the performance of a model trained using the original data to that of a model trained using the obfuscated data, which produced identical results. Our claim is further strengthened by an information theoretic proof and experiment, which showed that the inferential content between variables remains the same after obfuscation, thereby avoiding the required communication of the proprietary data.

47 - OTHER INSTRUMENTATION↗

Disruption of Commercial Solar Inverter System by TLS Proxy Man-in-the-Middle Attack

Transport Layer Security (TLS) is a cryptographic protocol that encrypts communication data, providing end-to-end communication encryption and authentication. Currently, TLS is widely adopted for securing communication between servers and end devices, including solar inverter systems. Therefore, users/operators can securely access the solar inverters through a web user interface (WebUI) application programmable interface (API) on a PC or server over TLS-enabled Wi-Fi or Ethernet. However, the security of the TLS-based network becomes compromised if it is breached by a TLS proxy man-in-the-middle (MITM) exploit. This report explores potential vulnerabilities in a commercial solar inverter system that leverages a TLS proxy MITM and discusses the impacts through assume-breached penetration testing. Furthermore, the paper explores recommended mitigation methods against the TLS proxy MITM exploit in solar inverters.

97 MATHEMATICS AND COMPUTING↗

To image, or not to image: class-specific diffractive cameras with all-optical erasure of undesired objects

Abstract Privacy protection is a growing concern in the digital era, with machine vision techniques widely used throughout public and private settings. Existing methods address this growing problem by, e.g., encrypting camera images or obscuring/blurring the imaged information through digital algorithms. Here, we demonstrate a camera design that performs class-specific imaging of target objects with instantaneous all-optical erasure of other classes of objects. This diffractive camera consists of transmissive surfaces structured using deep learning to perform selective imaging of target classes of objects positioned at its input field-of-view. After their fabrication, the thin diffractive layers collectively perform optical mode filtering to accurately form images of the objects that belong to a target data class or group of classes, while instantaneously erasing objects of the other data classes at the output field-of-view. Using the same framework, we also demonstrate the design of class-specific permutation and class-specific linear transformation cameras, where the objects of a target data class are pixel-wise permuted or linearly transformed following an arbitrarily selected transformation matrix for all-optical class-specific encryption, while the other classes of objects are irreversibly erased from the output image. The success of class-specific diffractive cameras was experimentally demonstrated using terahertz (THz) waves and 3D-printed diffractive layers that selectively imaged only one class of the MNIST handwritten digit dataset, all-optically erasing the other handwritten digits. This diffractive camera design can be scaled to different parts of the electromagnetic spectrum, including, e.g., the visible and infrared wavelengths, to provide transformative opportunities for privacy-preserving digital cameras and task-specific data-efficient imaging.

47 OTHER INSTRUMENTATION↗

November 2021 Operational Highlights

Completed: 1. the initial tests of document workflows for Titan on the Red, which included standing up a software encryption capability to test data ingestion; 2. a software encryption capability in order to ingest the first data source by the end of the month; 3. a stand-alone computer for classified ontology data entry. Titan on the Red is an artificial intelligence/machine learning system to make digitizing, cataloging, and searching NSRC collections easier and more efficient. Created Online Vault backups, with one copy stored at LANL and one shipped to Lawrence Livermore National Laboratory. The Online Vault is a classified, searchable library of LANL’s nuclear weapons design and test history. Imported new Laboratory Directed Research and Development (LDRD) documents based on revised access categories. Bulk ingested nearly 10,000 documents via java-based PowerLoader. This application ingests metadata and content into the Online Vault to meet the requirements for the NSRC collections. Rehoused 300 linear feet of weapons physics documents in archival, acid-free storage folders and boxes.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Additively Manufactured Tamper Evident Container

Los Alamos National Laboratory has developed a revolutionary and reliable new tamper evident container (TEC) to monitor and protect the health, security, and distribution of high-value assets, technological advancements, products, materials and more that are critical to the operations of businesses and government organizations. Unlike traditional tamper evident seals, the entire TEC serves as a seal, with encrypted on-board electronics able to continuously monitor and log structural health data including but not limited to force, temperature, pressure, humidity, orientation, radiation, acceleration, or vibration as needed. Analog and encrypted digital boards safely stored inside the TEC permanently record the complete integrity history of the protected items and have the ability to alert the TEC owners or take immediate defensive actions should a disruptive or tamper event take place.

36 MATERIALS SCIENCE↗

Security Enhancements for Distributed Energy Resource Systems Interconnected with Distribution Networks: Final Technical Report

The revised IEEE 1547 Standard defines new complex communication-adjustable voltage and frequency regulation and ride-through characteristics, while maintaining the general antiislanding requirement for unintentional islanding situations. Unintentional islanding is prohibited while intentional islanding is specifically allowed, thus effectively enabling microgrid operation mode. Further, IEEE 1547-2018 Standard introduces new requirements in terms of interoperability so that the DER plant/circuit segments may be seamlessly integrated with the utility networks but at the same time become vulnerable to a cyber-attack. Traditional cybersecurity measures including encryption, authentication and role-based access control may not be fully implementable to all communication protocols specified in the IEEE 1547 Standard. Therefore, in this project we have identified, researched, implemented and tested several cyberphysical approaches that rely mostly on the behavior of the DER circuit and may help with validating the incoming command and control action potentially coming through an insecure communications channel. Additionally, we have built semantic models and communications profiles for DER facilities and have implemented lightweight IEC 61850 based publisher-subscriber GOOSE messaging mechanism, with security extensions in terms of authentication and encryption. The project proposed information models for integration into UCA OpenFMB 2.0 profiles focusing on grid code compliance.

24 POWER TRANSMISSION AND DISTRIBUTION↗

The Integration of The Cloudflare WAF

HTTP Strict Transport Security (HSTS) is a standard that ensures website visitor’s traffic is always sent using HTTPS ensuring that all traffic is protected during transit. This initiative was adopted in 2012 by the IETF and has grown in popularity all around the world. Because the traffic is encrypted with TLS/SSL, it can be used by attackers to bypass various cybersecurity capabilities such as a site firewall. To address this lack of visibility into encrypted traffic in motion, the CST at Fermilab acquired the Cloudflare Web Application Firewall (WAF). To help in the implementation and integration of the Cloudflare WAF, I was directed to learn about and aid in this process. This has been a profound learning experience into the on-goings of project management, web application firewalls, collaboration, and networking.

Blum, Ethan T.↗

Precursor Analysis Report: Conti Ransomware Attack on the Health Service Executive of Ireland 2021

The Conti Ransomware Attack on the Health Service Executive (HSE) of Ireland 2021 Precursor Analysis Report leverages publicly available information about the attack and catalogs anomalous observables for each technique employed by the adversary. This analysis is based upon the methodology of the Cybersecurity for the Operational Technology Environment (CyOTE) program. The HSE provides public healthcare corporate services and operational services throughout Ireland, with critical functions including the acute national ambulance service, acute hospital service, and community healthcare service. On 14 May 2021, Conti ransomware encrypted 80 percent of the HSE’s Information Technology (IT) infrastructure across corporate, hospital, community, and electronic health record services. Conti is a ransomware-as-a-service operation that encrypts local files, uses double extortion against victims, and is facilitated by many intrusion tools. The attack forced the HSE to shut down its entire IT infrastructure to contain the ransomware, forcing employees to revert to pen and paper recordkeeping and leading to the cancellation of many appointments and procedures. The adversary also exfiltrated 700 GB of data, compromising the confidentiality of patients’ protected health information. Had the adversary targeted the COVID-19 cloud systems or operational technology assets, such as Internet of Medical Things medical devices or smart building management systems, the impact of the attack would almost certainly have been far more severe. Researchers and analysts identified 21 unique techniques (used in a sequence of 23 steps) likely utilized during the attack with a total of 1,185 observables using MITRE ATT&CK® for Industrial Control Systems. The CyOTE program assesses observables accompanying techniques used prior to the triggering event to identify opportunities to detect malicious activity. If observables accompanying the attack techniques are perceived and investigated prior to the triggering event, earlier comprehension of malicious activity can take place. Twenty-one of the identified techniques used during the attack on the HSE were precursors to the triggering event. Analysis identified 1,086 observables associated with these precursor techniques, 850 of which were assessed to have an increased likelihood of being perceived in the 57 days preceding the triggering event. The response and comprehension time could have been reduced if the observables had been identified earlier. The information gathered in this report contributes to a library of observables tied to a repository of artifacts, data sources, and technique detection references for practitioners and developers to support the comprehension of indicators of attack. Asset owners and operators can use these products if they experience similar observables or to prepare for comparable scenarios.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Privacy-Preserving Transactive Energy System

In this paper, the privacy issue of recently proposed transactive energy systems for electric power systems is studied for the first time. It is identified that the private information of individual market participants is subject to the risk of leakage during their market-based interaction. In order to protect their privacy, a homomorphic encryption-based approach is developed to achieve the privacy preservation with the Paillier encryption scheme. The proposed privacy-perserving design is then demonstrated on a transactive energy system that coordinates and controls residential air conditioners to manage the feeder congestion. The simulation results confirm the effectiveness of the proposed design in protecting the privacy of individual market participants without affecting the overall system performance. Future work on the proposed design is also suggested.

Lu, Yang↗

Accessing protected data by a high-performance computing cluster

A data protection system is provided that allows applications to access protected data in a way that restricts applications from outputting to unauthorized targets any unprotected data derived from the protected data and that ensures that the applications do not have access to a key that allows access to the unprotected data. The data protection system provides a policy server that may execute on a service node of a high performance computing system and a data encryption process that may execute on each compute node that is allocated to an application or batch job. The policy server maintains policies of entities specifying access control for protected data. The data encryption process generates a secure execution environment for an application process and interfaces with the policy server to retrieve keys for decrypting protected data in accordance with a policy, and it decrypts and provides the decrypted data to the application process.

Barnes, Peter↗

Exploring Applied Cryptosystems to Formally Verify Security in Cyber-Physical Systems

This project aims to evaluate RSA as a method for public-key encryption for cyber-physical systems (CPS). As technology advances, cyber attacks are increasing, and with them, the need for cybersecurity advances; the average cost for cybercrime in the world was estimated at $6 trillion in 2021. A public-key cryptosystem that has been around since 1977, RSA has recently garnered some critiques for its fragility, computational cost, and lazy implementation. In this project I will review the mathematical derivation of RSA, analyze the practical implications of such mathematical framework for the security of RSA, and propose a formal methods based approach to verify encryption schemes for CPS.

97 MATHEMATICS AND COMPUTING↗

CMOS-Based Single-Cycle in-Memory XOR/XNOR

Big data applications are on the rise, and so is the number of data centers. The ever-increasing massive data pool needs to be periodically backed up in a secure environment. Moreover, a massive amount of securely backed-up data is required for training binary convolutional neural networks for image classification. XOR and XNOR operations are essential for large-scale data copy verification, encryption, and classification algorithms. The disproportionate speed of existing compute and memory units makes the von Neumann architecture inefficient to perform these Boolean operations. Compute-in-memory (CiM) has proved to be an optimum approach for such bulk computations. The existing CiM-based XOR/XNOR techniques either require multiple cycles for computing or add to the complexity of the fabrication process. Here, we propose a CMOS-based hardware topology for single-cycle in-memory XOR/XNOR operations. Our design provides at least 2× improvement in the latency compared with other existing CMOS-compatible solutions. We verify the proposed system through circuit/system-level simulations and evaluate its robustness using a 5000-point Monte Carlo variation analysis. This all-CMOS design paves the way for practical implementation of CiM XOR/XNOR at scaled technology nodes.

97 MATHEMATICS AND COMPUTING↗

Stimuli‐Responsive Emission from Hybrid Metal Halides

Abstract Stimuli‐responsive photoluminescent (PL) materials have attracted considerable attention in recent years owing to their potential applications in anti‐counterfeiting, information encryption, and sensing. Further investigations of the transformation mechanism and potential applications of stimulus‐responsive PL materials are considerably important. In the current study, an organic–inorganic metal halide, C 9 H 15 N 3 SbCl 5 ([C 9 H 13 N 3 ] 2+ is a 1‐(2‐pyridyl) piperazine cation) is obtained, which exhibits a 0D structure withP‐1 space group. At room temperature, when excited by UV light, the C 9 H 15 N 3 SbCl 5 single crystals exhibit unimodal blue light emission at 405 nm, and grinding or hydrostatic pressure induces double‐peak emissions at 405 and 650 nm. Interestingly, double‐emission samples can be restored to single‐emission samples by short annealing or storage in air for 2 weeks, and this process is reversible. Luminescence response to mechanical stimuli can also be achieved in the presence of hydrochloric acid and water. Spectral analysis and the analysis of the microstructural changes revealed that the structural modifications of the inorganic group play a pivotal role in the response to the stimulus. Finally, a composite film device based on C 9 H 15 N 3 SbCl 5 is prepared to demonstrate the potential of these smart materials in anti‐counterfeiting and sensing applications.

Chemistry↗

Multicolor Photonic Pigments for Rotation-Asymmetric Mechanochromic Devices

Photonic crystals are extensively explored to replace inorganic pigments and organic dyes as coloring elements in printing, painting, sensing, and anti-counterfeiting due to their brilliant structural colors, chemical stability, and environmental friendliness. However, most existing photonic-crystal-based pigments can only display monochromatic colors once made, and generating multicolors has to start with designing different building blocks. In this work, a novel photonic pigment featuring highly tunable structural colors in the entire visible spectrum, made by the magnetic assembly of monodisperse nanorods into body-centered-tetragonal photonic crystals, is reported. Their prominent magnetic and crystal anisotropy makes it efficient to generate multicolors using one photonic pigment by magnetically controlling the crystal orientation. Further, the combination of angle-dependent diffraction and magnetic orientation control enables the design of rotation-asymmetric photonic films that display distinct patterns and encrypted information in response to rotation. The efficient multicolor generation through precise orientational control makes this novel photonic pigment promising in developing high-performance structural-colored materials and optical devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗