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At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
NASA NTRS2002

Neurovestibular Effects of Long-Duration Spaceflight: A Summary of Mir-Phase 1 Experiences

Space motion sickness and associated neurovestibular dysfunction though not completely understood - have been relatively well clinically and operationally characterized on short-duration (1-2 week) Space Shuttle missions (Oman, et al, 1984, 1986; Thornton, et al, 1987; Reschke, et al, 1994). Between March 1995 and June 1998, seven NASA astronauts flew on the Russian Mir space station, as "Phase 1" of the joint effort to build the International Space Station, and provided NASA with invaluable experience on the operational and biomedical problems associated with flights of up to six months in duration. The goal of this paper is to provide a summary of the available information on neurovestibular dysfunction, space motion sickness, and readaptation to Earth's gravity on the NASA Mir flights, based on a set of medical questionnaire data, transcripts, and interviews which are available from the NASA-Mir Phase I program. Records were incomplete and anecdotal. All references to specific crewmembers have been removed, to respect their individual privacy. Material was excerpted from multiple sources of information relating to neurologic function, sensory illusions and motion sickness of NASA-Mir Phase I Program crewmembers. Data were compiled by epoch (in-flight vs landing/postflight) and grouped by neurovestibular topic. The information was recorded either contemporaneously during or within days after landing, or retrospectively weeks to months later. Space motion sickness symptoms are more intense and longer in duration. Sense of spatial orientation takes at least a month to become "natural and instinctive" in space station structures, but mental survey knowledge is apparently not completely developed even after 3 months in some cases. Visual reorientation illusions (VRI) are more easily induced after long exposure to weightlessness. Head movements can cause illusory spinning sensations for up to 7 days postflight. Postural and balance control does not fully recover for at least a month postflight.

Richards, Jason T.↗
DOE OSTI2025

Exploring the Utility-Privacy Trade-Off: Impacts of Semantic and Visit Types Ambiguities on Human Mobility Simulation

Humans are in perpetual movement, constantly traversing buildings, cities, waters, oceans, and countries. Mobility stands out as a major driving force shaping our modern societies. Capturing and explaining human behavior in a world of eight billion distinct mobility agendas is a complex challenge. With the rise of interconnected devices and platforms, such as smartphones, wearables, and point-of-interest data, largescale behavioral data has become more accessible, enabling rich insights into mobility patterns. However, the widespread availability of such data introduces significant ethical challenges. Detailed mobility data can inadvertently reveal sensitive personal information, including individuals' locations, habits, social interactions, and even political or religious affiliations. Beyond privacy breaches, the ethical implications of uncovering and potentially manipulating underlying behavioral patterns demand attention. Striking a balance between the utility of mobility models and the protection of individual privacy is therefore paramount. This paper explores the utility-privacy trade-offs in human mobility modeling, focusing on the impacts of introducing semantic and visit type ambiguities. By systematically examining how these ambiguities affect the fidelity of simulated trajectories and privacy risks, we provide a framework for evaluating ethical and privacy-conscious modeling practices. Our findings emphasize the need for methods that safeguard privacy without undermining the usefulness of mobility models, contributing to the responsible advancement of mobility science in alignment with ethical standards and societal expectations.

Amichi, Licia [ORNL] (ORCID:0000000177631394)↗
DOE OSTI2020

EVALUATING NUCLEAR SECURITY IMPLICATIONS OF THE SPLINTERNET

The internet, which for years has been viewed as a global online commons with standardized protocols but few regulations is, according to some experts, starting to mirror the contentious political and commercial contours of the physical world. Contributing to this is the rise in data breaches, cyber-enabled attacks on critical infrastructure, government surveillance operations, theft of intellectual property, manipulation of electoral processes, and perceived erosion of privacy, all of which are resulting in a growing skepticism that an open internet will naturally serve the best interests of users, communities, countries, and the global economy. In addition, the rapidly emerging and increasingly lucrative power of data has global superpowers scrambling to protect their informational sovereignty as an urgent matter of national security. Underscoring this urgency is the fact that, despite its global reach and cosmopolitan contributor base, internet infrastructure and governance of the World Wide Web remain largely under U.S. corporate auspices, which reinforces the perception of U.S. control. Whether fragmentation is politically, economically, or socially motivated, there appears to be a growing appetite for an internet that is partitioned and controlled at the national level. From “the Great Firewall of China” to the “Halal” internet of Iran, the trend towards a “Splinternet” has courts and governments embarking on what some call a "legal arms race" to impose a maze of national or regional rules, often conflicting, in the digital realm. The paper explores the emerging Splinternet phenomenon, analyses the implications of this trend on nuclear security, and identifies questions that present opportunities for future research.

Internet, Data Security, Cyber Security, Nuclear S↗
DOE OSTI2023

Distributed Energy Resource Management Systems: Preserving Customer Privacy through K-Anonymity

The smart grid represents the next generation of electricity distribution systems that utilizes recent technological innovations. It uses digital communication between its components and entities to attain more automation, self-sufficiency, and reliability. One of the many concerns in smart grid digital communication discussions is the possibility of violating customers’ privacy. Violating customers’ privacy imposes a significant barrier as smart grid desirable attributes are tightly tied to customers’ participation. Employing privacy models can address concerns regarding information privacy in smart grid digital communication. In this work, we provide an approach to utilizing K-anonymity to ensure data within the system excludes Personally Identifiable Information. Results suggest that a dynamically generated generalization hierarchy minimizes information loss incurred by the anonymization process.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2015

Space in Space: Designing for Privacy in the Workplace

Privacy is cultural, socially embedded in the spatial, temporal, and material aspects of the lived experience. Definitions of privacy are as varied among scholars as they are among those who fight for their personal rights in the home and the workplace. Privacy in the workplace has become a topic of interest in recent years, as evident in discussions on Big Data as well as the shrinking office spaces in which people work. An article in The New York Times published in February of this year noted that "many companies are looking to cut costs, and one way to do that is by trimming personal space". Increasingly, organizations ranging from tech start-ups to large corporations are downsizing square footage and opting for open-office floorplans hoping to trim the budget and spark creative, productive communication among their employees. The question of how much is too much to trim when it comes to privacy, is one that is being actively addressed by the National Aeronautics and Space Administration (NASA) as they explore habitat designs for future space missions. NASA recognizes privacy as a design-related stressor impacting human health and performance. Given the challenges of sustaining life in an isolated, confined, and extreme environment such as Mars, NASA deems it necessary to determine the acceptable minimal amount for habitable volume for activities requiring at least some level of privacy in order to support optimal crew performance. Ethnographic research was conducted in 2013 to explore perceptions of privacy and privacy needs among astronauts living and working in space as part of a long-distance, long-duration mission. The allocation of space, or habitable volume, becomes an increasingly complex issue in outer space due to the costs associated with maintaining an artificial, confined environment bounded by limitations of mass while located in an extreme environment. Privacy in space, or space in space, provides a unique case study of the complex notions of privacy, the impact of design and others on achieving it, and the sensemaking that occurs when privacy is less than expected. The findings show that privacy is not just a personal, individual need but is also a need that is shared among teams and groups. Moreover, the case of space in space reveals the influence the design of the built and social environments have on privacy needs and on achieving privacy. When the level of privacy is less than expected, sensemaking occurs and the lack of privacy is dealt with by means of absencing the present. creating new social norms, and "making space" by manipulating the spatial, temporal, material aspects of the lived experience. Although the Mars habitat study represents an extreme case of privacy in the workplace, lessons learned from outer space are applicable to life in the Earth-bound workplace. A mini-case study was conducted to evaluate office space at the headquarters of a major American airline that illustrates the usefulness of building unexpected bridges between the unknown, unfamiliar Mars habitat and the everyday workplace. The comparative studies reveal insight into the interconnected, social nature of the spatial, temporal, and material aspects of the lived experience and how users of the habitat and office workspace view privacy, self, and others through an embodied, design interaction.

Akin, Jonie↗
NASA NTRS1979

Considerations associated with the introduction of female crewmembers in spacecraft and space stations

This paper examines considerations of inclusion of female crewmembers in spacecraft and space stations. The anthropometric and physiological differences between males and females as related to spaceflight such as body dimensions, muscle strength characteristics, body posture, reach, and physiological differences are discussed. Crew provisions including inflight garments, hair style, cosmetics, personal hygiene, waste management, and personal privacy are described. Impacts on hardware design and crew performance, examples of effects on Orbiter systems, data on females and their performance under conditions analogous to spaceflight, and earth-based simulation experience are examined. It is concluded that no major problems have been found which would preclude females from space, and in the future the novelty of mixed crews will significantly decrease.

Brown, J. W.↗
DOE OSTI2026

Designing resilient IoT and Edge Computing with federated tinyML

The rapid growth of the Internet of Things (IoT) and Edge Computing (EC) has brought significant conveniences to modern society but has also greatly expanded the cyber attack surfaces, particularly as these technologies are being increasingly integrated into critical systems such as power grids, healthcare, and smart homes. Here, to improve IoT/EC’s cybersecurity posture, we leveraged Artificial Intelligence (AI) and Machine Learning (ML) by employing tinyML to monitor voluminous IoT data for cyber threats while addressing devices’ resource constraints, and utilizing Federated Learning (FL) to share local detection knowledge across the system while preserving privacy. Building on our three-layer architecture combining tinyML and FL to enhance autonomous cyber attack detection, this paper demonstrated that the architecture improves detection accuracy, reduces resource consumption, and enables lightweight, secure IoT device monitoring. These results were validated using the public N-BaIoT dataset as well as real IoT network traffic data collected under multiple attack scenarios from our testbeds. Additionally, we introduced an enhanced FL methodology with a novel preprocessing stage, including federated feature selection and global preprocessor construction, to address IoT/EC data heterogeneity. We developed a physical IoT testbed for attack simulations and data collection, implemented a tinyML-powered detector for realistic model validation, and also built a virtual testbed for scalable evaluations of FL models across diverse network environments.

Cognitive cyber↗
DOE OSTI2025

Pooled Rideshare in the U.S.: An Exploratory Study of User Preferences

Pooled ridesharing offers on-demand, one-way, cost-effective transportation for passengers traveling in similar directions via a shared vehicle ride with others they do not know. Despite its potential benefits, the adoption of pooled rideshare remains low in the United States. This exploratory study aims to evaluate potential service improvements and features that may increase users’ willingness to adopt the service. The study analyzed transportation behaviors, rideshare preferences, and willingness to adopt pooled rideshare services among 8296 U.S. participants in 2025, building on findings from a 2021 nationwide survey of 5385 U.S. participants. The study incorporated 77 actionable items developed from the results of the 2021 survey to assess whether addressing specific user-generated topics such as safety, reliability, convenience, and privacy can improve pooled rideshare use. A side-by-side comparison of the 2021 and 2025 data revealed shifts in transportation behavior, with personal rideshare usage increasing from 22% to 28%, public transportation from 21% to 27%, and pooled rideshare from 6% to 8%, while personal vehicle (79%) use remained dominant. Participants rated features such as driver verification (94%), vehicle information (93%), peak time reliability (93%), and saving time and money (92–93%) as most important for improving rideshare services. A pre-to-post analysis of willingness to use pooled rideshare utilizing the actionable items as per respondents’ preferences showed improvement: “definitely will” increased from 15.9% to 20.1% and “probably will” rose from 35.6% to 47.7%. These results suggest that well-targeted service improvements may meaningfully enhance pooled rideshare acceptance. This study offers practical guidance for Transportation Network Companies (TNCs) and policymakers aiming to improve pooled rideshare as well as potential future research opportunities.

Transportation Network Companies (TNCs)↗
NASA NTRSDate not supplied

Zero-Trust Architecture for Autonomous Edge Computing

We are at the apex of an aviation revolution where autonomy will play a central role in enabling complex, multi-agent systems to communicate, interact, and collaborate on a myriad of applications spanning autonomous swarms to wild-fire management. Autonomy is not an absolute but rather a spectrum ranging from a system requiring significant human intervention to one requiring little to none [1]. For example, the extreme, in the case of an autonomous aircraft, is one that operates independently in the airspace interacting with all other elements (air traffic controllers, other pilots) as if it were a human pilot. Critical to this vision is an architecture that enables autonomous agents to interact with minimal latency. Edge computing is an emerging architecture where compute and storage is pushed to the ‘edge’ of the network in order to minimize the round-trip time from agent to resource thereby mitigating the latency associated with cloud-only based approaches. Additionally, services can generate massive amounts of data (e.g., video feeds), which may require analysis in near real-time. Moving this data to the cloud for further processing may not be feasible due to latency, bandwidth, and cost. Privacy, security, and reliability can also be improved by edge computing architectures. However, this geo-distributed and dynamic* architecture complicates the establishment of unambiguous network security boundaries and can lead to vulnerabilities including man in the middle attacks, replay attacks, physical security breaches of edge nodes, signal interception, etc. This motivates the need for zero-trust architectures [2–4] which de-emphasize the notion of static network perimeters and, as the name implies, do not instill any innate trust in any particular agent. It is required that all agents must be authorized and approved in every transaction. In this paper, we present a zero-trust architecture suitable for edge-computing applications that demand significant low-latency, security, privacy, and reliability.

zero trust↗
DOE OSTI2023

Are System Baselines within OT Environments Feasible?

Critical infrastructure stakeholders need to baseline their systems to understand expected protocol communications.Baseline behaviors may vary based on operational context.Expected operations during a maintenance window, for example, may be different from normal operations.Furthermore, constructing system baselines for Industrial Control Systems (ICS) is difficult and time-consuming.ICS processes generate artifacts expressed across heterogeneous data sources such as network and device logs. There needs to be a corpus of data in order to develop and compare methods that evaluate the feasibility, performance, and generality of approaches to construct baselines for ICS events. Standalone repositories of network packet captures are insufficient to develop methods to classify or recognize operational events expressed across multiple data sources. Moreover, static data corpora do not enable researchers to compare the impact of changing the underlying system for which a baseline is being constructed and this limits the ability to evaluate the performance of system baselines given system changes (e.g. patches, configuration, maintenance events). In order to address these limitations within the community, this talk intends to promote discussion about the state of the practice of constructing baselines. In this manner, we can continue to understand requirements within industry that are not being met by current approaches to baseline construction. This talk builds on two previous talks on the topic of system baselines for OT environments. First, Weaver co-presented at the RSA Conference ICS Sandbox with Dan Gunter. The talk confirmed the need within industry to construct baselines across multiple types of data sources relative to the semantics of specific business processes. Second, Weaver presented at IEEE Security and Privacy Workshop on Language-Theoretic Security.

02 PETROLEUM↗
NASA NTRSDate not supplied

Results for the Subjective Habitability Acceptability Questionnaire From HERA C5 and C6

BACKGROUND The impact of habitability on psychological and performance outcomes is recognized as an important factor in habitat and vehicle design—especially as missions increase in length. Formal evaluation of habitability’s impact is possible using the Spaceflight Habitability Acceptability Questionnaire (SHAQ), which was psychometrically validated by Roma et al. in 2022 [1]. The SHAQ survey systematically quantifies the relationships between habitat areas (e.g., bedroom, kitchen, hygiene area, office, etc.) and behavioral health and performance (BHP) outcomes (i.e., individual and team performance, mood, stress, sleep, social interaction), and considers the moderating effects of key habitability aspects (i.e., privacy, control, convenience, efficiency, comfort, social density) on that relationship. METHOD Respondents were HERA participants from Campaign 5 and 6 (n = 32). Data from three environments were used in our SHAQ analyses: SHAQ in HERA (in-mission), SHAQ at Home (pre-mission), and SHAQ in Hotel (pre- and post-mission for C6, just pre-mission for C5). For each habitat area, respondents are asked how that area layout impacts six BHP outcomes on a 201-point visual analog scale with the anchors: impairs, has no effect, and facilitates. They also had the option to respond “Not Applicable”. Follow up questions asked why six key habitability aspects (e.g., privacy) influenced the way the habitat area affected a given outcome. Participants indicated whether a habitat area’s habitability aspects were inadequate (low score) to adequate (midpoint) to ideal (high score), using a 201-point visual analog scale as well but were binned to a 7-point scale for analyses. RESULTS AND CONCLUSION When comparing across environments, ratings of BHP outcomes were worse in HERA compared to home and pre-mission hotel, but rebounded for the post-mission hotel such that post-mission hotel rating were often higher than all previous ratings. Within HERA, ratings of how a habitat area impacted an outcome skewed towards facilitation with communal areas (i.e., galley and office) rated most facilitating. The follow up questions about why six key aspects related to habitability moderated outcomes indicated that most habitat areas were rated as having “adequate” habitability characteristics. Privacy was the only moderator with average scores below adequate for all habitat areas. The office had the most moderators scoring above adequate for all habitat areas. Ratings indicated small to moderate effects of layouts on BHP outcomes: with facilitating layouts averaging between 4 and 5, and impairing layouts averaging between 2 and 4. The sleeping module layout facilitated sleep, with ratings indicating adequate comfort but inadequate privacy. The galley layout facilitated social interaction and mood, with ratings indicating adequate efficiency and convenience. The office layout facilitated social interaction, team and individual performance, with ratings similarly indicating adequate efficiency and convenience. The hygiene module worsened individual performance, mood and stress, with ratings indicating less than adequate privacy and social density. Our findings suggest there is value in having dedicated team and individual spaces. REFERENCES [1] Roma, P. G., Landon, L.B., Spencer, C. A., Whitmire, A. M., & Williams, T. J. (2022). SHAQ: Development and Validation. Human Factors: Special Issue on Spaceflight, 65(6), 1074-1104. ACKNOWLEDGEMENTS This project was funded by the NASA Human Research Program directed task Human Factors and Behavioral Performance in HERA (PI = S. Bell) to the BHP Lab. KBR Inc. and JES Tech authors were supported by KBR’s Human Health and Performance Contract NNJ15HK11B with NASA.

behavioral health↗
DOE OSTI2021

Ethical, legal and social implications of human genome studies in radiation research: a workshop report for studies on atomic bomb survivors at the Radiation Effects Research Foundation

The Radiation Effects Research Foundation (RERF) is the primary organization in Japan dedicated to studying the health consequences of the Hiroshima and Nagasaki atomic bombings in World War II. In December 2020, RERF held a virtual international workshop on the ethical, legal and social implications (ELSI) of genome studies. In this workshop, the ELSI considerations of future human genome studies on radiation research including atomic bomb survivors and their families were discussed. Since genome sequencing (GS) is now practical and affordable, RERF now plans GS of parents/child trios to examine genetic effects of atomic bomb radiation. As such studies may engender some novel risks and benefits, ethics review and engagement with families (including consent) need to be considered. These include protection of individual privacy, use of samples from deceased prior participants, return of results to the participants, public sharing of genome data and advance science and social welfare. Specifically with regard to social welfare, the results of such studies may have implications for public and government decision-making regarding social benefits of victims and other important questions. Based on these broad-ranging discussions we have developed the following concepts to guide this work: “trust,” “compromise” and “relationship building,” inclusive of the concerned stakeholders, scientific aims and Japanese society at large. We conclude that in order to realize, establish and maintain these concepts, it is essential to put procedures into place to ensure the successful, consensus-based implementation of the RERF studies.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2025

Cognitive IoT and Edge Computing for Intrusion Detection with Federated TinyML

Internet of Things (IoT) and Edge Computing (EC) are rapidly becoming an integral part of the modern society. By 2030, there is estimated to be over 40 billion active and connected IoT devices [1]. This rapid progress also comes with a significant implication on cybersecurity. Back-end infrastructure and systems have a much broader attack than they did previously due to vulnerable IoT/EC devices being connected to wireless networks. This expanding attack surface is a growing concern because IoT/EC are increasingly being used in critical systems such as power grids, health care, and smart homes. To effectively address a problem of this scale, cognitive cyber methods—which can autonomously detect and react to cyber attacks as they develop—are needed. To address this, we bring Artificial Intelligence (AI) and Machine Learning (ML) to IoT/EC devices, using tinyML to monitor voluminous IoT data against cyber threats, and using Federated Learning (FL) to share local detection knowledge across the system while preserving privacy. We propose a novel three-layer architecture: (1) an IoT layer for tinyML-based inference, (2) an edge layer for ML model training, and (3) a cloud layer for FL operations. Using the publicly available 11-class N-BaIoT dataset [2], we demonstrate that this architecture mitigates resource constraints at the IoT layer while improving detection accuracy over standard two-layer designs. An outlier-resistant scaler, feature reduction, and quantization enable the tinyML model to maintain detection accuracy with a reduced model size. Additionally, federated learning that only utilizes the intersection (across heterogenous devices) of the reduced feature set achieves superior detection accuracy compared to locally trained models.

Li, Mingyan [ORNL] (ORCID:0009000569532640)↗
NASA NTRSDate not supplied

Artificial Intelligence Enhancements to Imagery for Space Operations

Philosophy classes still ponder the question asked by Dr. George Berkely, an Anglican Bishop and philosopher in the 1600’s-- “If a tree falls in a forest and no one is around to hear it, does it make a sound?” With that in mind, I ask the following—If a still image or motion imagery from a space mission cannot be found during a search, does it exist? Since the beginning of spaceflight, imagery has been a key form of data collected. Whether for mere curiosity (what does Earth look like from Space?), or for operational reasons (did the solar panel deploy?), or for engineering purposes (what was that object that floated away from the spacecraft?), imagery has been included in space missions. To be useful, though, the image or motion imagery must be accessible and accessed when needed. During the analog era, that typically meant captions and numbers associated with the physical media. With “born digital” imagery, it is possible to add metadata to the image data file. This metadata might include the date and time of capture, mission, camera, exposure data, and similar data fields. Many modern cameras embed some basic metadata into the image file at the moment of capture. The reality, though, is even with today’s born-digital enhancements with embedded metadata at the time of capture, reviewing and cataloging still and motion imagery is very labor intensive. Humans review the imagery for sensitive content (privacy concerns, imagery containing proprietary data/subject matter), and to identify imagery containing crew members or imagery that should be reviewed for engineering or scientific reasons. All this review and manual data entry is very time-consuming. Many improvements in Artificial Intelligence (AI), Machine Learning, and processing power now make it possible to identify persons, objects, motion, color, audio with sensitive content, and other details after or while the imagery is captured.

Rodney Grubbs↗
DOE OSTI2024

Ultrasound Interim cyber-physical research evaluation

Recent events have presented Medical Practitioners with concerns about safety and privacy implications associated with GE’s VScan MIot Ultrasound Device. Concerns relate to the devices potential risk to broadcast location data that can pose serious risks to device users and patients. This report was commission in collaboration with Augusta University to determine if device concerns pose real threat to operators and patients. In effort to ensure all potential threat vectors are targeted, the initial step was to analyze the supply chain. Here the devices are CT scanned to look for any hardware anomalies that could present threat vectors to users of these devices. (See SRNL-STI-2024-00225 for detailed analysis). No anomalies were found associated with the hardware utilized within the GE VScan Air.

42 ENGINEERING↗
DOE OSTI2021

A high-fidelity residential building occupancy detection dataset

Abstract This paper describes development of a data acquisition system used to capture a range of occupancy related modalities from single-family residences, along with the dataset that was generated. The publicly available dataset includes: grayscale images at 32-by-32 pixels, captured every second; audio files, which have undergone processing to remove personally identifiable information; indoor environmental readings, captured every ten seconds; and ground truth binary occupancy status. The data acquisition system, coined the mobile human presence detection (HPDmobile) system, was deployed in six homes for a minimum duration of one month each, and captured all modalities from at least four different locations concurrently inside each home. The environmental modalities are available as captured, but to preserve the privacy and identity of the occupants, images were downsized and audio files went through a series of processing steps, as described in this paper. This dataset adds to a very small body of existing data, with applications to energy efficiency and indoor environmental quality.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

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↗