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Security vulnerabilities such as Meltdown and Spectre demonstrate how chip complexity grew faster than our ability to manage unintended consequences. Here, attention to security from the outset should be part of the rememdy, yet complexity must be controlled at a more fundamental level.
Some influential American policymakers, scholars, and analysts are extremely concerned with the effects that quantum computing will have on national security. Similar to the way space technology was viewed in the context of the US-Soviet rivalry in the Cold War, they view scientific advancement in quantum computing as a race with significant national security consequences and a part of the emerging US-China rivalry. It is claimed that the winner of this race will be able to thwart all the cryptographic efforts of the loser and gain unfettered access to any state secret of the losing government. Additionally, it is suggested that the winner will be able to protect their secrets with a higher level of security than contemporary cryptography guarantees at the moment. This paper argues that these three claims are considerably overstated, and that policymakers and scholars should shift focus to a different national security problem that quantum computing will create. Maintaining the long-term security of secret information secured by contemporary cryptographic protections, which will fail against an attack by a future quantum computer, is the predominant challenge needing attention. This paper takes a technically-informed approach to this issue. It first lays out the national security problems that are envisioned in much of the current discourse surrounding quantum computing. Then, it will assess the technical advantages that quantum computers will have over classical computers in the field of cryptography. Next, it will provide an explanation of the specific ways that the technical realities of quantum computing are inconsistent with the predominant areas of concern. Following, it will highlight the more pressing national security problem posed by quantum computing that the public discussion has, for the most part, missed. The piece will conclude with recommendations for how to mitigate this issue.
Distributed-object computing systems are presented with many security threats, including network eavesdropping, message tampering, and communications middleware masquerading. NASA Glenn Research Center, and its industry partners, has taken an active role in mitigating the security threats associated with developing and operating their proprietary aerospace propulsion simulations. In particular, they are developing a collaborative Common Object Request Broker Architecture (CORBA) Security (CORBASec) test bed to secure their distributed aerospace propulsion simulations. Glenn has been working with its aerospace propulsion industry partners to deploy the Numerical Propulsion System Simulation (NPSS) object-based technology. NPSS is a program focused on reducing the cost and time in developing aerospace propulsion engines
A guide is provided to system security with emphasis on requirements and guidelines that are necessary to maintain an acceptable level of security on the network. To have security for the network, each node on the network must be secure. Therefore, each system manager, must strictly adhere to the requirements and must consider implementing the guidelines discussed. There are areas of vulnerability within the operating system that may not be addressed. However, when a requirement or guideline is discussed, implementation techniques are included. Information related to computer and data security is discussed to provide information on implementation options. The information is presented as it relates to a VAX computer environment.
The classical computing has already done wonders with computation, however limitations on speed and security of transmitted information is endorsing novel computation techniques. Quantum computing is expected to resolve complex problems especially for unachievable speed with best possible secure communication. The logic gates for two Quantum bits (qubits) are one of the most important part of information processing in Quantum computing. Although photons are the best candidates for the processing of qubit but they need lots of nonlinear coupling to perform logic operations. Recent developments in the field of integrated optics showing promising signs for the development of Quantum networks and Quantum computation. In this article we have reviewed the technology of handling polarization encoded Qubit to perform logic operations and interconnections of logic circuits.
Big data has a potential to unlock novel groundbreaking opportunities in the power grid sector that enhances a multitude of technical, social, and economic gains. The currently untapped potential of applying the science of big data for better planning and operation of the power grid is a very challenging task and needs significant efforts all-around. As power grid technologies evolve in conjunction with measurement and communication technologies, this results in unprecedented amount of heterogeneous big data sets from diverse sources. In particular, computational complexity, data security, and operational integration of big data into utility decision frameworks are the key challenges to transform the heterogeneous large dataset into actionable outcomes. Moreover, due to the complex nature of power grids along with the need to balance power in real time, seamless integration of big data into utility operations is very critical. In this context, big data analytics combined with grid visualization can lead to better situational awareness and predictive decisions. This paper presents a comprehensive state-of-the-art review of big data analytics and its applications in power grids, and also identifies challenges and opportunities from utility, industry, and research perspectives. The paper analyzes research gaps and presents insights on future research directions to integrate big data analytics into electric utility decision framework. Detailed information for utilities looking to apply big data analytics and details insights on how utilities can enhance revenue streams and bring disruptive innovation in the industry are discussed. More importantly, general guidelines for utilities to make the right investment in the adoption of big data analytics by unveiling interdependencies among critical infrastructures and operations are also provided.
The following subject areas are covered: a DOD development system - the Army Secure Operating System; non-development commercial computer systems; security, integrity, and assurance of service (SI and A); post delivery SI and A and malicious software; computer system unique attributes; positive feedback to commercial computer systems vendors; and NDI (Non-Development Item) computers and software safety.
Abstract not provided.
Edge computing methods allow devices to efficiently train a high-performing, robust, and personalized model for predictive tasks. However, these methods succumb to privacy and scalability concerns such as adversarial data recovery and expensive model communication. Furthermore, edge computing methods unrealistically assume that all devices train an identical model. In practice, edge devices have varying computational and memory constraints which may not allow certain devices to have the space or speed to train a specific model. To overcome these issues, we propose MIDDLE: a model independent distributed learning algorithm which allows heterogeneous edge devices to assist each other’s training while communicating only non-sensitive information. MIDDLE unlocks the ability for edge devices, regardless of computational or memory constraints, to assist each other even with completely different model architectures. Furthermore, MIDDLE does not require model or gradient communication which greatly reduces communication size and time. We prove that MIDDLE attains the optimal convergence rate O(1/sqrt(TM)) of stochastic gradient descent for convex and non-convex smooth optimization (for total iterations T and batch size M). Finally, our experimental results demonstrate that MIDDLE (even in non-IID data settings) attains robust and high-performing models without model or gradient communication.
Abstract not provided.
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As electric power systems undergo a transformative upgrade with the integration of advanced technologies to enable the smarter electric grid, professionals who work in the area require a new understanding of the evolving complexity of the grid. Cyber Infrastructure for the Smart Electric Grid delivers a comprehensive overview of the fundamental principles of smart grid operation and control, smart grid technologies, including sensors, communication networks, computation, data management, and cyber security, and the interdependencies between the component technologies on which a smart grid's security depends. The book offers readers the opportunity to critically analyze the smart grid infrastructure needed to sense, communicate, compute, and control in a secure way.
Center 9300 is very proud to provide a wide range of computing and networking resources ranging from desktop support to high performance computing that enable Sandia’s national security mission needs. Our goal is to provide these services in the most efficient, secure, user friendly, and agile means necessary. High performance computing is one example of how we are delivering on this goal. Thanks to investments from NNSA’s Advanced Simulation and Computing program, coupled with Sandia’s Institutional Computing program, a wide variety of computing resources are available and used to support national security needs. This year we are expanding our high performance computing infrastructure with the procurement of institutional resources for information computing or analytics. Big data analytics has been the buzzword in the computing industry for over a decade now and industries in finance, food and drug, business, and security organizations have been leading the charge. Much like how scientific computing has changed the way science and engineering are performed, data analytics is changing just about every aspect of our lives and more especially our ability to contribute to the national security mission of Sandia. This third edition of our HPC Annual Report continues our commitment to communicate the details and impact of Sandia’s large-scale computing resources that support missions work across Sandia. The Laboratories’ and NNSA’s strategic investments in high performance computing demonstrate our commitment to keeping mission-related research on the cutting edge of science, at pace with technology advances, and at a scale that meets the toughest demands of the nation we so proudly serve.
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The control of future power grids is migrating from a centralized to a distributed/decentralized scheme to enable a massive penetration of distributed energy resources with rising dependence on communication infrastructure. A common assumption made for most existing distributed/decentralized controllers is that local controllers would faithfully follow the designated controller dynamics based on the data received from communication channels. However, with increased probability of cyberattacks on Operational Technology infrastructure, such an assumption could be risky because proper execution of the controller dynamics is then built on trust in secure communication and computation. In this work, we leverage a cryptography technology known as zero-knowledge scalable transparent arguments of knowledge (zk-STARK) to verify the computational integrity of power grid control algorithms, with projected linear dynamics-based control schemes as the initial proof-of-concept test case. The method presented here converts the cybersecurity challenge of data integrity for grid control into a subset of computational integrity.
This paper introduces an extended taxonomy of faults specific to hybrid quantum-classical systems, addressing the unique challenges that arise from integrating quantum accelerators into high-performance computing (HPC) infrastructures. Building on the foundational fault classification by Avizienis et al., we incorporate fault types unique to quantum computing-such as qubit decoherence, spontaneous gate errors, and photon loss-alongside traditional and human-induced faults including development errors, operational mistakes, and malicious attacks. Our taxonomy classifies faults by their origin (natural vs. human-made), intent (accidental, deliberate non-malicious, or malicious), system boundaries (internal vs. external), and persistence (transient to permanent). We also explore how different architectural integration patterns-ranging from tight coupling to loose on-premise and cloud-based configurations-shape the manifestation and propagation of faults. These scenarios are analyzed in terms of timing mismatches, interface inconsistencies, and security threats such as data tampering and denial-of-service attacks. Through this fault-centric lens, we aim to support the co-design of dependable quantum-classical systems and highlight the critical role that integration strategies play in ensuring reproducibility, resilience, and security across hybrid computing platforms.
In probabilistic risk assessment, it is important to have an environment where analysts have access to a shared and secured high performance computing and a statistical analysis tool package. As part of the advanced small modular reactor probabilistic risk analysis framework implementation, we have identified the need for advanced Bayesian computations. However, in order to make this technology available to non-specialists, there is also a need of a simplified tool that allows users to author models and evaluate them within this framework. As a proof-of-concept, we have implemented an advanced open source Bayesian inference tool, OpenBUGS, within the browser-based cloud risk analysis framework that is under development at the Idaho National Laboratory. This development, the “OpenBUGS Scripter” has been implemented as a client side, visual web-based and integrated development environment for creating OpenBUGS language scripts. It depends on the shared server environment to execute the generated scripts and to transmit results back to the user. The visual models are in the form of linked diagrams, from which we automatically create the applicable OpenBUGS script that matches the diagram. These diagrams can be saved locally or stored on the server environment to be shared with other users.
My overall sense of the cyber defense field is one of an adolescent discipline currently bogged down in a cloud of issues, the most iconic of which is the great diversity of approaches that are being aggregated to form a coherent field. Because my own expertise is complex systems and materials physics research, I have limited direct experience in cyber security sciences except as a user of secure networks and computing resources. However, in producing this report, I have found with certainty that there exists no calculus for cyber risk assessment, mitigation, and response, although some hopeful precepts toward this end are emerging.