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Cyber-Physical Security Analysis of a DER Application for IoT Communications.
Abstract not provided.
Testbed-based Evaluation of SIEM Tool for Cyber Kill Chain Model in Power Grid SCADA System
Development of a smarter electric grid necessitates addressing the associated cyber security challenges. Since the interdependence between the legacy grid infrastructure and advanced information technology is growing rapidly, there are numerous ways advanced, motivated, and persistent attackers can affect the SCADA based critical infrastructure. Hence, developing a security information and event management (SIEM) is crucial for securing the SCADA power system. This paper presents the application of Security Onion (SecOn) to develop the network security monitoring (NSM) and intrusion detection system (IDS) in the context of SCADA cyber physical security. Initially, we have applied a cyber kill-chain model to demonstrate the different stages of attacks and associated mechanisms. Later, the rule- based IDS (RIDS) is developed using Snort IDS, and tested in the cyber-physical SCADA environment. Furthermore, we have evaluated its performance in terms of accuracy and detection latency. Our experimental results reveal that the SecOn tool is efficient in monitoring and detecting attacks within an acceptable time frame with a high accuracy rate.
Keyless Infrastructure Security Solution (Kiss): Examining Security and Trust Gaps
The following cyber security gaps analysis focuses on opportunities and challenges related to applying a unique Keyless Infrastructure Security Solution (KISS) to increase the trustworthiness and integrity of energy delivery systems (EDSs) in electricity infrastructure.
Cybersecurity Standards for Photovoltaic Operations
Solar energy plays an important role in securing a more resilient, cyber-secure electrical grid in Pennsylvania. Solar's ability to be widely "distributed" on residential and large roofs, marginal lands, and many other locations across Pennsylvania - as opposed to being centralized - offers a strong option for addressing the myriad of potential disruptions that can occur to the grid's infrastructure. And when combined with energy storage, local energy needs can be met immediately without having to wait on the delivery of an off-site fuel source. As more and more distributed solar electricity generation is brought online, researchers, technology developers, solar developers and grid operators are paying close attention to the potential for solar to enhance grid cybersecurity. Although nobody may know when, where, or how the next cyberattack will take place, there are security measures, technical solutions, and management practices that are being implemented across the industry to protect against network control issues and grid operations. Everyone participating in the solar value chain stands to gain from a coordinated, iterative approach to protect against cyber vulnerabilities and build deeper resilience into the architecture of our grid.
Quantum Lock Technologies: Innovation Crossroads Final Report
At Quantum Lock Technologies, our mission is to use future-proof hardware and software to bridge the gap between physical access control and cyber security. Physical security includes access to doors, lockboxes/containers, and machinery/robots. Connecting physical access control to the cloud allows for remote detection, fast ledger updates, and mobile or remote access. However, this also opens physical security up to the world of cyber-attacks. At Quantum Lock, we use quantum random number generation to generate completely random and unpredictable digital keys to be used by connected equipment in a facility. This quantum technology is then paired with end-to-end encryption and a one-time-key communication protocol to ensure the highest level of security. Through the Innovation Crossroads program at Oak Ridge National Laboratory, we have developed benchtop prototypes of our technology, connected with utility boards as our first target customers, and prepared for our first pilot with customers (target end of summer 2022). Below is a photograph of myself at an energy substation where we plan to eventually apply our technology.
Cyberattack Detection for Cyber Physical Systems Security–A Preliminary Study.
Cyber-physical systems (CPS) security has become an increasingly important research topic in recent years. Geared towards more advanced cyberattack detection techniques as part of strategies for enhancing the security of CPS, in this paper we propose a machine learning based cyber-attack detection scheme. The proposed scheme is a physical-domain technique; specifically, it assumes the physical measurements of the system carry sufficient information for capturing the system behavior, thus can be used for differentiating normal operation and attacks. CPS are complex in nature and the number of physical measurements available for CPS is often overwhelmingly high. Thus, accurately modeling CPS’ dynamic behavior, more importantly, distinguishing normal and adversary activities based on the large number of physical measurements, can be challenging. To address the challenge, we have focused our research effort on feature engineering, that is, to intelligently derive a set of salient signatures or features from the noisy measurements. We make sure the derived features are more compact and, more importantly, have more discriminant power than the original physical measurements, thus enabling us to achieve more accurate and robust detection performance. To demonstrate the effectiveness of the proposed scheme, in our experimental study we consider gas turbines of combined cycle power plants as the cyberphysical system. Using the data from the high-fidelity simulation we show that our proposed cyberattack detection scheme is able to achieve high detection performance.
Authentication Without Secrets
This work examines a new approach to authentication, which is the most fundamental security primitive that underpins all cyber security protections. Current Internet authentication techniques require the protection of one or more secret keys along with the integrity protection of the algorithms/computations designed to prove possession of the secret without actually revealing it. Protecting a secret requires physical barriers or encryption with yet another secret key. The reason to strive for "Authentication without Secret Keys" is that protecting secrets (even small ones only kept in a small corner of a component or device) is much harder than protecting the integrity of information that is not secret. Promising methods are examined for authentication of components, data, programs, network transactions, and/or individuals. The successful development of authentication without secret keys will enable far more tractable system security engineering for high exposure, high consequence systems by eliminating the need for brittle protection mechanisms to protect secret keys (such as are now protected in smart cards, etc.). This paper is a re-release of SAND2009-7032 with new figures numerous edits.
Quantum Graph Analysis
In recent years, advanced network analytics have become increasingly important to na- tional security with applications ranging from cyber security to detection and disruption of ter- rorist networks. While classical computing solutions have received considerable investment, the development of quantum algorithms to address problems, such as data mining of attributed relational graphs, is a largely unexplored space. Recent theoretical work has shown that quan- tum algorithms for graph analysis can be more efficient than their classical counterparts. Here, we have implemented a trapped-ion-based two-qubit quantum information proces- sor to address these goals. Building on Sandia's microfabricated silicon surface ion traps, we have designed, realized and characterized a quantum information processor using the hyperfine qubits encoded in two 171 Yb + ions. We have implemented single qubit gates using resonant microwave radiation and have employed Gate set tomography (GST) to characterize the quan- tum process. For the first time, we were able to prove that the quantum process surpasses the fault tolerance thresholds of some quantum codes by demonstrating a diamond norm distance of less than 1 . 9 x 10 [?] 4 . We used Raman transitions in order to manipulate the trapped ions' motion and realize two-qubit gates. We characterized the implemented motion sensitive and insensitive single qubit processes and achieved a maximal process infidelity of 6 . 5 x 10 [?] 5 . We implemented the two-qubit gate proposed by Molmer and Sorensen and achieved a fidelity of more than 97 . 7%.
Cyber Infrastructure for the Smart Electric Grid
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.
Joint attack detection and secure state estimation of cyber-physical systems
Not provided.
Detection and Diagnosis of Data Integrity Attacks in Solar Farms Based on Multilayer Long Short-Term Memory Network
Photovoltaic (PV) systems are becoming more vulnerable to cyber threats. In response to this emerging concern, developing cyber-secure power electronics converters has received increased attention from the IEEE Power Electronics Society that recently launched a cyber-physical-security initiative. Here this letter proposes a deep sequence learning based diagnosis solution for data integrity attacks on PV systems in smart grids, including dc–dc and dc–ac converters. The multilayer long short-term memory networks are used to leverage time-series electric waveform data from current and voltage sensors in PV systems. The proposed method has been evaluated in a PV smart grid benchmark model with extensive quantitative analysis. As a comparison, we have evaluated classic data-driven methods, including K-nearest neighbor, decision tree, support vector machine, artificial neural network, and convolutional neural network. Comparison results verify performances of the proposed method for detection and diagnosis of various data integrity attacks on PV systems.
Vulnerability Assessments for Power-Electronics-Based Smart Grids
Here, in this paper, a novel method is proposed to evaluate the cyber security of the power-electronics-based smart grids (PESG). The proposed method considers the performance and stability of both the individual inverter and the grid. To our knowledge, this is a first attempt to evaluate the performance and stability of PESG due to cyber attacks. We first develop impedance-based modeling and cyber-attack modeling for PESG. Then we propose innovative two security criteria to evaluate the security of PESG, including stability-based and metrics-based. For metrics-based criteria, we propose to use both total harmonic distortion (THD) and space phasor model (SPM) to evaluate the inverter performance. The simulation results with a two-inverter-based power grid verify the validity and accuracy of the proposed security evaluation method. Results have shown that the performance and stability of PESG are significantly affected by cyber attacks, and thus there is indeed a need to further study cyber security issues of PESG.
Spatio-Temporal Characterization of Synchrophasor Data Against Spoofing Attacks in Smart Grids
“Source ID Mix” has emerged as a new type of highly deceiving attack which can alter the source information of synchrophasor data measured by multiple phasor measurement units, thereby paralyzing many wide-area measurement systems applications. To address such sophisticated cyber attacks, we have exploited the spatio-temporal characteristics of synchrophasor data for authenticating measurements’ source information. Specifically, the source authentication is performed when the measurements are subjected to three types of spoofing attacks. Some practical difficulties in applying the proposed method on real-time authentication caused by insufficient measurement data have also been solved. Experimental results with real synchrophasor measurements have validated the effectiveness of the proposed method in detecting such complicated data spoofing and improving power systems’ cyber security.
Capability Building Progression of an Insider Threat Mitigation Program at an International Research Reactor
The nuclear industry recognizes the difficulties involved in developing effective managerial and leadership skills in a highly technical and proficient workforce such as that found in nuclear facilities. Implementing an insider threat mitigation program (ITMP) within the nuclear industry is a complex and ongoing process that demands a comprehensive understanding of human behavior, an organization’s security culture, and rigorous regulatory requirements yet also accounts for facility characteristics, physical security, material flow, and activities involving nuclear material. Given the high-consequence nature of research reactor operations, even minor lapses can lead to safety, security, and reputational risks. An effective ITMP requires a defense-in-depth approach that incorporates behavioral analysis, robust vetting procedures, continuous monitoring, and cross-disciplinary coordination. It must also promote a culture of vigilance and accountability at all levels up to and including executive leadership but be flexible enough to adapt to evolving global threats and technological advances. Insider threat mitigation is not a one-time effort but rather a sustained commitment to excellence in safety and security. Establishing a culture in which personnel proactively report incidents and issues that could affect nuclear safety and security is vital to maintaining a safe and secure operational environment. This document was developed to guide senior management and research reactor organizations in creating comprehensive programs to effectively manage and mitigate insider threat behaviors and actions. It focuses on the key pillars of an effective ITMP, including the national legal framework, security culture, preventive and protective measures, cyber security, and performance evaluation. By using a systematic approach during implementation, facilities can foster environments conducive to insider threat detection and support long-term program sustainability. The document also provides strategies for improving communication across all levels of an organization, helping to eliminate barriers that hinder the development of robust ITMPs and enhance overall security culture. In today’s organizations, the concept of leveraging safety and security culture lessons to facilitate knowledge transfer is rapidly evolving to expedite insider threat management and security culture improvements. This document outlines the rationale for evaluating an ITMP based on national customs, culture, and stakeholders. The elements are all germane to reliability and trustworthiness and relate to security concerns that states may encounter. The document focuses not only on individual perceptions regarding security issues and capability building but also on team building and how to resolve concerns. The implementers of a facility’s ITMP may zero in on indicators of insider threats within their enterprise. This material will benefit organizations when it is applied using a systematic and structured approach as demonstrated throughout the document.
A PROVEN APPROACH FOR EFFECTIVE COMPUTER SECURITY SELF-ASSESSMENTS AT NUCLEAR FACILITIES
A proven method for conducting cybersecurity self-assessments at nuclear power plants is now available for international use. This method was originally developed by Pacific Northwest National Laboratory, under the sponsorship of the U.S. Nuclear Regulatory Commission (NRC), for use at U.S. nuclear power plants. The “Method,” described in NUREG/CR-6847 “Cyber Security Self-Assessment Method for U.S. Nuclear Power Plants,” was originally a limited release document that was withheld from public disclosure but is now publicly available. The Method provides a systematic, phased, and risk-informed approach to help decision makers and security specialists understand their relative cybersecurity posture. Completed Method assessments may be used to support or validate selection of computer security controls to mitigate cyber threats as well as demonstrate compliance with regulations or statutes enacted by competent authorities. The Method assesses the cybersecurity posture of key systems at a nuclear facility with a focus on protection of design base functions. It considers both physical and digital elements of system vulnerabilities and the resulting potential consequences from exploitation. It is well-suited for addressing blended cyberattacks. A semi-quantitative analytical approach is used in the evaluation of potential vulnerabilities, consequences, and risks and provides a technical basis for the selection of security controls to mitigate cyberattacks. The Method’s application at U.S. nuclear power plants has been very encouraging. The only nuclear plant in the United States that did not have adverse findings during its initial NRC computer security inspection prepared for inspection through the diligent application of this self-assessment method and the implementation of recommendations that came out of that self-assessment. Nuclear facilities around the world might find application of the Method extremely helpful for making cost-effective, risk-based decisions regarding computer security and for preparing to pass computer security inspections by their competent authorities.
CRADA Number NFE-20-08292 with Quantum Lock Technologies LLC (CRADA Final Report)
At Quantum Lock Technologies, our mission is to use future-proof hardware and software to bridge the gap between physical access control and cyber security. Physical security includes access to doors, lockboxes/containers, and machinery/robots. Connecting physical access control to the cloud allows for remote detection, fast ledger updates, and mobile or remote access. However, this also opens physical security up to the world of cyber-attacks. At Quantum Lock, we use quantum random number generation to generate completely random and unpredictable digital keys to be used by connected equipment in a facility. This quantum technology is then paired with end-to-end encryption and a one-time-key communication protocol to ensure the highest level of security. Through the Innovation Crossroads program at Oak Ridge National Laboratory, we have developed benchtop prototypes of our technology, connected with utility boards as our first target customers, and prepared for our first pilot with customers (target end of summer 2022).