ESTABLISHMENT OF CYBER-PHYSICAL CORRELATION AND VERIFICATION BASED ON ATTACK SCENARIOS IN POWER SUBSTATIONS

Insurance businesses for the cyberworld are an evolving opportunity. However, a quantitative model in today\u27s security technologies may not be established. Besides, a generalized methodology to assess the systematic risks remains underdeveloped. There has been a technical challenge to capture intrusion risks of the cyber-physical system, including estimating the impact of the potential cascaded events initiated by the hacker\u27s malicious actions. This dissertation attempts to integrate both modeling aspects: 1) steady-state probabilities for the Internet protocol-based substation switching attack events based on hypothetical cyberattacks, 2) potential electricity losses. The phenomenon of sequential attacks can be characterized using a time-domain simulation that exhibits dynamic cascaded events. Such substation attack simulation studies can establish an actuarial framework for grid operation. The novelty is three-fold. First, the development to extend features of steady-state probabilities is established based on 1) modified password models, 2) new models on digital relays with two-step authentications, and 3) honeypot models. A generalized stochastic Petri net is leveraged to formulate the detailed statuses and transitions of components embedded in a Cyber-net. Then, extensive modeling of steady-state probabilities is qualitatively performed. Methodologies on how transition probabilities and rates are extracted from network components and actuarial applications are summarized and discussed. Second, dynamic models requisite for switching attacks against multiple substations or digital relays deployed in substations are formulated. Imperative protection and control models to represent substation attacks are clarified with realistic model parameters. Specifically, wide-area protections, i.e., special protection systems (SPSs), are elaborated, asserting that event-driven SPSs may be skipped for this type of case study. Third, the substation attack replay using a proven commercially available time-domain simulation tool is validated in IEEE system models to study attack combinations\u27 critical paths. As the time-domain simulation requires a higher computational cost than power flow-based steady-state simulation, a balance of both methods is established without missing the critical dynamic behavior. The direct impact of substation attacks, i.e., electricity losses, is compared between steady-state and dynamic analyses. Steady-state analysis results are prone to be pessimistic for a smaller number of compromised substations. Finally, simulation findings based on the risk-based metrics and technical implementation are extensively discussed with future work

Therapeutic Approaches to Vascular Protection in Ischemic Stroke

Reperfusion with recombinant tissue plasminogen activator (tPA) sometimes causes catastrophic hemorrhagic transformation (HT) in the ischemic brain. Consequently, the application of tPA has been strictly limited. Recent studies have indicated that matrix metalloproteinases (MMPs), especially MMP-9, play a critical role in blood brain barrier (BBB) disruption in the ischemic brain, leading to brain edema and HT. In the ischemic brain, free radicals and exogenous tPA itself can trigger MMP-9 activation through several signaling pathways containing LDL receptor-related protein (LRP) and proteinase-activated receptor 1 (PAR1). Therapeutic targeting of free radicals and MMP-9/t-PA related signaling pathways might be promising approaches to minimizing catastrophic HT in acute stroke patients. We provide an overview of the available scientific reports to improve our understanding of the mechanisms leading to HT, and highlight recent progress in the development of new therapeutic strategies for preventing HT in the post-stroke brain

The Deodorizing Effect of Weak Acid Hypochlorous Solution against Ammonia

The deodorizing effect of weak acid hypochlorous solution against ammonia was investigated. When atomized particles of weak acid hypochlorous solution contacted ammonia, the ammonia concentration decreased in a concentration-dependent manner. The deodorizing effect was also observed against ammonia generated from the used floor cover for mice. When the floor mat was present, the ammonia concentration gently decreased but then rapidly decreased when the floor mat was removed. In the future, we will examine effective spraying conditions for weak acid hypochlorous solution in laboratory animal facilities, and we will also proceed with the validation of effects other than spraying

Impact Assessment of Hypothesized Cyberattacks on Interconnected Bulk Power Systems

The first-ever Ukraine cyberattack on power grid has proven its devastation by hacking into their critical cyber assets. With administrative privileges accessing substation networks/local control centers, one intelligent way of coordinated cyberattacks is to execute a series of disruptive switching executions on multiple substations using compromised supervisory control and data acquisition (SCADA) systems. These actions can cause significant impacts to an interconnected power grid. Unlike the previous power blackouts, such high-impact initiating events can aggravate operating conditions, initiating instability that may lead to system-wide cascading failure. A systemic evaluation of "nightmare" scenarios is highly desirable for asset owners to manage and prioritize the maintenance and investment in protecting their cyberinfrastructure. This survey paper is a conceptual expansion of real-time monitoring, anomaly detection, impact analyses, and mitigation (RAIM) framework that emphasizes on the resulting impacts, both on steady-state and dynamic aspects of power system stability. Hypothetically, we associate the combinatorial analyses of steady state on substations/components outages and dynamics of the sequential switching orders as part of the permutation. The expanded framework includes (1) critical/noncritical combination verification, (2) cascade confirmation, and (3) combination re-evaluation. This paper ends with a discussion of the open issues for metrics and future design pertaining the impact quantification of cyber-related contingencies

Effect of edaravone on pregnant mice and their developing fetuses subjected to placental ischemia

Growing evidence indicates that reduced uterine perfusion pressure (RUPP) triggers the cascade of events leading to preeclampsia. Edaravone is a powerful free radical scavenger used for the treatment of ischemia/reperfusion diseases due to its anti-oxidative stress and anti-inflammatory properties. Here we investigate the effect of edaravone (3 mg/kg) on different maternal and fetal outcomes of RUPP-induced placental ischemia mice model. RUPP surgery was performed on gestation day (GD) 13 followed by edaravone injection from GD14 to GD18, sacrifice day. The results showed that edaravone injection significantly decreased the maternal blood pressure (113.2 +/- 2.3 mmHg) compared with RUPP group (131.5 +/- 1.9 mmHg). Edaravone increased fetal survival rate (75.4%) compared with RUPP group (54.4%), increased fetal length, weights, and feto-placental ratio (7.2 and 5.7 for RUPP and RUPP-Edaravone groups, respectively) compared with RUPP group. In addition, RUPP resulted in many fetal morphological abnormalities as well as severe delayed ossification, however edaravone decreased the morphological abnormalities and increased the ossification of the fetal endoskeleton. Edaravone improved the histopathological structure of the maternal kidney and heart as well as decreased the elevated blood urea and creatinine levels (31.5 +/- 0.15 mg/dl (RUPP), 25.6 +/- 0.1 mg/dl (RUPP+edaravone) for urea and 5.4 +/- 0.1 mg/dl (RUPP), 3.5 +/- 0.1 mg/dl (RUPP+edaravone) for creatinine) and decreased cleaved caspase-3 expression in the maternal kidney. In conclusion, this study demonstrated that our RUPP mice model recapitulated preeclampsia symptoms and edaravone injection ameliorated most of these abnormalities suggesting its effectiveness and potential application in preeclampsia treatment regimes

Adversarial Purification for Data-Driven Power System Event Classifiers with Diffusion Models

The global deployment of the phasor measurement units (PMUs) enables real-time monitoring of the power system, which has stimulated considerable research into machine learning-based models for event detection and classification. However, recent studies reveal that machine learning-based methods are vulnerable to adversarial attacks, which can fool the event classifiers by adding small perturbations to the raw PMU data. To mitigate the threats posed by adversarial attacks, research on defense strategies is urgently needed. This paper proposes an effective adversarial purification method based on the diffusion model to counter adversarial attacks on the machine learning-based power system event classifier. The proposed method includes two steps: injecting noise into the PMU data; and utilizing a pre-trained neural network to eliminate the added noise while simultaneously removing perturbations introduced by the adversarial attacks. The proposed adversarial purification method significantly increases the accuracy of the event classifier under adversarial attacks while satisfying the requirements of real-time operations. In addition, the theoretical analysis reveals that the proposed diffusion model-based adversarial purification method decreases the distance between the original and compromised PMU data, which reduces the impacts of adversarial attacks. The empirical results on a large-scale real-world PMU dataset validate the effectiveness and computational efficiency of the proposed adversarial purification method