7,840 research outputs found
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
A Novel Side-Channel in Real-Time Schedulers
We demonstrate the presence of a novel scheduler side-channel in preemptive,
fixed-priority real-time systems (RTS); examples of such systems can be found
in automotive systems, avionic systems, power plants and industrial control
systems among others. This side-channel can leak important timing information
such as the future arrival times of real-time tasks.This information can then
be used to launch devastating attacks, two of which are demonstrated here (on
real hardware platforms). Note that it is not easy to capture this timing
information due to runtime variations in the schedules, the presence of
multiple other tasks in the system and the typical constraints (e.g.,
deadlines) in the design of RTS. Our ScheduLeak algorithms demonstrate how to
effectively exploit this side-channel. A complete implementation is presented
on real operating systems (in Real-time Linux and FreeRTOS). Timing information
leaked by ScheduLeak can significantly aid other, more advanced, attacks in
better accomplishing their goals
Applications of Cyber Threat Intelligence (CTI) in Financial Institutions and Challenges in Its Adoption
The critical nature of financial infrastructures makes them prime targets for cybercriminal activities, underscoring the need for robust security measures. This research delves into the role of Cyber Threat Intelligence (CTI) in bolstering the security framework of financial entities and identifies key challenges that could hinder its effective implementation. CTI brings a host of advantages to the financial sector, including real-time threat awareness, which enables institutions to proactively counteract cyber-attacks. It significantly aids in the efficiency of incident response teams by providing contextual data about attacks. Moreover, CTI is instrumental in strategic planning by providing insights into emerging threats and can assist institutions in maintaining compliance with regulatory frameworks such as GDPR and CCPA. Additional applications include enhancing fraud detection capabilities through data correlation, assessing and managing vendor risks, and allocating resources to confront the most pressing cyber threats. The adoption of CTI technologies is fraught with challenges. One major issue is data overload, as the vast quantity of information generated can overwhelm institutions and lead to alert fatigue. The issue of interoperability presents another significant challenge; disparate systems within the financial sector often use different data formats, complicating seamless CTI integration. Cost constraints may also inhibit the adoption of advanced CTI tools, particularly for smaller institutions. A lack of specialized skills necessary to interpret CTI data exacerbates the problem. The effectiveness of CTI is contingent on its accuracy, and false positives and negatives can have detrimental impacts. The rapidly evolving nature of cyber threats necessitates real-time updates, another hurdle for effective CTI implementation. Furthermore, the sharing of threat intelligence among entities, often competitors, is hampered by mistrust and regulatory complications. This research aims to provide a nuanced understanding of the applicability and limitations of CTI within the financial sector, urging institutions to approach its adoption with a thorough understanding of the associated challenges
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An Assessment of PIER Electric Grid Research 2003-2014 White Paper
This white paper describes the circumstances in California around the turn of the 21st century that led the California Energy Commission (CEC) to direct additional Public Interest Energy Research funds to address critical electric grid issues, especially those arising from integrating high penetrations of variable renewable generation with the electric grid. It contains an assessment of the beneficial science and technology advances of the resultant portfolio of electric grid research projects administered under the direction of the CEC by a competitively selected contractor, the University of California’s California Institute for Energy and the Environment, from 2003-2014
Horizontal Cybersurveillance Through Sentiment Analysis
This Essay describes emerging big data technologies that facilitate horizontal cybersurveillance. Horizontal cybersurveillance makes possible what has been termed as “sentiment analysis.” Sentiment analysis can be described as opinion mining and social movement forecasting. Through sentiment analysis, mass cybersurveillance technologies can be deployed to detect potential terrorism and state conflict, predict protest and civil unrest, and gauge the mood of populations and subpopulations. Horizontal cybersurveillance through sentiment analysis has the likely result of chilling expressive and associational freedoms, while at the same time risking mass data seizures and searches. These programs, therefore, must be assessed as adversely impacting a combination of constitutional rights, such as simultaneously affecting both First and Fourth Amendment freedoms
Artificial intelligence and UK national security: Policy considerations
RUSI was commissioned by GCHQ to conduct an independent research study into the use of artificial intelligence (AI) for national security purposes. The aim of this project is to establish an independent evidence base to inform future policy development regarding national security uses of AI. The findings are based on in-depth consultation with stakeholders from across the UK national security community, law enforcement agencies, private sector companies, academic and legal experts, and civil society representatives. This was complemented by a targeted review of existing literature on the topic of AI and national security.
The research has found that AI offers numerous opportunities for the UK national security community to improve efficiency and effectiveness of existing processes. AI methods can rapidly derive insights from large, disparate datasets and identify connections that would otherwise go unnoticed by human operators. However, in the context of national security and the powers given to UK intelligence agencies, use of AI could give rise to additional privacy and human rights considerations which would need to be assessed within the existing legal and regulatory framework. For this reason, enhanced policy and guidance is needed to ensure the privacy and human rights implications of national security uses of AI are reviewed on an ongoing basis as new analysis methods are applied to data
Fundamental Concepts of Cyber Resilience: Introduction and Overview
Given the rapid evolution of threats to cyber systems, new management
approaches are needed that address risk across all interdependent domains
(i.e., physical, information, cognitive, and social) of cyber systems. Further,
the traditional approach of hardening of cyber systems against identified
threats has proven to be impossible. Therefore, in the same way that biological
systems develop immunity as a way to respond to infections and other attacks,
so too must cyber systems adapt to ever-changing threats that continue to
attack vital system functions, and to bounce back from the effects of the
attacks. Here, we explain the basic concepts of resilience in the context of
systems, discuss related properties, and make business case of cyber
resilience. We also offer a brief summary of ways to assess cyber resilience of
a system, and approaches to improving cyber resilience.Comment: This is a preprint version of a chapter that appears in the book
"Cyber Resilience of Systems and Networks," Springer 201
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