83 research outputs found
Sustainability Awareness Week 2021: esa New York presents Halima Garrett of Threads of Habit
No full textIn this workshop, master-thrifter and designer, Halima Garrett, will describe the importance and craft of upcycling. She will give advice for identifying materials that can be upcycled and take the audience through a short upcycling tutorial to show how it is done in a way that minimizes waste and maximizes utility and style. Ms. Garrett is the founder of Threads of Habit, a New Jersey-based outlet offering bold, eccentric, and unique vintage pieces.Sustainability is a key component of FIT’s mission and is embedded in the college’s curriculum and operations. During virtual Sustainability Awareness Week, we invite our community to learn about recent innovations from leaders in the industry, FIT students, faculty, staff, and alumni; experience FIT’s efforts to make a positive impact on the earth; and discover new ways to live with a smaller footprint
The traumatic experience and sexual violence in Halima Bashir’s tears of the desert
Full text linkEl objetivo principal de este trabajo se centra en el análisis de la experiencia traumática de la escritora sudanesa Halima Bashir en su obra autobiográfica Las lágrimas del desierto. A la hora de analizar la obra hemos tenido en cuenta los postulados del trauma para entender la función de la memoria como herramienta a partir de la cual la memoria individual de Halima se convierte en memoria colectiva para los sudaneses oprimidos en Darfur. La obra de Halima, aunque se centra en la experiencia de violación de un individuo, implica un mensaje político y un testimonio histórico de las atrocidades en Darfur.This paper applies trauma theory to Tears of the Desert, an autobiography written by the Sudanese author Halima Bashir. It examines the traumatic experience of the protagonist Halima Bashir who has been raped during Darfur conflict. In applying the aforementioned theory, this paper shows how the traumatic memory of Halima stands as a collective memory for the oppressed Sudanese in Darfur. Halima’s work, although focusing on the rape experience of an individual, implies a political message that many Sudanese were subjected to physical and psychological traumas as they were bearing witness to the conflict in Darfur
Halima C. Schmaling, Lawan Bala Hausawa (co-author of Book 1). Maganar Hannu. Harshen Bebaye na ƙasar Hausa/Hausa Sign Language. Liffafi na farko: Iyali/Book 1: Family, Kano: Good Image Printing Ltd., 2011, 28 pp; Littafi na biyu: Haɗuwa da sadarwa/Book 2: Meeting and communicating, Hamburg: Helmut Buske Verlag, 2013, 31 pp; Littafi na uku: Kwatancin mutane da abubuwa/Book 3: Describing people and things, Hamburg: Helmut Buske Verlag, 2016, 35 pp; Littafi na huɗu: Kasuwanci da kiɗaya/Book 4: Commerce and counting, Hamburg: Helmut Buske Verlag 2016, 32 pp; Littafi na biyar: Ayyukan yau da kullum/Book 5: Everyday activities, Hamburg: Helmut Buske Verlag, 2017, 35 pp.
No full textA review of series of books by Halima C. Schmaling, Lawan Bala Hausawa (co-author of Book 1). Maganar Hannu
An Integrated Cybersecurity Risk Management (I-CSRM) Framework for Critical Infrastructure Protection
Full text linkRisk management plays a vital role in tackling cyber threats within the Cyber-Physical System (CPS) for overall system resilience. It enables identifying critical assets, vulnerabilities, and threats and determining suitable proactive control measures to tackle the risks. However, due to the increased complexity of the CPS, cyber-attacks nowadays are more sophisticated and less predictable, which makes risk management task more challenging. This research aims for an effective Cyber Security Risk Management (CSRM) practice using assets criticality, predication of risk types and evaluating the effectiveness of existing controls. We follow a number of techniques for the proposed unified approach including fuzzy set theory for the asset criticality, machine learning classifiers for the risk predication and Comprehensive Assessment Model (CAM) for evaluating the effectiveness of the existing controls.The proposed approach considers relevant CSRM concepts such as threat actor attack pattern, Tactic, Technique and Procedure (TTP), controls and assets and maps these concepts with the VERIS community dataset (VCDB) features for the purpose of risk predication. Also, the tool serves as an additional component of the proposed framework that enables asset criticality, risk and control effectiveness calculation for a continuous risk assessment. Lastly, the thesis employs a case study to validate the proposed i-CSRM framework and i-CSRMT in terms of applicability. Stakeholder feedback is collected and evaluated using critical criteria such as ease of use, relevance, and usability. The analysis results illustrate the validity and acceptability of both the framework and tool for an effective risk management practice within a real-world environment.The experimental results reveal that using the fuzzy set theory in assessing assets' criticality, supports stakeholder for an effective risk management practice. Furthermore, the results have demonstrated the machine learning classifiers’ have shown exemplary performance in predicting different risk types including denial of service, cyber espionage, and Crimeware. An accurate prediction can help organisations model uncertainty with machine learning classifiers, detect frequent cyber-attacks, affected assets, risk types, and employ the necessary corrective actions for its mitigations.Lastly, to evaluate the effectiveness of the existing controls, the CAM approach is used, and the result shows that some controls such as network intrusion, authentication, and anti-virus show high efficacy in controlling or reducing risks. Evaluating control effectiveness helps organisations to know how effective the controls are in reducing or preventing any form of risk before an attack occurs. Also, organisations can implement new controls earlier. The main advantage of using the CAM approach is that the parameters used are objective, consistent and applicable to CPS
Cyber Threat Intelligence for Improving Cybersecurity and Risk Management in Critical Infrastructure
No full textCyber-attack is one of the significant threats affecting to any organisation specifically to the Critical Infrastructure (CI) organisation. These attacks are nowadays more sophisticated, multi-vectored and less predictable, which make the Cyber Security Risk Management (CSRM) task more challenging. Critical Infrastructure needs a new line of security defence to control these threats and minimise risks. Cyber Threat Intelligence (CTI) provides evidence-based information about the threats aiming to prevent threats. There are existing works and industry practice that emphasise the necessity of CTI and provides methods for threat intelligence and sharing. However, despite these significant efforts, there is a lack of focus on how CTI information can support the CSRM activities so that the organisation can undertake appropriate controls to mitigate the risk proactively. This paper aims to fill this gap by integrating CTI for improving cybersecurity risks management practice specifically focusing on the critical infrastructure. In particular, the proposed approach contributes beyond state of the art practice by incorporating CTI information for the risk management activities. This helps the organisation to provide adequate and appropriate controls from strategic, tactical and operational perspectives. We have integrated concepts relating to CTI and CSRM so that threat actor's profile, attack detailed can support calculating the risk. We consider smart grid system as a Critical Infrastructure to demonstrate the applicability of the work. The result shows that cyber risks in critical infrastructures can be minimised if CTI information is gathered and used as part of CSRM activities. CTI not only supports understanding of threat for accurate risk estimation but also evaluates the effectiveness of existing controls and recommend necessity controls to improve overall cybersecurity. Also, the result shows that our approach provides early warning about issues that need immediate attention
Cyber Threat Intelligence for Improving Cybersecurity and Risk Management in Critical Infrastructure
Full text linkCyber-attack is one of the significant threats affecting to any organisation specifically to the Critical Infrastructure (CI) organisation. These attacks are nowadays more sophisticated, multi-vectored and less predictable, which make the Cyber Security Risk Management (CSRM) task more challenging. Critical Infrastructure needs a new line of security defence to control these threats and minimise risks. Cyber Threat Intelligence (CTI) provides evidence-based information about the threats aiming to prevent threats. There are existing works and industry practice that emphasise the necessity of CTI and provides methods for threat intelligence and sharing. However, despite these significant efforts, there is a lack of focus on how CTI information can support the CSRM activities so that the organisation can undertake appropriate controls to mitigate the risk proactively. This paper aims to fill this gap by integrating CTI for improving cybersecurity risks management practice specifically focusing on the critical infrastructure. In particular, the proposed approach contributes beyond state of the art practice by incorporating CTI information for the risk management activities. This helps the organisation to provide adequate and appropriate controls from strategic, tactical and operational perspectives. We have integrated concepts relating to CTI and CSRM so that threat actor's profile, attack detailed can support calculating the risk. We consider smart grid system as a Critical Infrastructure to demonstrate the applicability of the work. The result shows that cyber risks in critical infrastructures can be minimised if CTI information is gathered and used as part of CSRM activities. CTI not only supports understanding of threat for accurate risk estimation but also evaluates the effectiveness of existing controls and recommend necessity controls to improve overall cybersecurity. Also, the result shows that our approach provides early warning about issues that need immediate attention
Assets focus risk management framework for critical infrastructure cybersecurity risk management
Full text linkCritical infrastructure (CI) is vital for the overall economic growth and its reliable and safe operation is essential for a nation's stability and people's safety. Proper operation of the assets is essential for such a system and any threats that could negatively impact the asset could have a severe disruption. Risk management is an important aspect of the protection of CI. There are several frameworks and methodologies for identifying assets, quantifying and analysing vulnerabilities. However, there is a lack of focus on the interdependencies among the assets and cascading effect of the inherent vulnerabilities on the asset. This study attempts to bridge that gap by presenting a novel asset focus risk management approach for the CI. It presents a systematic methodology for identifying and analysing critical assets, their potential vulnerabilities, threats and risks facing CI. This work taking into account cascading vulnerability impacts on assets leading to threats and causing risk. The authors use a running example from a smart grid system to demonstrate the usability of the approach. The result shows that some assets are prioritised and more vulnerable than other assets for the power grid system and it can severely impact on the overall business continuity
Call for Papers: Technologies MDPI Special Issue – Cybersecurity Challenges and Applications of AI in Engineering
Full text linkA special issue of Technologies (ISSN 2227-7080).
Deadline for manuscript submissions: 1 July 2026.
Artificial Intelligence (AI) in engineering has the potential to both enhance cybersecurity defenses through threat detection and automation and create new challenges such as cybercriminals leveraging AI for attacks like deepfakes and adaptive malware. Common applications include automating security tasks, improving threat detection, and enabling real-time incident response, while major challenges include adversarial attacks against AI models, data integration issues, ethical concerns, and the use of AI by attackers to create more sophisticated attacks
An Integrated Cyber Security Risk Management Approach for a Cyber-Physical System
Full text linkA cyber-physical system (CPS) is a combination of physical system components with cyber capabilities that have a very tight interconnectivity. CPS is a widely used technology in many applications, including electric power systems, communications, and transportation, and healthcare systems. These are critical national infrastructures. Cybersecurity attack is one of the major threats for a CPS because of many reasons, including complexity and interdependencies among various system components, integration of communication, computing, and control technology. Cybersecurity attacks may lead to various risks affecting the critical infrastructure business continuity, including degradation of production and performance, unavailability of critical services, and violation of the regulation. Managing cybersecurity risks is very important to protect CPS. However, risk management is challenging due to the inherent complex and evolving nature of the CPS system and recent attack trends. This paper presents an integrated cybersecurity risk management framework to assess and manage the risks in a proactive manner. Our work follows the existing risk management practice and standard and considers risks from the stakeholder model, cyber, and physical system components along with their dependencies. The approach enables identification of critical CPS assets and assesses the impact of vulnerabilities that affect the assets. It also presents a cybersecurity attack scenario that incorporates a cascading effect of threats and vulnerabilities to the assets. The attack model helps to determine the appropriate risk levels and their corresponding mitigation process. We present a power grid system to illustrate the applicability of our work. The result suggests that risk in a CPS of a critical infrastructure depends mainly on cyber-physical attack scenarios and the context of the organization. The involved risks in the studied context are both from the technical and nontechnical aspects of the CPS
Protection of critical infrastructure using an Integrated Cybersecurity Risk Management (i-CSRM) framework
Full text linkRisk management plays a vital role in tackling cyber threats within the cyber-physical system (CPS) for overall system resilience. It enables identifying critical assets, vulnerabilities, and threats and determining suitable proactive control measures to tackle the risks. However, due to the increased complexity of the CPS, cyber-attacks nowadays are more sophisticated and less predictable, which makes risk management task more challenging. This chapter proposes an integrated cyber security risk management (i-CSRM) framework for systematically identifying critical assets through the use of a decision support mechanism built on fuzzy set theory, predicting risk types through machine learning techniques, and assessing the effectiveness of existing controls through the use of comprehensive assessment model (CAM) parameters
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