Disaster Recovery Planning Research Articles

Developing a Disaster Recovery Plan to Enhance Corporate Resilience and Ensure Business Continuity

Disasters occur in the corporate operational environment. Earthquakes, floods, fires, and other unpredictable events that might disrupt company activities are among these calamities. The incidence of disasters in the workplace adds to unfavorable consequences. As a result, the construction of a disaster recovery plan becomes necessary for the firm to manage the bad consequences that may arise as a result of the unfavorable occurrences. With a disaster recovery strategy in place, a firm can sustain and swiftly restart normal operations. The firm's disaster recovery plan is a written document that outlines an efficient strategy for dealing with unforeseen and unmanageable catastrophes. Developing a disaster recovery strategy ensures the organization's survival by responding effectively to the present calamity.

Remote sensing assessment of wildfire using high-resolution PlanetScope satellite observations: A case study on Co Tien Mountain, Nha Trang City, Vietnam

In this study, high spatial resolution (3 m) PlanetScope (PS) imagery was utilized to map burned areas caused by a wildfire occurring on January 10, 2024, on Co Tien Mountain in Nha Trang city, Khanh Hoa province, South Central Coast of Vietnam. A pre-fire image, acquired ten days earlier, on December 31, 2023, and a post-fire one, acquired nearly one month after, on February 04, 2024, were used to create pre- and post-fire Normalized Difference Vegetation Index (NDVI) maps of the study area, then the difference of NDVI (dNDVI). A threshold (T = 0.20), proposed by the author, was applied to the histogram of the dNDVI product to classify the study area into two clusters: burned pixels (dNDVI > T) and unburned pixels (dNDVI <= T). Classification results estimate that a total of 16.11 ha of grass, reeds, small shrubs and vegetation have been burned out during the wildfire. A field trip is required to map the burned areas using unmanned aerial vehicles (UAVs) for an accurate validation of results derived purely from PS satellite observations. Although lacking a ground truth dataset for validation is a significant limitation, the proposed approach remains beneficial for local managers and decision-makers. It enables the rapid assessment of damages caused by small wildfires and provides essential data for effective disaster management and recovery planning, particularly in remote areas.

Comprehensive data security and compliance framework for SMEs

Small and Medium-sized Enterprises (SMEs) are increasingly relying on cloud platforms to support critical business operations, making effective disaster recovery (DR) strategies essential for ensuring business continuity. This review proposes a robust disaster recovery framework tailored for SMEs, designed to minimize downtime and data loss in the event of a system failure, cyberattack, or natural disaster. The framework integrates advanced cloud technologies to create a cost-effective, scalable solution that aligns with the resource constraints of SMEs while providing enterprise-grade resilience. Key components of the disaster recovery framework include cloud-based data replication, automated backup solutions, and geo-redundant storage to ensure that data is continuously available and recoverable. This model employs real-time data synchronization and incremental backups to minimize Recovery Point Objectives (RPO), ensuring that critical data is not lost during an unexpected outage. Additionally, the framework leverages automated failover mechanisms to achieve low Recovery Time Objectives (RTO), allowing businesses to restore operations quickly after an interruption. Cloud orchestration tools such as AWS Elastic Disaster Recovery or Azure Site Recovery are utilized to automate disaster recovery processes, reducing manual intervention and improving the speed of recovery. The framework also incorporates regular testing of disaster recovery plans, using simulation tools to identify weaknesses and optimize response times. For SMEs, cost-effectiveness and ease of management are crucial. The framework emphasizes a pay-as-you-go model for cloud resources, allowing businesses to scale their disaster recovery solutions as they grow without incurring excessive upfront costs. By providing continuous monitoring and proactive threat detection, this disaster recovery framework ensures that SMEs can maintain uninterrupted business operations on cloud platforms, thereby enhancing resilience and mitigating the financial and operational risks associated with data loss and system downtime.

Electronic health record downtime responses : One health system’s process for ongoing readiness

Since the implementation of the HITECH Act 2009, the integration of the electronic health record (EHR) with other technology platforms has increased the complexity and necessity of technology downtimes, and the continuity of patient care has become increasingly dependent on an intact EHR. To maintain business continuity and safe patient care during planned or unplanned EHR downtime, it is imperative that organisations have solid downtime and disaster recovery plans. Successful downtime planning will include documenting, with annual reviews, the process for patient care during downtime, as well as an exercise programme that touches all aspects of the downtime process. This paper discusses the experience of a healthcare system based in the US Midwest, which has chosen to exercise part of that process on a quarterly basis, prior to scheduled EHR upgrades. Over the past year of exercises, this healthcare system has collected various data elements in order to identify the education needed and the fine-tuning of the exercise design required to ensure staff competency and patient safety during EHR downtime. The paper describes the process, outcome and the steps the organisation is taking to improve the outcomes of future EHR downtimes.

Improving rapid flood impact assessment: An enhanced multi-sensor approach including a new flood mapping method based on Sentinel-2 data

Rapid flood impact assessment methods need complete and accurate flood maps to provide reliable information for disaster risk management, in particular for emergency response and recovery and reconstruction plans. With the aim of improving the rapid assessment of flood impacts, this work presents a new impact assessment method characterized by an enhanced satellite multi-sensor approach for flood mapping, which improves the characterization of the hazard. This includes a novel flood mapping method based on the new multi-temporal Modified Normalized Difference Water Index (MNDWI) that uses multi-temporal statistics computed on time-series of Sentinel-2 multi-spectral satellite images. The multi-temporal aspect of the MNDWI improves characterization of land cover over time and enhances the temporary flooded areas, which can be extracted through a thresholding technique, allowing the delineation of more precise and complete flood maps. The methodology, if implemented in cloud-based environments such as Google Earth Engine (GEE), is computationally light and robust, allowing the derivation of flood maps in matters of minutes, also for large areas.The flood mapping and impact assessment method has been applied to the seasonal flood occurred in South Sudan in 2020, using Sentinel-1, Sentinel-2 and PlanetScope satellite imagery. Flood impacts were assessed considering damages to buildings, roads, and cropland. The multi-sensor approach estimated an impact of 57.4 million USD (considering a middle-bound scenario), higher than what estimated by using Sentinel-1 data only, and Sentinel-2 data only (respectively 24% and 78% of the estimation resulting from the multi-sensor approach). This work highlights the effectiveness and importance of considering multi-source satellite data for flood mapping in a context of disaster risk management, to better inform disaster response, recovery and reconstruction plans.

Strategi Disaster Recovery dengan Virtualisasi: Backup dan Restore Sistem Operasi di VMware dengan Menggunakan Snapshot

A Disaster Recovery Plan (DRP) is a structured approach that describes how an organization can carry out its operations after an unplanned incident that can result in system failure. Creating strong system resilience requires an IT team with strong experience and understanding as well, and this is the background of this research. This research aims to provide practical guidance in implementing disaster recovery strategies with virtualization, especially the snapshot feature on VMware Workstation to test disaster scenarios and evaluate their recovery effectiveness.

Information Systems Security, Detection and Recovery from Cyber Attacks

Cyber attacks have become a major concern for organizations and individuals a like, as they continue to evolve in sophistication and scale. In response to this growing threat, information systems security has emerged as a critical area of research and practice. The objective of this study is to investigate and analyze various aspects related to information systems security, detection, and recovery from cyber attacks. The research methodology employed in this study encompasses a comprehensive literature review, case studies, and interviews with experts in the field, in order to identify key concepts and best practices in information systems security. The findings of this research reveal that effective measures for protecting information systems from cyber attacks involve a multi-layered approach, comprising of technical, organizational, and human factors. Technical measures involve the implementation of robust security systems, such as firewalls, intrusion detection systems, and encryption protocols, to safeguard against unauthorized access. Furthermore, regular system updates and patches are crucial in mitigating vulnerabilities and preventing potential breaches. Recovery from cyber attacks is a critical aspect that organizations should consider. Prompt and effective response is crucial to minimize the impact of cyber attacks and restore normal operations. This study emphasizes the importance of having a well-defined incident response plan, which includes steps for containment, eradication, and recovery. Additionally, regular backups and disaster recovery plans are essential for data and system restoration. This research highlights the importance of information systems security, detection, and recovery from cyber attacks. It provides insights into the various measures and strategies that organizations can adopt to protect their systems and data. The findings of this research contribute to the existing body of knowledge in the field of information systems security and serve as a valuable resource for practitioners and policymakers. Further research in this area is recommended to address the evolving nature of cyber threats and the advancements in security technologies.

Cybersecurity Considerations in Disaster Recovery Planning

Abstract: This article talks about the important link between cybersecurity and disaster recovery planning, showing how important it is to include strong security measures in disaster recovery plans. It looks at the risks and weaknesses that come up during disaster recovery, like being more open to online threats, having security controls broken, and the chance that vulnerabilities will appear again during the recovery process. Some of the most important things that the piece talks about to lower cyber risks are strong backup and recovery plans, data encryption, access controls, and authentication measures. It also stresses how important it is to have a clear plan for how to handle an event, regular training and education programs for cybersecurity, and ongoing improvement through testing and using new technologies. Case studies and examples from real life are used to show what happens when safety measures aren't up to par and how important it is to plan for all possible disasters.

Reliablity and Security for Fog Computing Systems

Fog computing (FC) is a distributed architecture in which computing resources and services are placed on edge devices closer to data sources. This enables more efficient data processing, shorter latency times, and better performance. Fog computing was shown to be a promising solution for addressing the new computing requirements. However, there are still many challenges to overcome to utilize this new computing paradigm, in particular, reliability and security. Following this need, a systematic literature review was conducted to create a list of requirements. As a result, the following four key requirements were formulated: (1) low latency and response times; (2) scalability and resource management; (3) fault tolerance and redundancy; and (4) privacy and security. Low delay and response can be achieved through edge caching, edge real-time analyses and decision making, and mobile edge computing. Scalability and resource management can be enabled by edge federation, virtualization and containerization, and edge resource discovery and orchestration. Fault tolerance and redundancy can be enabled by backup and recovery mechanisms, data replication strategies, and disaster recovery plans, with a residual number system (RNS) being a promising solution. Data security and data privacy are manifested in strong authentication and authorization mechanisms, access control and authorization management, with fully homomorphic encryption (FHE) and the secret sharing system (SSS) being of particular interest.

Cloud service models, business continuity and disaster recovery plans, and responsibilities

Purpose The purpose of this article is to identify the role of cloud computing services in business continuity and disaster recovery plans and delineate responsibilities for their execution. In recent times, there has been a huge upsurge in the usage of cloud service models such as infrastructure-as-a-service, platform-as-a-service, software-as-a-service and disaster recovery-as-a-service. However, in case of an emergency event or during contract negotiations, a question might arise as to who should be accountable and responsible for the content and execution of recovery plans. The main stakeholders in this scenario are cloud service providers and cloud consumers. Design/methodology/approach After a review of academic articles, standards, guidelines and vendor documentation, a proposal for assigning accountability and responsibility for business continuity and disaster recovery plans is presented, based on the RACI (responsible, accountable, consulted and informed) matrix. In this regard, a critical information infrastructure protection plan, a disaster recovery plan, an information systems contingency plan and a business continuity plan have been elaborated on in the article. Findings RACI matrices are presented for three general cloud service models and for three DRaaS models (managed, assisted and self-service). Accountability and responsibilities depend on the deployed cloud service model and the roles of cloud service providers and cloud consumers. Originality/value The proposed model for accountability and responsibility assignment provides a guideline for the allocation of responsibilities to roles not only during recovery but also during contract negotiations between cloud service providers and cloud consumers. By delving into business continuity and disaster recovery processes and activities, similar yet nuanced RACI matrices should be developed, as presented in this paper. They need to be customised for the specific context.

Hurricane Ian Damage Assessment Using Aerial Imagery and LiDAR: A Case Study of Estero Island, Florida

Remote sensing techniques have emerged as an essential tool for conducting damage assessments and are commonly used to improve disaster recovery planning and community resilience policies. The objective of this study was to use aerial imagery data and LiDAR to identify the hardest hit areas, quantify the extent of damages, and compare pre- and post-storm beach morphology conditions in Estero Island, Florida, relating to Hurricane Ian in 2022. This study identified >2400 structures that were impacted by Hurricane Ian, with 170 structures suffering extensive damage. Clustering of heavily damaged buildings was observed on the northern and central portions of the island, with lower levels of damage clustered on the southern part. Among the ‘severely damaged’ and ‘destroyed’ structures were seven mobile home subdivisions. The total assessed value of the heavily damaged structures was estimated at over USD 200 million. The results also indicated substantial post-storm debris and sand deposition across the entire island. Remote sensing provides advanced techniques that can help prioritize emergency response efforts after catastrophic impacts from a natural disaster.

Partnerships in the recovery planning process: lessons from Puerto Rico after Hurricane Maria and Irma

PurposeTo assess which partnerships were most critical during the recovery planning process following Hurricanes Maria and Irma. We discuss the roles and impact of different types of partners, barriers and facilitators to partnerships and lessons in collaboration during the development of the economic and disaster recovery plan for Puerto Rico.Design/methodology/approachThe Homeland Security Operational Analysis Center (HSOAC) was tasked with assisting the Puerto Rican government with an assessment of damages from Hurricanes Maria and Irma and the development of the Recovery Plan. During the process, a small team compiled and coded a database of meetings with non-HSOAC partners. The team was divided into sector teams that mirrored FEMA’s Recovery Support Functions. Each sector completed two surveys identifying high impact partners and their roles and contributions, as well as barriers and facilitators to partnerships.FindingsA total of 1,382 engagements were recorded across all sectors over seven months. The most frequently identified high impact partners were federal and Puerto Rican governmental organizations partners. NGOs and nonprofits were noted as key partners in obtaining community perspective. Sector teams cited a lack of trust and difficulty identifying partners as barriers to partner engagement. Given the expedited nature of disaster response, establishing partnerships before disasters occur may help facilitate community input. Early networking, increased transparency and defining roles and responsibilities may increase trust and effectiveness among partnerships.Originality/valueTo our knowledge, this is one of the few studies that quantifies and illustrates the partnerships formed and their contributions during recovery planning, and lessons learned.

Kajian Keamanan Sistem Informasi Akademik Menggunakan Framework COBIT 5

This study examines the security of academic information systems using the COBIT 5 Framework. Key issues are uncertainty in protecting student and staff data, the potential for cyberattack vulnerabilities, and non-compliance with international security standards. The goal is to evaluate the security level of the system and suggest improvement recommendations according to COBIT 5 principles. Research methods include Renstar IT policy analysis, system audits, and interviews with IT personnel and related academic communities. Data is analyzed quantitatively to identify weaknesses and opportunities for improvement. The COBIT 5 framework is used as a security assessment framework. The results highlight the need for improvement, including access management, activity monitoring, and continuous improvement plans. Using COBIT 5, substantial measures such as strengthening access controls and developing disaster recovery plans can be identified. The research emphasizes the importance of a structured approach in improving the security of academic information systems, with COBIT 5 as a useful tool. With the right measures, system security can be enhanced to protect the integrity, confidentiality, and availability of critical data for educational institutions. In conclusion, these measures demonstrate how important COBIT 5 implementation is in addressing information security challenges in academic environments.

Investigating information security risk management in Yemeni banks: An CILOS-TOPSIS approach

In today's digital age, the banking sector faces increasing challenges in ensuring operational resilience, protecting customer assets, and maintaining a competitive edge. Prioritizing information security risk management (ISRM) practices is crucial to effectively address these challenges. This paper aims to demonstrate the effectiveness of the multi-criteria decision-making (MCDM) method in evaluating and improving ISRM practices in Yemeni banks. The study employs an integrated CILOS-TOPSIS model, considering two criteria and five sub-criteria, with criteria weights determined using the CILOS method. The results highlight the significance of specific criteria in ISRM, with the existence of a comprehensive business continuity and disaster recovery plan (C2.1) standing out as a top priority (weight: 0.266). Additionally, the frequency of data backups and the presence of an active backup policy (C2.2) and the adequacy of physical security measures (C1.1) are identified as crucial factors (weights: 0.228 and 0.203, respectively). Furthermore, the TOPSIS method is employed to rank 13 banks based on these criteria, revealing the top-performing banks as B10, B4, B13, B1, and B12. Conversely, the 7th, 5th, and 6th ranked banks require attention for improvement. The paper provides comprehensive details on criteria weighting, bank ranking, and recommendations for enhancements. The findings presented in this paper offer valuable insights to decision-makers in the banking sector, enabling them to effectively guide their efforts and allocate resources to areas, controls, and banks that require greater attention.

Assessment of Benilde Associates towards a Dynamic Business Continuity Model in Disruptive Times

Business continuity and disaster recovery planning are comprised of activities that an organization must perform to resume operations in an unexpected event. The De La Salle College of Saint Benilde SMIT research study adopted the Business Continuity Model and identified gaps that will lead to the proposed Dynamic Business Continuity Model in disruptive times. From this problem, the research question is to what extent BCM factors impact levels (depth and breadth) of the Business Continuity Model during disruptive times. Data was collected by surveying Benilde associates in various academic positions and the Office Center. The data collected was treated using Exploratory Factor Analysis and Multiple Regression for causal relationships. DLS CSB SMIT identified gaps and challenges for faculty and staff in several dimensions in the existing Business Continuity Model factors and the ff are: a. Systems/Data Recovery b. Organizational Support c. Employee Engagement d. Forecasting Capacity and among the identified gaps- “Organizational Support ‘ is considered the most significant among the 4 factors. This consists of Student Support Services, Hunan Resource, and Registrar’s Office. To prevent the interruption in DLS CSB SMIT operations and the survival of an organization during disruptive times, Transparency of the BCM Strategy cascaded to Benilde associates, the importance of creating awareness and being prepared for the unexpected. Business Continuity Model is an essential element that should form part of every critical business process within the College. It is imperative to understand the factors that were identified as gaps that the Institution could be faced with and also understand the steps that should be taken to address and manage these risks. This dissertation paper led to the development of a Dynamic Business Continuity Model which is essential to prepare DLS CSB for any disaster or crisis. The Model serves as a guide for all Centers on what they should do in such an event to ensure that the organizations will survive during the fortuitous event and how to restore the Business and Institution to normalcy. This Research study could provide a Business Continuity Model framework for leaders to assess their organization’s capacity from an unexpected disruption and be used by organizational leaders to assign contingency planning responsibilities or hire business continuity and disaster recovery planning professionals. Keywords: Business Continuity, Disruptive, Dynamic Business Model, Systems/Data Recovery, Organizational Support, Employee Engagement, Forecasting Capacity

Participating in Disaster Recovery Planning and Testing to Ensure Data Availability and Continuity in Case of Failures: A Comprehensive Review

Participating in Disaster Recovery Planning and Testing to Ensure Data Availability and Continuity in Case of Failures: A Comprehensive Review

The Risk-Informed Asset-Centric (RIACT) Urban Resilience Enhancement Process: An Outline and Pilot-Case Demonstrator for Earthquake Risk Mitigation in Portuguese Municipalities

This study introduces the Risk-Informed Asset-Centric (RIACT) process, a novel approach aimed at enhancing the safety and resilience of urban infrastructures against natural and man-made disasters. The RIACT method stands out for its comprehensive analysis of potential disruptions to urban areas, encompassing their susceptibility to disasters, vulnerability factors, and recovery capabilities. This study’s primary focus is on Portugal’s 308 municipalities, assessing their preparedness and ability to recover from earthquake events. Methodologically, the study involved employing geographic information system (GIS) mapping to evaluate earthquake risks, combining data on regional risk areas, demographic and economic profiles, and resilience capacities. This approach provides a detailed understanding of each municipality’s strengths and areas in need of improvement, encouraging a collaborative framework for sharing and implementing best practices. The results reveal significant variations in earthquake resilience across different regions, highlighting the need for tailored resilience strategies. Conclusively, the RIACT method not only enhances the resilience of individual municipalities but also contributes to a broader national strategy for urban resilience, offering valuable insights for effective disaster risk management and recovery planning.

Resilient critical infrastructures: An innovative methodological perspective for critical infrastructure (CI) integrated assessment models by inducing digital technologies during multi-hazard incidents

Over the last decade, the notion of community resilience, which encompasses planning for, opposing, absorbing, and quickly recovering from disruptive occurrences, has gained momentum across the world. Critical Infrastructures (CI) are seen as critical to attaining success in today's densely populated countries. Such infrastructures must be robust in the face of multi-hazard catastrophes by implementing appropriate disaster management and recovery plans. Given these facts, it is critical to establish a new methodological perspective with an integrated system for effective disaster management of CI, as well as an intelligent application that will aid in the construction of more resilient and sustainable cities and communities. This perspective proposes a holistic gaming scenario application for assessing the vulnerability and accessibility of critical infrastructures during multi-hazard events, with a primary focus on conducting an integrated assessment for critical infrastructures and their assets. Mainly, the perspective includes a holistic gaming scenario application that will aid in accurately quantifying geographical spatial information and integrating big data into predictive and prescriptive management tools using virtual reality.•Conducting Integrated Assessment Models for evaluating vulnerability of Critical Infrastructures.•Inducing Digital Technologies during Multi-Hazard Incidents for improving Natural hazard assessment models.•Developing an open-world gaming scenario that is considered with high visual motion pictures and scenes.

Disaster recovery plan implementation evaluation model at the corporation

The application of information technology in addition to making internal business processes more effective and efficient, is also to improve customer service. This role is important for companies to maintain the sustainability of information systems as a strategic tool for competitive advantage so system availability is absolutely essential. Research related to the Disaster Recovery Plan (DRP) needs to be carried out to see the readiness of a corporation to build a backup system in different places and locations. By using the method of factor analysis and regression analysis to form an evaluation model, it will obtain an overview of what factors must be considered and what the current conditions are. The results of the study show that there are Core Technical DRP, Organizational Preparation, and Costing factors which are the main variables in supporting DRP readiness. The conclusion from this study, through these three new factors a mathematical model can be built as a reference for improving DRP implementation in corporations.

Integrating Statistical Simulation and Optimization for Redundancy Allocation in Smart Grid Infrastructure

It is a critical issue to allocate redundancy to critical smart grid infrastructure for disaster recovery planning. In this study, a framework to combine statistical prediction methods and optimization models for the optimal redundancy allocation problem is presented. First, statistical simulation methods to identify critical nodes of very large-scale smart grid infrastructure based on the topological features of embedding networks are developed, and then a linear integer programming model based on generalized assignment problem (GAP) for the redundancy allocation of critical nodes in smart grid infrastructure is presented. This paper aims to contribute to the field by employing a general redundancy allocation problem (GRAP) model from high-order nonlinear to linear model transformation. The model is specifically implemented in the context of smart grid infrastructure. The innovative linear integer programming model proposed in this paper capitalizes on the logarithmic multiplication property to reframe the inherently nonlinear resource allocation problem (RAP) into a linearly separable function. This reformulation markedly streamlines the problem, enhancing its suitability for efficient and effective solutions. The findings demonstrate that the combined approach of statistical simulation and optimization effectively addresses the size limitations inherent in a sole optimization approach. Notably, the optimal solutions for redundancy allocation in large grid systems highlight that the cost of redundancy is only a fraction of the economic losses incurred due to weather-related outages.