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Ransomware
Full text linkThis paper explores ransomware and it’s effect on organizations with the intent of uncovering the ideal way for an organization to handle an attack. It begins with a short introduction of ransomware and it’s similarities and differences to traditional crimes, such as theft. Then the paper explains the two main categories of ransomware – crypto-ransomware and locker ransomware – and how most variants are derived from these categories. It includes a description of each category and the typical ways an organization would encounter it. The paper examines the emergence of ransomware-as-a-service (RaaS) and how it’s divide-and-conquer nature allows cybercriminals to specialize in either malware development or network penetration. In addition, RaaS has enabled criminals with low-level programming skills to partake in and profit from ransomware. It discusses the most common RaaS business models and some of the most prolific and dangerous variants. The paper analyzes cryptocurrency’s role in ransomware attacks and how it perpetuates the anonymity of the cybercriminals. It also investigates the evolution of ransomware from it’s origin until 2020 and the different variants that have emerged. Then the paper shifts to focus on what can be done to combat ransomware. It looks at preventative measures, reactive measures, and mitigation. Finally, the paper concludes with the best way for an organization to handle a ransomware attack
Effectiveness of an Instructional Program on Decreasing Fall Incidents in Geriatric Patients with Psychiatric Disorders
Full text linkFalls occur in 25% of older adults, resulting in over 8 million fatal and nonfatal injuries. In addition to the human suffering, associated medical and legal costs amount to over 50 billion dollars a year. This study examines the impact on fall rates of an evidence-based fall prevention program provided to a multidisciplinary staff on a psycho geriatric unit in Philadelphia, Pennsylvania. Staff knowledge of effective fall prevention interventions was measured before and after their participation in an evidence-based instructional workshop provided by the Project Director using the Falls Prevention Knowledge Test by Dykes et al. (2019). While there were not statistically significant differences in levels of knowledge about fall prevention, the actual number of falls decreased. Implications of findings for discipline-specific and future fall prevention efforts are discussed
Spacecraft tracking control and synchronization: An assessment of conventional, unconventional, and combined methods
Full text linkArtificial intelligence (AI) promises breakthroughs in space operations, from mission design planning to satellite data processing and navigation systems. Advances in AI and space transportation have enabled AI technologies in spacecraft tracking control and synchronization. This study assesses and evaluates three alternative spacecraft tracking control and synchronization (TCS) approaches, including non-AI TCS methods, AI TCS methods, and combined TCS methods. The study proposes a hybrid model, including a new model for defining weight coefficients and interval type-2 fuzzy sets based combined compromised solution (IT2FSs-CoCoSo) to solve the spacecraft TCS problem. A new methodology is used to calculate the weight coefficients of criteria, while IT2FSs-CoCoSo is applied to rank the prioritization of TCS methods. A comparative analysis is conducted to demonstrate the performance of the proposed hybrid model. We present a case study to illustrate the applicability and exhibit the efficacy of the proposed method for prioritizing the alternative TCS approaches based on ten different sub-criteria, grouped under three main aspects, including complexity aspects, operational aspects, and efficiency aspects. AI and non-AI methods combined are the most advantageous alternative, whereas non-AI methods are the least advantageous, according to the findings of this study
Esports gender diversity: A leisure constraints perspective
No full textEsports are a leading form of digital leisure. Esports offer salient career opportunities, ranging from professional players to roles in science, technology, engineering, and mathematics, fields where women have been traditionally underrepresented. Yet women are also underrepresented at the professional level in esports. This is particularly problematic as high-level competitors provide visible representation to inspire others, foregoing opportunities to leverage esports broad appeal. We employ the hierarchical model of leisure constraints to understand what limits individuals from engaging in leisurely pursuits. The purpose of our study is to compare leisure constraints to esports participation by gender. Data were collected from male and female esports participants (N = 402) via online survey. Results show that female esports participants had significantly higher interpersonal and intrapersonal constraints. This likely influences their desire to work in esports and related fields, thereby partially explaining the lack of female representation in the upper echelons of esports
An Evidence-Based Teaching Plan for an Anesthesia Crisis Resource Management Simulation Targeting Malignant Hyperthermia
Full text linkMost medical errors in health care are preventable and result from lack of communication and teamwork among health care workers. Despite health care providers’ training on preventing medical errors and managing medical crises, patient care services may be compromised and result in patient harm when teamwork and communication decrease among clinicians. Anesthesia Crisis Resource Management (ACRM) was designed to help anesthesia providers effectively manage crises by working in multidisciplinary teams to improve and develop both teamwork and technical skills. The purpose of the Doctor of Nursing Practice project is to design an evidence-based teaching plan for a ACRM simulation targeting malignant hyperthermia (MH) to increase non-technical skills of staff in the operating room. MH is a rare anesthesia crisis that can prove fatal if not properly recognized and treated. The teaching plan for the ACRM simulation will be designed with the goal of being utilized in the operating rooms to enhance teamwork and communication which is critical when responding to an MH crisis
Esports in Emerging Markets: A Balanced Scorecard Approach to LAN Gaming Centers in Iran
No full textEsports, competitive video gaming competitions, are becoming increasingly popular worldwide, with their growth in emerging markets contingent on local area network (LAN) gaming centers. LAN gaming centers are integral in emerging economies as they provide access to gaming technology and infrastructure that may be otherwise unavailable. Given their importance, the purpose of our study is to identify characteristics relevant to LAN gaming center operations within the context of an emerging market. We conducted a two-phase, multimethod analysis of LAN gaming centers in Iran, an emerging yet dynamic market. In the first phase, we used a balanced scorecard (BSC) approach to identify business factors salient to LAN gaming center operations. In the second phase, we collected data from LAN gaming center consumers (N = 330) to rank the factors by importance using a multi attribute decision-making (MADM) model. We found that business factors relevant to LAN gaming centers operations include: offering a variety of services, providing attractive and modern facilities, employing sports marketing methods, monitoring competition, and developing multiple streams of revenue. via the BSC, our research offers strategic recommendations for LAN gaming centers. LAN gaming centers provide access to modern gaming technology and help consumers overcome technological limitations by providing a physical space for esports. LAN gaming centers help create a sense of community and social connection for players and fans alike and facilitate how consumers in emerging markets connect with the global esports community
A novel median-based optimization model for eco-efficiency assessment in data envelopment analysis
No full textEconomic-environmental performance or eco-efficiency is a topic of great interest due to the “green movement.” Data Envelopment Analysis (DEA) is a non-parametric method for measuring the eco-efficiencies in comparable Decision-Making Units (DMUs) under various technology assumptions, e.g., constant or variable returns to scale. In the case of variable returns to scale, the returns to scale (RTS) values show whether the DMUs under consideration have the correct scale size or can be improved by upsizing or downsizing. However, sometimes the RTS values for some DMUs are unusually high or low and hence useless in practice. The RTS-mavericks test is devised to propose RTS bounds to fix this flaw. However, these bounds can be ineffective in practice. Even if this flaw is rectified, it needs to be clarified how the concept of RTS-mavericks influences eco-efficiency analysis. For the case of a single technology and a combination of two technologies (a so-called pollution-generating technology), we derive RTS equations and develop new median-based optimization problems to correct this flaw and show that the new concept can lead to non-convex technologies. We also demonstrate the applicability and exhibit the efficacy of the proposed model in the context of eco-efficiency analysis in the European Union
Data Poisoning: A New Threat to Artificial Intelligence
Full text linkArtificial Intelligence (AI) adoption is rapidly being deployed in a number of fields, from banking and finance to healthcare, robotics, transportation, military, e-commerce and social networks. Grand View Research estimates that the global AI market was worth 93.5 billion in 2021 and that it will increase at a compound annual growth rate (CAGR) of 38.1% from 2022 to 2030. According to a 2020 MIT Sloan Management survey, 87% of multinational corporations believe that AI technology will provide a competitive edge. Artificial Intelligence relies heavily on datasets to train its models. The more data, the better it learns and predicts. However, the downside to AI is data, data that can be manipulated or poisoned. A new type of threat is emerging, and that threat is data poisoning. Data Poisoning is challenging and time consuming to spot and when it is discovered, the damage is already extensive. Unlike traditional attack that is caused by errors found in code, this new threat is attacking the AI training data used in its algorithm. Data is now being weaponized. It requires minimal effort but can cause substantial damages. It only takes 1-3% of data to be poisoned to severely diminish an AI’s ability to produce accurate predictions
Going Dark and Encryption
Full text linkLaw officers across the country and around the world are being left in the technological dust by their criminal counterparts. They have no problem obtaining evidence, however they run into issues accessing this information due to various encryption techniques being used. This phenomenon has been dubbed the “Going Dark” problem. James Comey describes the Going Dark problem as, “We have the legal authority to intercept and access communications and information pursuant to court order, but we often lack the technical ability to do so” (Comey, 2014).
The Going Dark problem is a relatively new problem facing law enforcement officers (LEOs) that has roots going back to the Crypto Wars of the early 1990s. At its core, the Going Dark problem is really just an issue of how to attack encrypted data. Data is either at rest, or in motion, and can be attacked several different ways depending on which state it is in. Recently, the FBI has found some success using a man-in-the-middle attack on criminals’ cell phones, but since they sold the cell phones themselves, they were able to attack data both at rest and in motion. Today, LEOs are trying to solve the Going Dark problem by attacking encrypted data using a variety of tactics, and by trying to amend the Communications Assistance to Law Enforcement Act (CALEA) to include email and social media