Implementation of Feature Selection and Data Split using Brute Force to Improve Accuracy

This study seeks to classify data using feature selection and brute force. The dataset contains irrelevant characteristics, therefore feature selection influences computing time and the classification model. UCI's YouTube Spam Collection was used for testing. This dataset contains five datasets with 1,956 legitimate messages from five popular videos (Shakira, Katy Perry, Psy, Eminem, and LMFAO). Using weight information gain, the feature selection technique finds the best attributes. The dataset will then be separated into two parts: training with a 70:30 ratio and testing with a 30:70 ratio. Comparing using C4.5 and Nave Bayes. The FS+BF+C4.5 approach has an accuracy of 69.90%, 63.37%, 98.32%, 50.89%, and 91.75 for five videos (Psy, Katy Perry, LMFAO, Eminem and Shakira). Standard C4.5 technique accuracy is 66.99%, 59.41%, 95.80%, 50.89%, and 88.66%. Naive Bayes accuracy is 61.17, 51.49, 89.08, 50.00, and 79.38. FS+BF+C4.5 obtains an overall average accuracy of 74.85%, 2.5% and 8.6% higher than C4.5 and Naive Bayes (72.35 percent and 66.22 percent). Using feature selection and brute force with the C4.5 approach can reduce classification error compared to the normal C4.5 and Naive Bayes methods

Guest editorial: Insider threat solutions - moving from concept to reality

As society has embraced technology and systems to promote services, trade and ubiquitous communication, it has also inadvertently exposed itself to a plethora of security risks. One of the most significant of these risks is that of insider threat, where privileged insiders (be they employees or trusted third-parties) within an enterprise, intentionally or inadvertently cause harm their organisations. While the topic of insider threat has been examined and researched for decades, the problem still persists, and some would even argue that it is becoming worse. Could this be the result of a disconnect between approaches and solutions being researched and those that are (or can be) actually implemented

Public Health Care Cybersecurity Challenges and Solutions for Cyber-Attacks on Critical Health Infrastructure

The opportunities for public health care and safety are especially high, and the healthcare industry is particularly susceptible to cybersecurity threats. Cybercriminals find healthcare facilities appealing due to their size, reliance on technology, handling of sensitive data, and susceptibility to certain disruptions. The Internet of Things, or IoT, has gained a lot of traction in recent years due to its many benefits, which include reduced costs, time savings, enhanced user comfort, and effective use of electricity. The most crucial component of the cyber-physical system is the low-capacity sensor node. These components are diverse in nature and can function as hosts or clients on the internet by connecting via a wireless network. The well-known security features found in desktop computers are inoperable on these systems because of resource constraints such low processor power, low storage capacity, and low energy backup. The suggested study uses SNMP in conjunction with an ANN classifier and secure data transmission to detect cybersecurity attacks on healthcare data and medical devices. The vulnerabilities in the security of IoT-centric systems give rise to privacy concerns that impact the use of smart environment applications

The Impact of Service Distinction on Durable Competitive Advantage: An Investigation in Private Hospital Outpatient Units During the COVID-19 Pandemic

The COVID-19 pandemic has compelled hospitals to sustain their competitive edge in delivering healthcare services, with service differentiation being a key factor in maintaining this advantage. This research aims to evaluate how service differentiation impacts a hospital\u27s ability to maintain a sustainable competitive advantage during the COVID-19 pandemic. This research, conducted in 2020, is a quantitative descriptive study involving 204 outpatients at Aisyiyah Bojonegoro Hospital. The survey was carried out online using Google Forms and achieved a response rate of 31.2%. The data were analyzed using linear regression. The findings indicate that service differentiation positively influences sustainable competitive advantage (p = 0.00). According to the study, during the COVID-19 pandemic, patients tend to prefer hospitals that offer distinct services

Revolutionizing WBAN communication for public health: Effective Optimization strategy-driven health assessment

This study explores the optimization procedures that are critical to enhancing WBAN communication efficacy in an environment of public health initiatives. In order to observe someone\u27s physiological characteristics continuously and non-invasively, wireless body area networks (WBANs), are an essential piece of innovation for distant health observation. The WBAN individual nodes, yet, might relocate and lose reception from a distant base station over time. Thus, an effective inter-WBAN interaction approach is required to address this issue. In order to lower cost associated with networks and maximize cluster lifespan towards the network\u27s effectiveness, this research develops a clustering-driven routing approach that uses cluster head serving as a gateway. For efficient cluster head selection, a novel customized chicken swarm optimization (CCSO) technique was introduced. Various parameter adjustments are made in multiple trials to verify the suggested approach effectiveness. The research conduct comprehensive comparison analysis of suggested and existing algorithms, several tests are conducted. The results show that the approach technique can increase the effectiveness of WBAN engagement and create clusters more quickly than the other methods in the framework of public health initiatives

Levels of Oxytocin Hormone During Breastfeeding

Background: The rate of successful early breastfeeding in new mothers remains low. Various factors influence the lactation process, including the levels of prolactin and oxytocin hormones in the body. Prolactin and oxytocin are crucial for lactation, with oxytocin being released in response to nipple stimulation when the baby suckles, facilitating milk ejection. Purpose: It is the purpose of this research to determine the levels of the hormone oxytocin in postpartum moms who are nursing their infants entirely. Methods: A quantitative cross-sectional design was used for the research project. It involved measuring oxytocin hormone levels during the third day after birth in postpartum women by the collection of blood samples and the subsequent analysis of those samples using the ELISA technique. Researchers also assessed breastfeeding success using observation sheets. The participants included 30 postpartum mothers who had undergone uncomplicated cesarean deliveries. Statistical tests were used to analyze the data on oxytocin levels and breastfeeding success. Results: A total of 53% of postpartum mothers were able to breastfeed successfully without encountering significant issues. The average oxytocin level in these mothers on the third day postpartum was found to be 786.8 pg/ml. Conclusion: The significant factor was found to be 0.002 after the data analysis was performed, indicating a significant relationship between oxytocin hormone levels and breastfeeding

Internet of Drones (IoD): Threats, Vulnerability, and Security Perspectives

The development of the Internet of Drones (IoD) becomes vital because of a proliferation of drone-based civilian or military applications. The IoD based technological revolution upgrades the current Internet environment into a more pervasive and ubiquitous world. IoD is capable of enhancing the state-of-the-art for drones while leveraging services from the existing cellular networks. Irrespective to a vast domain and range of applications, IoD is vulnerable to malicious attacks over open-air radio space. Due to increasing threats and attacks, there has been a lot of attention on deploying security measures for IoD networks. In this paper, critical threats and vulnerabilities of IoD are presented. Moreover, taxonomy is created to classify attacks based on the threats and vulnerabilities associated with the networking of drone and their incorporation in the existing cellular setups. In addition, this article summarizes the challenges and research directions to be followed for the security of IoD.Comment: 13 pages, 3 Figures, 1 Table, The 3rd International Symposium on Mobile Internet Security (MobiSec'18), Auguest 29-September 1, 2018, Cebu, Philippines, Article No. 37, pp. 1-1

A novel strategic trajectory-based protocol for enhancing efficiency in wireless sensor networks

This research presents a comprehensive approach to enhance the efficiency and performance of Wireless Sensor Networks (WSNs) by addressing critical challenges, such as race conditions, reservation problems, and redundant data. A novel protocol combining Self-Adaptive Redundancy Elimination Clustering and Distributed Load Bandwidth Management is proposed to mitigate these challenges. The work intelligently extracts transmission hops and any-cast transmission features from diversity traffic information obtained through trace files, to eliminate nodes harboring redundant data. To optimize network organization, the number of clusters is dynamically adjusted according to the node density using the affinity propagation technique. Furthermore, load balancing is achieved by reallocating available bandwidth through bandwidth re-segmentation. The research also delves into the Proposed Network Infrastructure and Channel Coordination. The architecture encompasses cooperative clustering of nodes, strategic access point selection, data compression, and channel migration. By fostering collaboration among nodes within clusters, selecting access points judiciously, and employing efficient data compression techniques, the network overall efficiency is significantly improved. Channel migration strategies further bolster the network agility and responsiveness. The integration of Channel Sensing enriches the approach by collecting channel state information, enriched with spatial and temporal node information. This added insight empowers the network to make more informed decisions regarding channel allocation and coordination contributing to reduced interference and optimized data transmission. As a result of the work, the proposed methodology achieves remarkable results, including an average Packet Delivery Ratio of 99.1 % and an average reduction of packet loss by 4.3 % compared to existing studies. Additionally, the proposed protocol exhibits an average throughput improvement of 4.7 % and reduces average network delay to 52 milliseconds highlighting its significant contributions to the enhancement of WSN performance