Ultra-Dense Request Impact on Cluster-Based Web Server Performance

It's been clearer over the last two decades that computer science plays a crucial role in the growth of every company. With each passing cycle, the IT industry blossoms a brand-new subfield. The Internet of Things (IoT) refers to the idea of connecting any device to the Internet in order to interact with the consumer and convert it into an intelligent device; this is a relatively new concept in the realm of information technology (IT) and the Internet, but it is gaining popularity and importance in people's daily lives. The Internet of Things is predicted to play a pivotal role in the development of business IT infrastructure. With the help of IoT, we can link billions of smart gadgets that can talk to one another in an automated fashion. One of the most rapidly expanding fields in computer history, with an expected 50 billion devices by the end of 2020. Security techniques, such as encryption, authentication, access control, network security, and application security, are rendered useless when applied to Internet of Things (IoT) devices because of these inherent weaknesses. The Internet of Things (IoT) has attracted the attention of many academics and industry leaders, who have published studies and made statements on the significance of IoT architectural layers for corporate systems (ESs). This literature study included a wide variety of studies that implemented and developed IoT technology in several human domains, including healthcare, smart homes and cities, assisted charities, and monitoring systems. The article also detailed the computers and programs that facilitated each study. Plus, the reliable algorithm used in the research articles' tests and analyses of data. Lastly, drawing parallels between these publications helps to provide insight on the difficulties and possibilities facing potential IoT impact researchers in the industrial sector.

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Internet of Things Impact on Web Technology and Enterprise Systems

Yazdeen¹,

Qashi²,

Malallah³

et al. 2023

“…Many cybercrimes such as spam, theft, cyber terrorism, and phishing are commonly carried out. New cybercrime and very common today are among this phishing [3,4]. Phishing is an attempt at deception to gain confidential user information.…”

Section: Introductionmentioning

confidence: 99%

“…We will check the URL and settle on this website to monitor this. The selection of established phishing sites to find unknown phishing sites is one way to identify phishing [36][37][38]. The study of web functionality is another means of finding out the bogus websites.…”

Section: Introductionmentioning

confidence: 99%

Web Phishing Detection Using Web Crawling, Cloud Infrastructure and Deep Learning Framework

Abdulrahman¹,

Ahmed²,

Rashid³

et al. 2023

The pandemic of COVID-19 obliges citizens to follow the “work from home “scheme. The Internet is also a powerful channel for social connections. The huge dependency of people on digital media opens doors to fraud. Phishing is a form of cybercrime that is used to rob users of passwords from online banking, e-commerce, online schools, digital markets, and others. Phishers create bogus websites like the original and deliver users spam mails. When an online user visits fake web pages via spam, phishers steal their credentials. As a result, it is important to identify these forms of fraudulent websites until they do any harm to victims. Inspired by the ever-changing existence of phishing websites. This paper reviews the work on Phishing attack detection and aims to examine techniques that mainly detect and help in preventing phishing attacks rather than mitigating them. Here we offered a general overview of the most effective phishing attack detection strategies focused on deep learning.

“…This process is carried out on a group of things that have been gathered together [11][12][13]. Clustering is a technique that can be used to organize data structures into a number of groups that are incompatible with one another and are referred to collectively as clusters [14][15][16]. Clustering is a strategy that may be employed.…”

Section: Introductionmentioning

confidence: 99%

Document Clustering in the Age of Big Data: Incorporating Semantic Information for Improved Results

Haji¹,

Al-Zebari²,

Şengür³

et al. 2023

There has been a meteoric rise in the total amount of digital texts as a direct result of the proliferation of internet access. As a direct result of this, document clustering has evolved into a crucial method that must be used in order to successfully extract relevant information from big document collections. When employing the document clustering approach, documents are automatically sorted into groups whose members have a high degree of similarity to one another. These groups are created by applying the document clustering technique. Because they do not take into account the semantic linkages that exist between the texts, traditional clustering approaches are unable to provide an acceptable description of a collection of texts. This is because traditional clustering techniques. Document clusters, in which texts are ordered according to their meaning rather than their use of keywords, have been extensively utilized as a means of overcoming these challenges as a result of the incorporation of semantic information. This has been possible as a result of the fact that document clusters can group together related texts. In this investigation, we looked at a total of 27 distinct papers that were published over the previous five years and categorized the documents based on the semantic similarities that existed between the various pieces. A detailed literature evaluation is included to each and every one of the publications that were selected for further consideration. Comparative research is carried out on a wide variety of evaluation strategies, including as algorithms, similarity metrics, instruments, and processes. Following that, there is a drawn-out discussion that analyzes the similarities and differences between the activities.