Analysis of Traditional Web Security Solutions and Proposal of a Web Attacks Cognitive Patterns Classifier Architecture

2018 ◽  
pp. 186-198
Author(s):  
Carlos Martínez Santander ◽  
Sang Guun Yoo ◽  
Hugo Oswaldo Moreno
Keyword(s):  
Web Security ◽  
Web Attacks ◽  
Cognitive Patterns

scholarly journals Enhancing Security of Data Exchange through Block Chain Technology

2020 ◽  
Vol 9 (4) ◽  
pp. 266-269
Keyword(s):  
Cyber Security ◽  
Information Exchange ◽  
Web Application ◽  
Data Exchange ◽  
Web Applications ◽  
Web Security ◽  
The Internet ◽  
Plain Text ◽  
Web Attacks ◽  
Data Transferring

Cyber security refers to a set of well-defined techniques used to protect the integrity of networks. It is used to protect vital data of customers and to restrict unauthorised access. In the era of E-Commerce, the demand for websites, web application increasing exponentially day by day. Web security is currently a significant issue for Internet enabled organization. Using websites, managing information through digital way. HTTP is a Hyper Text Transfer Protocol. It is used to transfer information over the internet. HTTP is most popular protocol widely used in web applications and allowed by internet firewalls, operating systems. HTTP is an unsecured information exchange protocol. Integrity is not there, so someone can easily alter with the content. In the internet data transferring over HTTP connection in plain text, this opening new loop hole to attackers to read every data sent over HTTP connection to web or webserver. Http is insecure as there is no encryption methods for it. So, it subjected towards the web attacks such as Man in the middle, cross site scripting, SQL Injection, click jacking, Broken authentication and session management attacks can occur. HTTP interaction with TCP is bad, causes the problems with performances and server scalability. In our proposed system, document which is used by more than one user and if there is in updation of the content user who is modifying the content of thier shared document must take their concern from other users. The process which is being used to authenticate the modifications of content of shared document is done with the help of shared key unless or until all users send the shared keys of each user the document will not be decrypted and hence further the changes in the document will not be possible.

Experiential Learning of Networking Technologies: Understanding Web Security

2018 ◽  
Author(s):  
Ram P. Rustagi ◽  
Viraj Kumar
Keyword(s):  
Experiential Learning ◽  
Web Security ◽  
Web Based ◽  
Security Issues ◽  
Hands On ◽  
Networking Technologies

With the rapid increase in the volume of e-commerce, the security of web-based transactions is of increasing concern. A widespread but dangerously incorrect belief among web users is that all security issues are taken care of when a website uses HTTPS (secure HTTP). While HTTPS does provide security, websites are often developed and deployed in ways that make them and their users vulnerable to hackers. In this article we explore some of these vulnerabilities. We first introduce the key ideas and then provide several experiential learning exercises so that readers can understand the challenges and possible solutions to them in a hands-on manner.

scholarly journals Security of Things Intrusion Detection System for Smart Healthcare

Electronics ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 1375
Author(s):  
Celestine Iwendi ◽  
Joseph Henry Anajemba ◽  
Cresantus Biamba ◽  
Desire Ngabo
Keyword(s):  
Genetic Algorithm ◽  
Intrusion Detection ◽  
False Alarm ◽  
False Alarm Rate ◽  
Detection Rate ◽  
Web Security ◽  
Intrusion Detection Systems ◽  
High Detection Rate ◽  
Detection Systems ◽  
Smart Healthcare

Web security plays a very crucial role in the Security of Things (SoT) paradigm for smart healthcare and will continue to be impactful in medical infrastructures in the near future. This paper addressed a key component of security-intrusion detection systems due to the number of web security attacks, which have increased dramatically in recent years in healthcare, as well as the privacy issues. Various intrusion-detection systems have been proposed in different works to detect cyber threats in smart healthcare and to identify network-based attacks and privacy violations. This study was carried out as a result of the limitations of the intrusion detection systems in responding to attacks and challenges and in implementing privacy control and attacks in the smart healthcare industry. The research proposed a machine learning support system that combined a Random Forest (RF) and a genetic algorithm: a feature optimization method that built new intrusion detection systems with a high detection rate and a more accurate false alarm rate. To optimize the functionality of our approach, a weighted genetic algorithm and RF were combined to generate the best subset of functionality that achieved a high detection rate and a low false alarm rate. This study used the NSL-KDD dataset to simultaneously classify RF, Naive Bayes (NB) and logistic regression classifiers for machine learning. The results confirmed the importance of optimizing functionality, which gave better results in terms of the false alarm rate, precision, detection rate, recall and F1 metrics. The combination of our genetic algorithm and RF models achieved a detection rate of 98.81% and a false alarm rate of 0.8%. This research raised awareness of privacy and authentication in the smart healthcare domain, wireless communications and privacy control and developed the necessary intelligent and efficient web system. Furthermore, the proposed algorithm was applied to examine the F1-score and precisionperformance as compared to the NSL-KDD and CSE-CIC-IDS2018 datasets using different scaling factors. The results showed that the proposed GA was greatly optimized, for which the average precision was optimized by 5.65% and the average F1-score by 8.2%.

scholarly journals Impulsiveness and Cognitive Patterns. Understanding the Perfectionistic Responses in Spanish Competitive Junior Athletes

2019 ◽  
Vol 10 ◽  
Author(s):  
Juan González-Hernández ◽  
Concepción Capilla Díaz ◽  
Manuel Gómez-López
Keyword(s):  
Junior Athletes ◽  
Cognitive Patterns
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