Navigating the Digital Frontier: A Comprehensive Analysis of Cybersecurity and Information Security in the Modern Era
Exploring Natural Language Processing Chatbots and Phishing Website Detection: A Literature Perspective
Survey on ATM Security Enhancement using Encryption Technology
A Growth of Artificial Intelligence in Crime Detection usages in Law Enforcement
Comparative Analysis of Deep Learning Models for Financial Fraud Detection
Exploring Natural Language Processing Chatbots and Phishing Website Detection: A Literature Perspective
Impact of Artificial Intelligence on Cybersecurity: A Case of Internet of Things
A Growth of Artificial Intelligence in Crime Detection usages in Law Enforcement
Comparative Analysis of Deep Learning Models for Financial Fraud Detection
An Extensive Overview on Dark Web
Mobile Ad-Hoc Networks (MANETs) are recognised as a key emerging technology for use whenever cellular communications are either infeasible, inefficient, or cost-ineffective. MANETS are composed of nodes that are arranged in a self-organizing manner, without a central device like a switch or router. The nodes communicate with each other over wireless links and cooperate in a distributed fashion. Smartphones are the most ideal network nodes in many scenarios where traditional networks are unavailable, but building a secure network with them is not easy. This paper extensively uses the existing possibilities to build a secure MANET. The designed MANET has been built on an NS3 simulator, with the base protocol being Ad-hoc On-demand Distance Vector (AODV) and message encryption is done by using RSA Algorithm. The Secure AODV protocol extension is implemented using the RSA extension.
In the modern era, the rapid use of the internet has led to reports of cybercrimes. The number of cybercrimes is constantly increasing. The purpose of this paper is to identify the root causes of cybercrime and find insights that can be used by the administration to take fruitful decisions to overcome cybercrime offenses. It has collected data related to the registered cybercrime cases in various Indian states on different parameters for the years 2016 to 2019. The preprocessing was applied to individual datasets, and a common data set was prepared. Data analysis using Power BI (business intelligence) and Microsoft (MS) Excel tools was performed for the Indian states, and its impact was analyzed through year-wise analysis. The outcome of this paper can be utilized by the Indian administration, cyber experts, working professionals, and users to take care of the affecting factors and limit cybercrimes.
At present, millions of people use mobile phones and computers in their daily lives. They are using these devices for online shopping, banking transactions, online gaming, share market, etc. Sometimes people have no knowledge of cybercrime and are easy victims of cyber-related fraud. This paper discusses different types of cybercrime, such as identity theft, cyberstalking, cyberbullying, financial fraud, and the importance of cybersecurity techniques including risk management, internal audit, and the benefits of a cybersecurity audit. The conclusion emphasizes the importance of expanding cybersecurity measures to protect against evolving cyber threats.
This paper focuses on analyzing the performance of various encryption algorithms, namely RSA, ECC, and DSA, in terms of encrypting and decrypting sensitive data. Encryption is crucial for ensuring the security of data, and there are two types of encryption algorithms: Symmetric key and Asymmetric-key encryption. RSA is highly secure but has high computation time, whereas ECC provides equivalent security with lower computing power and battery usage. The study compares the implementation and analysis of DES, 3DES, AES, RSA, ECC, and DSA, highlighting their strengths and weaknesses. The paper aims to provide a comprehensive comparison of these cryptographic techniques, including their performances, to assist in selecting the most appropriate algorithm for specific applications.
The dependence of humans on computers is increasing in today's era of technology. All transactions, as well as digital data transformations, are done with the help of the network, so third parties or intruders can attack the network to access data and use it in the wrong way. Organizations and individuals use the network for their work. Due to the easy availability of the internet, there is always a risk of information falling into the wrong hands. This paper presents a detailed study of networking attacks and security algorithms, as well as an analysis of various viable network attack observation tools to detect attacks. The algorithms discussed include Symmetric Key Algorithm, Asymmetric Key Algorithm, and their respective types.
The survey focuses on the role of Artificial Intelligence (AI) in enhancing cyber security, as well as the challenges that come with it. AI has become a crucial component in addressing the increasing sophistication of cyber-attacks and malware. Implementing intelligent cyber security measures, especially in support, situation awareness, and data management domains, is necessary for optimal effectiveness. Professional system technology is a promising technology in areas where neural networks may not be the most suitable technology. While the timeline for universal computing advances is unclear, it is important to note that attackers can potentially use such technology as soon as it becomes available. Therefore, advancements in machine learning, knowledge understanding, illustration, and handling can significantly enhance a system's capacity for cyber security. This article provides a comprehensive review of AI and computer applications in cyber security and offers recommendations for improving security system intelligence.
