Emerging Cybersecurity Threats in the Eye of E-Governance in the Current Era

Introduction

As digital changes and hyper-convergence give a chance to vulnerabilities, attacks, attacks, and failures, a cyber-flexibility approach is necessary for the smooth running of a business quickly. An effective approach helps businesses to decrease risk, reputational damages, and financial influence, and status losses. Cyber security has made significant progress in recent years to meet the changes that are taking place within cyberspace. Cyber security is to be said that any organization can utilize to shelter its data and products contained within cyberspace. A primary object of this research to identify challenges is to cyber security and governance issues, using machine learning techniques such as culture, risk management awareness, and developing threats. The researcher has reviewed 33 articles and other associated articles and chapters (Liu et al., 2020). The activities of criminal networks (CN), which are sneaky and secretive, can create difficulties by criminal network analysis due to lack of comprehensive data sets. Collected criminal data is insufficient and unreliable, which is echoed physically in the criminal network in the procedure of disappeared nodes and association. Criminal networks are generally studied by social network analysis models. MLTs mostly trust the metrics of SNA models in the emergence of secreted. Though supervised learning generally needs the obtainability of a large dataset, training link prediction models to get all-out routine levels. Hence, the author has conducted experiments to discover the application of deep reinforcement (DRL) in emerging CN secreted links production models from the rebuilding of corrupted CN datasets (Lim et al., 2019). The researchers have explored from their studies that great growth in research in the part of cyber security to sustenance cyber applications to evade crucial security threats handled by these applications. The main object of this research is to analyse and identify the usual cyber security weaknesses. After a comprehensive analysis of the chosen studies, the author has identified the key security weaknesses and their rate of incidence. There are synthesizes and studies have been done by available publication data, important targeted organisations and applications. The result of this research shows that the security measures mentioned so far usually only target security and find out the solutions provided in these studies essential for more experimental authentication and actual implementation Figure-1 (Humayun et al., 2020). One of the current tendencies of mobile and networking technology is mobile cloud computing (MCC) that is giving rich computational services in clouds and storing resources to mobile users. MCC applications give a variety of services to users and location-based services (LBS) applications are one of them. Using LBS and mobile applications, the mobile device is working as a thin client, wherever the abundant data locations are storing and collecting at the mobile cloud to give corresponding services. The user’s location and privacy have opened new doors for the researchers and are widely studied in current years. However, secrecy is one of the greatest challenges in MCC due to the location of users on mobile devices (MD) being offloaded from MD to cloud providers that may be exploited by third parties Figure-2 (Almusaylim & Jhanjhi, 2020).

The main objective of this study is to find out emerging cybersecurity threats in the eye of e-governance in the current era and using machine learning techniques for exact results.

Figure 1.

Cyber security threats (Giles, 2019)

Figure 2.

Emerging cybersecurity threats (Engineering,)