Abstract:The current trend of research in cloud computing is challenging and keenly marginal to understand for the researchers and the learners due to its over-cover and complementary nature towards the new technologies. Cloud Computing is part and parcel of its applications with a majority of the extending concepts of Fog Computing, Internet of Things (IoT) and Big Data Analytics. In the current scenario, it is difficult for a researcher to identify the domain applicability and interrelationship among all the specifie… Show more
“…In addition to handling heavy transactional workloads in companies and organizations, SQL DBMSs in general, provide more security features than their NoSQL counterparts, this may be attributed to the fact that NoSQL DBMSs are still relatively new compared to SQL DBMSs. In the future, following the sporadic advancements in Cloud and IoT deployments [37][38] coupled with data processing requirements, it is believed that the security model of NoSQL platforms would advance to such a level that it can substantially compete with or outweigh the best security provisions in the best commercial SQL DBMSs available. In each case, it may be submitted that the greatest threat to database base security is the human factor.…”
Database security has become a very critical issue for organizations and agencies that deploy databases as major data stores for their operations. The ever-increasing data volumes to be stored, maintained and manipulated, the changing user and operational requirements, and the advancement in cloud platforms and hardware have contributed to the consistent change in trends around database research and development which are in many cases directed towards the engineering of innovative data models, techniques and systems that could help overcome the security challenges already established in the existing database management systems. This paper is an articulation of the critical security threats, challenges and vulnerabilities of two widely used database management systems (DBMS): the NoSQL and SQL-based DBMS respectively. The period under review is from 2010-2019, is perceived as a decade that recorded outstanding changes in data and database engineering respectively.
“…In addition to handling heavy transactional workloads in companies and organizations, SQL DBMSs in general, provide more security features than their NoSQL counterparts, this may be attributed to the fact that NoSQL DBMSs are still relatively new compared to SQL DBMSs. In the future, following the sporadic advancements in Cloud and IoT deployments [37][38] coupled with data processing requirements, it is believed that the security model of NoSQL platforms would advance to such a level that it can substantially compete with or outweigh the best security provisions in the best commercial SQL DBMSs available. In each case, it may be submitted that the greatest threat to database base security is the human factor.…”
Database security has become a very critical issue for organizations and agencies that deploy databases as major data stores for their operations. The ever-increasing data volumes to be stored, maintained and manipulated, the changing user and operational requirements, and the advancement in cloud platforms and hardware have contributed to the consistent change in trends around database research and development which are in many cases directed towards the engineering of innovative data models, techniques and systems that could help overcome the security challenges already established in the existing database management systems. This paper is an articulation of the critical security threats, challenges and vulnerabilities of two widely used database management systems (DBMS): the NoSQL and SQL-based DBMS respectively. The period under review is from 2010-2019, is perceived as a decade that recorded outstanding changes in data and database engineering respectively.
“…In addition to the overhead generated by the scan, IP addresses are usually dynamic and the requirement to login for identification is not possible, given that the DDoS attack may make an identification operation impossible. In [9], [21], attacks are dealt with by creating a new instance of the application. Once a DDoS attack is detected, the proposed mechanism seeks to identify the attackers through PINGs: if a client suspected of being an attacker does not respond to the PING, he is considered as an attacker, not being redirected to the new instance of the application.…”
Distributed Denial of Service (DDoS) attacks are often overlooked because they represent only a temporary interruption in the normal functioning of a system. With the advent of paradigms like the cloud, the mitigation of this type of threat with the increase of resources for the applications becomes viable, but it causes a problem called economic DDoS. This paper presents an architecture proposal to mitigate DDoS attacks directed at an application hosted in a cloud. Such architecture is based on the instantiation of a replication of the application -simple operation in a cloudand the redirection of only legitimate requirements for this reply. The proposed architecture does not need to identify attacking customers and, even so, it is able to filter only legitimate traffic without the load and possible errors resulting from the need for identification.
“…[8] proposed a secure and efficient mutual authentication concept for an edge-fog-cloud network architecture to mutually authenticate fog client computing at the edge of the network, with the fog servers at the fog layer. This author required a client in the network to hold only one long-term master secret key, which allows verifying a communication with any client in the fog server of the network, with a fully authenticated direction [24].…”
Many organizations, such as military, financial, and banking organizations, implement strict security policies for securing and protecting data from any possible attack. Moreover, these institutions use the Internet of things (IoT) and fog computing for communication and storage that require new solutions to confirming the login process between the two techniques. A methodology for increasing the security for fog computing is proposed in this research. The proposed methodology provides authentication that is based on the location of the device that will perform fog computing during communication, thereby ensuring the secure login to data and legal verification. Furthermore, the proposed methodology is simulated using the LabVIEW simulator with different case studies. Results show that location-based authentication increases authentication confidence and security.
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