A 'peer reviewed' journal indexed on Cabell's Directory, and also distributed by EBSCO and Proquest Database
It is a quarterly journal that publishes research papers on state-of-the-art Computing techniques and Encryption techniques; Computational problems; Artificial Intelligence; Cloud Computing; Databases; Algorithms and data structures; Cybernetics; Firewall techniques; Chip designing, Logic circuits and Software engineering; Programming techniques; Computer architecture; Neural networks, Machine Learning etc.
Mobile Edge Computing: Security and Privacy Issues, Challenges and Countermeasures
Mobile Edge Computing (MEC) is a novel technology that provides fast data processing with efficiency on 5G networks. It can be propitious in Internet of Things (IoT)-based contexts, as it renders a cloud-computing and IT services environment. Moreover, MEC has no terminal servers, as it is often deployed near the network's edge. However, the unique features and working principles of MEC will lead to a number of new security and privacy-related concerns. In this paper, the security issues are discussed along with their multiple solutions. Finally, suggestions to strengthen the security of MEC services are offered.
Strategy for Reliable, Efficient and Secure IoT Using Artificial Intelligence
The Internet of Things (IoT), one of the leading cutting-edge innovations, has become an economically attractive field of focus for the scientific community. It requires several system interconnections and device interactions with humans. In order to manage its data exchange and analysis, IoT needs a cloud computing environment; Artificial Intelligence (AI) is needed at the same time via the Internet and cloudbased network of networks. These interconnected IoT systems can interact and share information with each other using their respective identifiers and embedded sensors on each device. We live in the age of big data, and it has become very important to easily and reliably interpret the captured big data. However, while AI is currently playing a greater role in strengthening conventional safety, there are significant challenges to cloud security and IoT computer networking. There are many security concerns that cloud be a danger to the community. In comparison, several of the IoT systems installed on a public network that is wirelessly accessible are now under persistent cyber attack. The paper suggests a hybrid identification paradigm as a response strategy that utilizes Machine Learning (ML) and AI to mitigate and combat IoT cyberattacks both at the host and network levels in cloud computing environments.
A Comprehensive Overview of DDoS Attacks in Cloud Computing Environment and Different Machine Learning Techniques
As cloud computing usage gains popularity, the security vulnerabilities are also increasing. Cloud computing is affected by many types of attacks like account hijacking, data breaches, malicious insiders, human error, etc. This paper primarily focuses on Distributed Denial-of-Service (DDoS) attacks, a major security issue for a cloud system. By sending huge amounts of unusual traffic, a DDoS attack corrupts the resources and makes them inaccessible. DDoS attacks are designed to drain resources like main memory, CPU refining, processing space and network frequency, thus making them inaccessible to the customers. It is difficult to identify the difference between the attacker's requests and legitimate user requests in cloud systems at all stages, especially when the latter comes from a huge number of geographically dispersed workstations. The paper provides a detailed analysis of DDoS attacks and makes a comparative study of various algorithms against the attacks on cloud computing.
Microsoft Azure's Leading Edge in Cloud Computing Services
Although Amazon Web Services (AWS) has made its way as one of the preferred Cloud Service Providers (CSP) in the industry, a few factors have shown that it might not be the top choice for most cloud clients. Microsoft Azure, a competing cloud platform provides a range of services which includes computing, analysis, storage and network capabilities. Azure offers tools that support a wide range of technological compatabilities amongst various industries. This paper briefly discusses Azure's cloud capabilities in comparison to other cloud service providers. A review of all relevant sources was carried out. The results shows that Azure offers a set of capabilities and features that surpasses other cloud platforms.
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