Recently, the life in Earth becomes turbulent with the worldwide s pread of novel coronavirus (COVID-19). This outbreak has been declared as a public health emergency in the level of international concern by world health organization (WHO). To reduce the spread of COVID19 entire world has adopted social distancing, where working and learning from home is the new normal for this new world. To sustain the economical revenue and business growth companies that radically move into cloud infrastructure to support employees, who work remotely. With the unprecedented growth of cloud, data breaches and cyber security takes a huge leap. Apart from big cloud vendor small cloud startups are getting huge leap currently. Starting from enterprise solution providers, cloud supports in education, e-commerce, and healthcare also. Hackers penetrating not only the cloud resources it also hampers the hosts and device connected with it. This paper discovers several security challenges due to the sudden use of cloud platforms without adequate precautions. The aim of this paper is to highlight these areas causing security breaches and propose generic preventive measures.
The ubiquitous cloud computing services provide a new paradigm to the work-from-home environment adopted by the enterprise in the unprecedented crisis of the COVID-19 outbreak. However, the change in work culture would also increase the chances of the cybersecurity attack, MAC spoofing attack, and DDoS/DoS attack due to the divergent incoming traffic from the untrusted network for accessing the enterprise’s resources. Networks are usually unable to detect spoofing if the intruder already forges the host’s MAC address. However, the techniques used in the existing researches mistakenly classify the malicious host as the legitimate one. This paper proposes a novel access control policy based on a zero-trust network by explicitly restricting the incoming network traffic to substantiate MAC spoofing attacks in the software-defined network (SDN) paradigm of cloud computing. The multiplicative increase and additive decrease algorithm helps to detect the advanced MAC spoofing attack before penetrating the SDN-based cloud resources. Based on the proposed approach, a dynamic threshold is assigned to the incoming port number. The self-learning feature of the threshold stamping helps to rectify a legitimate user’s traffic before classifying it to the attacker. Finally, the mathematical and experimental results exhibit high accuracy and detection rate than the existing methodologies. The novelty of this approach strengthens the security of the SDN paradigm of cloud resources by redefining conventional access control policy.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.