The Challenges in SDN/ML Based Network Security : A Survey

Machine Learning is gaining popularity in the network security domain as many more network-enabled devices get connected, as malicious activities become stealthier, and as new technologies like Software Defined Networking (SDN) emerge. Sitting at the application layer and communicating with the control layer, machine learning based SDN security models exercise a huge influence on the routing/switching of the entire SDN. Compromising the models is consequently a very desirable goal. Previous surveys have been done on either adversarial machine learning or the general vulnerabilities of SDNs but not both. Through examination of the latest ML-based SDN security applications and a good look at ML/SDN specific vulnerabilities accompanied by common attack methods on ML, this paper serves as a unique survey, making a case for more secure development processes of ML-based SDN security applications.Comment: 8 pages. arXiv admin note: substantial text overlap with arXiv:1705.0056

DoS and DDoS Attacks: Defense, Detection and Traceback Mechanisms - A Survey

Denial of Service (DoS) or Distributed Denial of Service (DDoS) attacks are typically explicit attempts to exhaust victim2019;s bandwidth or disrupt legitimate users2019; access to services. Traditional architecture of internet is vulnerable to DDoS attacks and it provides an opportunity to an attacker to gain access to a large number of compromised computers by exploiting their vulnerabilities to set up attack networks or Botnets. Once attack network or Botnet has been set up, an attacker invokes a large-scale, coordinated attack against one or more targets. Asa result of the continuous evolution of new attacks and ever-increasing range of vulnerable hosts on the internet, many DDoS attack Detection, Prevention and Traceback mechanisms have been proposed, In this paper, we tend to surveyed different types of attacks and techniques of DDoS attacks and their countermeasures. The significance of this paper is that the coverage of many aspects of countering DDoS attacks including detection, defence and mitigation, traceback approaches, open issues and research challenges

Security Challenges from Abuse of Cloud Service Threat

Cloud computing is an ever-growing technology that leverages dynamic and versatile provision of computational resources and services. In spite of countless benefits that cloud service has to offer, there is always a security concern for new threats and risks. The paper provides a useful introduction to the rising security issues of Abuse of cloud service threat, which has no standard security measures to mitigate its risks and vulnerabilities. The threat can result an unbearable system gridlock and can make cloud services unavailable or even complete shutdown. The study has identified the potential challenges, as BotNet, BotCloud, Shared Technology Vulnerability and Malicious Insiders, from Abuse of cloud service threat. It has further described the attacking methods, impacts and the reasons due to the identified challenges. The study has evaluated the current available solutions and proposed mitigating security controls for the security risks and challenges from Abuse of cloud services threat