Open AccessPrediction of DDoS Attacksusing Machine Learning and Deep Learning Algorithms
Author(s) -
Vara Saritha,
B. Rama Subba Reddy,
A. Suresh Babu
Publication year - 2019
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.d8162.118419
Subject(s) - computer science , denial of service attack , computer security , the internet , cloud computing , network security , context (archaeology) , confidentiality , computer network , world wide web , operating system , paleontology , biology
With the emergence of network-based computing technologies like Cloud Computing, Fog Computing and IoT (Internet of Things), the context of digitizing the confidential data over the network is being adopted by various organizations where the security of that sensitive data is considered as a major concern. Over a decade there is a massive growth in the usage of internet along with the technological advancements that demand the need for the development of efficient security algorithms that could withstand various patterns of the security breaches. The DDoS attack is the most significant network-based attack in the domain of computer security that disrupts the internet traffic of the target server. This study mainly focuses to identify the advancements and research gaps in the development of efficient security algorithms addressing DDoS attacks in various ubiquitous network environments.