Prediction of DDoS Attacksusing Machine Learning and Deep Learning Algorithms
release_yrug2c32cfge3go6fatnpp2y2a
2019 p4860-4867
Abstract
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.
In application/xml+jats
format
Archived Files and Locations
application/pdf 554.3 kB
file_ykfyn65ldjdb7pmlo7pamh6ev4
|
www.ijrte.org (web) web.archive.org (webarchive) |
Open Access Publication
Not in DOAJ
In ISSN ROAD
Not in Keepers Registry
ISSN-L:
2277-3878
access all versions, variants, and formats of this works (eg, pre-prints)
Crossref Metadata (via API)
Worldcat
SHERPA/RoMEO (journal policies)
wikidata.org
CORE.ac.uk
Semantic Scholar
Google Scholar