Inspiration
To provide information based on the user query often fail to land the required page
because of the very short context text of the query. Heterogeneous data sources from the various domains in real world application are currently being described with multiconstructing classifiers for heterogeneous datasets . pre labels are identified as multi-label entities. Efficient learning and constructing classifiers for heterogeneous datasets
4## What it does The explosive rise of intelligent devices with ubiquitous connectivity have dramatically
increased Internet of Things (IoT) traffic in cloud environment and created potential attack surfaces for cyber-attacks.Traditional security approaches are insufficient and inefficient to address security threats in cloud-based IoT networks. In this vein, Software Defined Networking (SDN), Network Function Virtualization (NFV) and Machine Learning techniques introduce numerous advantages that can effectively resolve cybersecurity matters for cloud-based IoT systems.
Accomplishments that we're proud of
•TheexplosiveriseofintelligentdeviceswithubiquitousconnectivityhavedramaticallyincreasedInternetofThings(IoT)
trafficincloudenvironmentandcreatedpotentialattacksurfacesforcyber-attacks.Traditionalsecurityapproachesare insufficientandinefficienttoaddresssecuritythreatsincloud-basedIoTnetworks.Inthisvein,SoftwareDefinedNetworking (SDN),NetworkFunctionVirtualization(NFV)andMachineLearningtechniquesintroducenumerousadvantagesthatcan effectivelyresolvecybersecuritymattersforcloud-basedIoTsystem.
What's next for A Collaborative and Intelligent NIDS Architecture
weproposecollaborativeandintelligentnetwork-basedintrusiondetectionsystem(NIDS)architecture,namelySearch, forSDN-basedcloudIoTnetworks.InthispaperauthorisusingmachinelearningalgorithmstodetectattacksignatureinIoTnetworks asnow-a-dayseverywheresmallsensorsaredeployedtosensedataandthensendtocentralizedcloudserverforfurtherprocessing. Thesesensorscanbedeployedatroadsidetomonitortraffic,militaryarea,healthcaremonitoringetc.Thissensorwilluse3different devicessuchasEDGEIDS,FOGIDSandCloudserver.SensorswillsenddatatoEDGEIDSbyusingoptimizepathandthenEDGE IDwillrunSVMalgorithmtocheckwhetherrequestcontainsnormalorattacksignatureandthenEDGEIDSwillforwardrequestto FOGIDSandthenFOGIDSwillrunSOM(self-organizingmapclustering)algorithmtocheckwhetherrequestcontainsnormalor attacksignatureandthenFOGIDSwillsendrequesttoCLOUDserverandthencloudserverwillrunSAE(stackedautoencoderdeep learning)algorithmtocheckrequestcontainsattackornormalsignature.
Log in or sign up for Devpost to join the conversation.