迈向网络传感超越传统安全事件的冒险

ID：25591

大小：0.81 MB

页数：9页

时间：2022-12-01

金币：15

上传者：战必胜

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Towards Cyber Sensing: Venturing Beyond Traditional Security

Events

Artūrs Lavrenovs, Kimmo HeinäaroandErwinOrye

NATOCCDCOE,Tallinn,Estonia

Arturs.Lavrenovs@ccdcoe.org

Kimmo.Heinaaro@ccdcoe.org 

Erwin.Orye@ccdcoe.org

DOI:10.34190/EWS.20.062



Abstract:HostandnetworkbasedeventsarethebackbonesofanymodernITmonitoringanddetectionsystem.Thenumber

oflowerprioritysecurityeventsissignificantand might contain weak indicators of cyberattacks; by combininghostand

networkeve ntswithsensordatathatarenotpartofconventionalITsecurity,weareabletoelevateotherwisemissedevents

to discover hidden cyber attacks. The sensor data is fed into a situational awareness system whichaugments traditional

alerts.Thistechniqueisprimarilyapplicableforcriticalinfrastru cture,military,governmentandlargeorganisationswhere

the adversary is sophisticated enough to bypass existing detection methods. We discuss operational and strategic

implicationsbyusingthistypeofsensor.Wehaveimplementedtheseprinciplesintwoscenariostestedincyberexercises.

InthefirstproofofconceptwefocusedonsensorfusionbyintegratingexistingnonITsensorsystemswithITse curityand

correlatedthecollecteddata.ThisenabledtheBlueTeamtodetectwellhiddenRedTeamattacksagainstasimulatedpower

gridandcounteractthem.Inthesecond,weexploredalargevarietyofsensorsmonitoringindi vidualpersonnelandtheir

operating environment. Sensors used in this research are categorised into biological, environmental and EM spectrum.

Biologicalsensordataincludesheartrate,stressleveland brain wave monitoring. EnvironmentalsensorsmonitortheRF

spectrum,CO

level,VOClevel,temperature,humidity,infrared,ultraviolet,visiblelight,noiselevel,proximityandvibration.



Keywords:hostbasedevents,networkbasedevents,IDS,securityevents,sensors

1. Introduction

Criticalinfrastructure,governmentandmilitarynetworksareundereverincreasingthreatofcyberattack.The

defence solutions market is experiencing growth and vendors are constantly developing new and more

advancedsolutionsthatusecuttingedgeapproacheslikeArtificialIntelligence(AI).Butmostofthesesolutions

relyontraditionalsourcesof data  host andnetworkbasedevents.Asadversaries inthisscenarioareupto

statelevelactors,theyhavetheresourcestoinvestigate,adapttoandovercomenewadvanceddefences.This

callsforawideningofourviewandexploringadditionalsourcesofdata.

Itdoesnotnecessarilyequatetoacquiringanothernewandexpensivesolutioncontainingbothhardwareand

softwarecomponents,butratherevaluatingwhatsensordataisalreadyavailable.Sensorscanbeviewedfrom

systemcentric and humancentric perspectives. The former primarily focuses on the states of the systems,

inferring human properties indirectly when possible , while the latter addresses biological data that can be

measureddirectlyviadedicatedsensors.Werefertothecombiningoftraditional andothersensordataforthe

purposeofdetectingcyberattacksascybersensing.



InSection 2wereviewexistingresearchaddressinghumanbehaviouranalysisandtrainingmodels.InSection3

we explore data sources acquirable from different sensors. In Section 4 we describe a proof of concept

correlatingtraditionalsecurityeventswithbuildingautomationandgatheringdatafromenvironmentalsensors.

Section 5 discusses operational and strategic implications of cyber sensing, and Section 6 presents our

conclusions.

2. Relatedwork

Therearetworelatedstreamsofworkinthisfield.Thefirstisfromahumancentricperspectiveandthesecond

concernshowcomputermodelscanbeusedtopredicthumanbehaviour.



Sensorfusionmimicsthehumanbraincombiningmultiplesenses.Linetal.(2004)proposeaneural network

architecture to integrate data from several physiological and behavioural sensors to improve reliability and

resistancetoimpersonation(multimodalverificationsystem).

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