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Submitted URL: http://darktracecommunity.com/
Effective URL: https://darktrace.com/research
Submission: On January 06 via manual from JP — Scanned from JP

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CountryCountryUnited StatesCanadaAfghanistanAlbaniaAlgeriaAmerican
SamoaAndorraAngolaAnguillaAntarcticaAntigua and
BarbudaArgentinaArmeniaArubaAustraliaAustriaAzerbaijanBahamasBahrainBangladeshBarbadosBelarusBelgiumBelizeBeninBermudaBhutanBoliviaBosnia
and HerzegovinaBotswanaBouvet IslandBrazilBritish Indian Ocean
TerritoryBruneiBulgariaBurkina FasoBurundiCambodiaCameroonCape VerdeCayman
IslandsCentral African RepublicChadChileChinaChristmas IslandCocos
IslandsColombiaComorosRepublic of the CongoCook IslandsCosta
RicaCroatiaCubaCyprusCzechiaDenmarkDjiboutiDominicaDominican RepublicEast
TimorEcuadorEgyptEl SalvadorEquatorial GuineaEritreaEstoniaEthiopiaFalkland
IslandsFaroe IslandsFijiFinlandFranceFrench GuianaFrench PolynesiaFrench
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TerritoriesGabonGambiaGeorgiaGermanyGhanaGibraltarGreeceGreenlandGrenadaGuadeloupeGuamGuatemalaGuineaGuinea-BissauGuyanaHaitiHeard
Island and McDonald IslandsHondurasHong
KongHungaryIcelandIndiaIndonesiaIranIraqIrelandIsraelItalyIvory
CoastJamaicaJapanJordanKazakhstanKenyaKiribatiNorth KoreaSouth
KoreaKosovoKuwaitKyrgyzstanLaosLatviaLebanonLesothoLiberiaLibyaLiechtensteinLithuaniaLuxembourgMacaoMacedoniaMadagascarMalawiMalaysiaMaldivesMaltaMarshall
IslandsMartiniqueMauritaniaMauritiusMayotteMexicoMicronesiaMoldovaMonacoMongoliaMontenegroMontserratMoroccoMozambiqueMyanmarNamibiaNauruNepalNetherlandsNetherlands
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GuineaParaguayPeruPhilippinesPitcairnPolandPortugalPuerto
RicoQatarReunionRomaniaRussiaRwandaSaint Kitts and NevisSaint LuciaSaint Vincent
and the GrenadinesSamoaSan MarinoSao Tome and PrincipeSaudi
ArabiaSenegalSerbiaSeychellesSierra LeoneSingaporeSlovakiaSloveniaSolomon
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CongoJerseyIsle of ManGuernseySaint MartinMaliPalestinian TerritorySint
MaartenBonaire, Saint Eustatius and SabaSouth SudanSerbia and MontenegroSaint
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AI Research Abstracts
AI Research CENTRE
Home
Research Abstracts
Innovating Cyber Recovery - Key to Cyber Resilience
Rapid Process-Chain Anomaly Detection Using a Multistage Classifier
Sorting long lists of file names by relevance and sensitive content
A system for analyzing network activity to detect stealthy cryptocurrency mining
Autonomous detection of the intended function of a corporate inbox through
meta-scoring
Using epidemiology theory to identify the most damaging network devices
Automatic Identification of Scanned IP Ranges
A real-time, self-correcting similarity classifier for emails
Attack Path Modeling Research
Prevent: Security through Adversity
Using graph theory to identify critical nodes within computer networks
Analyzing network activity to detect compromised devices sending spam emails
Detecting and preventing misdirected emails with correspondence semantics
Gaussian constructions on surfaces for anomalous event identification
Structural construct detection as a variable indicator of compromise
Identifying compromises with graphs of high-precision security metadata
Programmatically monitoring disparate SaaS environments
Analysis of email structure to detect malicious intent
Securing tenant data in the public cloud
Matryoshka Bloom filters quickly and efficiently determine rarity
Robust identification of ransomware encryption over SMB
Identification of cryptomining credentials and their use in differentiating
between insider threats and wide-spread malware
Identification of services associated with data uploads for analysis of
exfiltration
A multi-platform approach to autonomous response




DARKTRACE CYBER
AI RESEARCH CENTRE

> Research unlocks the unknowns; it also helps shed light on what we are
> collectively up against.

— JACK STOCKDALE OBE, CTO




OUR HISTORY

The Darktrace AI Research Centre is foundational to our continued innovation.
Teams of mathematicians and other experts examine how AI can be applied to
real-world problems, to find new paths forward to augment human capabilities.

With more than 100 patents and patents pending, the AI Research Centre comprises
more than 150 members, including experts with 80 master's degrees and 30
doctorates in disciplines from astrophysics to linguistics to data science.  
Rather than confined to work on product roadmaps, researchers are free to
experiment and explore, guided by creative insight arising from pure research.
Yet we have never shied away from taking on real challenges faced by the
industry, and the AI Research Centre operates with a common goal of solving
these challenges with AI and mathematics. Following Darktrace’s acquisition of
Cybersprint, a second R&D center is operational in The Hague, The Netherlands.
The AI Research Centre has produced numerous award-winning breakthroughs, which
have gone on to form the AI capabilities that today comprise our products
contained in the Darktrace Cyber AI Loop. Please see below a selection of
 research abstracts stemming from these research initiatives.



48%

Headcount increase in 2021


30

Doctorates


88

Masters

> [The Centre] saw growth of 69.2% in related patent applications in the three
> months ending November, compared to the same period [the previous year] — the
> highest percentage growth out of all companies tracked.

— GLOBAL DATA


FEATURED RESEARCH

Innovating Cyber Recovery - Key to Cyber Resilience

Read our second Darktrace Discourse paper, authored by John C. Allen, MBA,
CRISC, and VP Cyber Risk & Compliance, Darktrace. This paper reviews the current
state of incident recovery and sets forth seven areas of innovation to improve
Recovery from cyber incidents, based on a core capability: Real-Time Adaptive
Incident Response.

Download
Attack Path Modeling Research

This paper outlines the Attack Path modeling (APM) module of Darktrace PREVENT,
exploring how real-time, automated, dual-aspect, multi-data-source, end-to-end
APM can be used to give blue teams a comprehensive view of realistic,
risk-prioritized attack paths so that resources can be best allocated to defend
key assets.

Download
Prevent: Security through Adversity

Read our Darktrace Discourse paper, authored by one of our researchers based at
the Centre. The author has seven years’ experience in the automation of complex
cyber-centric processes with specialization in the offensive domain, and holds a
PhD in Astrophysics from the University of Cambridge.

Download


RESEARCH

Structural construct detection as a variable indicator of compromise
Detecting email spoofing attempts by identifying unusual patterns in HTML and
CSS.
Researchers
Stephen Pickman
Read more

Sorting long lists of file names by relevance and sensitive content
Quickly assessing the importance of compromised files before, during and after
an attack.
Researchers
Dr. Andrés Curto Martín
Read more

Using graph theory to identify critical nodes within computer networks
How graph theory can be used to map out cross-domain, realistic, and
risk-assessed attack paths across an entire digital enterprise
Researchers
Darktrace researcher, PhD
Read more

Detecting and preventing misdirected emails with correspondence semantics
Identifying if the recipient of a particular email appears correct in the wider
context of user activity.
Researchers
Ben Akrill
Read more

Autonomous detection of the intended function of a corporate inbox through
meta-scoring
Knowing which corporate inboxes are supposed to receive a lot of email and which
are not.
Researchers
Dr. Steven Haworth
Read more

Identification of services associated with data uploads for analysis of
exfiltration
How the intelligent analysis of connection properties can help assess whether
specific uploads are associated with malicious exfiltration.
Researchers
Dr. Tim Bazalgette
Read more

Identification of cryptomining credentials and their use in differentiating
between insider threats and wide-spread malware
How global analysis of cryptomining credentials can identify malicious criminal
organizations leveraging corporate computing power for financial gain.
Researchers
Dr. Andrew Woodford
Read more

Robust identification of ransomware encryption over SMB
How the high-level analysis of SMB operations, files, and properties can
identify ransomware infections.
Researchers
Dr. Tim Bazalgette
Read more

Programmatically monitoring disparate SaaS environments
Optimizing the use, visibility and security of environments that span multiple
complex cloud and SaaS environments.
Researchers
Jacob Araiza
Read more

A system for analyzing network activity to detect stealthy cryptocurrency mining
Using AI to detect hard-to-see crypto-mining activity on corporate devices.
Researchers
Dr. Andrés Curto Martín
Read more

Rapid Process-Chain Anomaly Detection Using a Multistage Classifier
Timely analysis uses simple methods for simple problems and deep learning for
difficult problems, but only if you can tell the difference.
Researchers
Dr. Matthew Ferguson
Read more

Securing tenant data in the public cloud
Secure practices to ensure corporate data sitting within public servers such as
AWS is sufficiently isolated, in the event of a data breach targeting these
public cloud providers.
Researchers
Alex Smith
Read more

Automatic Identification of Scanned IP Ranges
Identifying targets of reconnaissance amongst the noise of background network
activity
Researchers
Dr. Tim Bazalgette
Read more

Matryoshka Bloom filters quickly and efficiently determine rarity
A novel data structure for the efficient storage and retrieval of statistics on
how common strings are in specific environments.
Researchers
Dr. Matthew Ferguson
Read more

Gaussian constructions on surfaces for anomalous event identification
Determining anomalies by creating probability density functions on different
surfaces corresponding to the properties of interest.
Researchers
Dr. Tim Bazalgette
Dr. Dickon Humphrey
Read more

Analyzing network activity to detect compromised devices sending spam emails
Distinguishing between genuine and illegitimate email traffic from network
servers.
Researchers
Dr. Andrés Curto Martín
Read more

A real-time, self-correcting similarity classifier for emails
Recognizing when similar but subtly different emails were sent by the same
sender or as part of a campaign, but also recognizing when the similarity is
coincidental.
Researchers
Dr. Steven Haworth
Read more

Identifying compromises with graphs of high-precision security metadata
Using directed graphs of lower-level security events to reliably discover
complex security incidents.
Researchers
Dr. Tim Bazalgette
Dr. Dickon Humphrey
Read more

Analysis of email structure to detect malicious intent
Using AI to determine whether an email is trying to induce the reader to do
something that would lead to compromise, such as clicking on a link or opening a
file.
Researchers
Dr. Antony Lawson
Read more

A multi-platform approach to autonomous response
How autonomous response technology works seamlessly across different
environments, providing a solution for organizations using multiple cloud
environments and SaaS applications.
Researchers
John Boyer
Read more

Using epidemiology theory to identify the most damaging network devices
Preventing disaster by modeling how an attack might spread after an initial
compromise
Researchers
Jake Lal
Read more



RESEARCHERS

BACHELOR OF SCIENCE

Stanford University
Specializes in electrical engineering including analog circuit design and
organic semiconductors.

PHD IN ASTROPHYSICS

University of Cambridge
Specializes in general automation of complex, typically human-driven processes
with current focus on adversarially-oriented preventative security.

PHD IN MATHEMATICS AND PHYSICS

University of Cambridge
Specializes in applications of machine learning and statistical analysis,
clustering techniques and the use of neural networks for the classification of
categorical data.

PHD IN BIOCHEMISTRY

University of Cambridge
Specializes in neuroscience and behaviour modeling, machine learning to identify
novel threats, and automated healing of computer systems following a digital
compromise.

MASTER’S IN MATHEMATICS

Durham University
Specializes in mathematical biology and mathematical modeling, numerical
analysis and adversarial attack simulations.

PHD IN STATISTICS

Durham University
Specializes in non-parametric modeling, statistical and optimization problems,
dimension reduction and classification problems.

MASTER’S IN PHYSICS

University of Cambridge
Specializes in the application of nuclear magnetic resonance to manufacturing
processes, and the application of machine learning to galaxy clustering.

MASTER’S IN ENGINEERING

University of Oxford
Specializes in applications of machine learning techniques in bioengineering,
applying neural networks to extract structures in medical imagery, and
investigating novel phishing techniques.

PHD IN THEORETICAL LINGUISTICS

University of Cambridge
Specializes in algorithmic modeling of cognitive representations and acquisition
of natural language syntax.

PHD IN COSMOLOGY

University of Cantabria
Specializes in developing novel advanced statistical techniques in data analysis
and software engineering for supercomputers.

PHD IN MATHEMATICS

University of Bath
Specializes in applications of AI to endpoint and cloud environments and network
traffic analysis.

PHD IN MATHEMATICS

University of York
Specializes in mathematical physics, anomaly detection in complex data to
improve efficiency, and optimization and stability in data processing.


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