DECEPTION
TECHNOLOGIES
Raj Gopalakrishna
Co-founder & Chief Product Architect
AcalvioTechnologiesCopyright AcalvioTechnologies 1
Brief History of Deception
DeceptionTypes
Under the Hood
Some Use Cases
Touch Points
Deception over the years
• Millions of years in Natural World for
survival/aggression
• Millions of years in bacteria and virus to
thrive
• 1000s of years in Warfare/Military to attack
or defend
• Decades in Cyber Warfare
• Attackers use Deception
• Phishing, spoofing, encryption
• Defender should use Deceptions
• Honeypots, Cryptographic Camouflage
• French Election used it recently
Owl Butterfly for Survival
3Copyright AcalvioTechnologies
Transmitter
Passion Fruit Leaf
with spots
UNDER
THE
HOOD
Copyright AcalvioTechnologies 4
Breadcrumbs: Extend Deceptions to Production Devices
Many flavors and forms:
1. Registry entries
2. Files & Folders
3. Memory hashes
4. User Profiles
5. Browser cookies
Few Challenges:
1. Need deployment Automation
and Intelligence
2. Avoid Accidental Alerts by
Users
5
DeceptionAnywhere or Everywhere
Copyright AcalvioTechnologies
Lures: Another powerful arrow in the quiver
Deliberately placed
1. Vulnerabilities in OS, Application,
Protocols
2. Weak configurations and permissions
3. Powerful fake Service Accounts
4. Shares
5. Interesting Data
6
Make Deceptions more attractive
Copyright AcalvioTechnologies
DecoyTypes
Low Interaction Deceptions
• Attacker typically cannot login
• Emulated Hosts, Applications,
Database Servers
High Interaction Deceptions
• Attacker can login – full interaction
• RealVM Hosts, Applications, Database
Servers, Shares
Copyright AcalvioTechnologies 7
Low Interaction Deceptions
 Deploy OS, Network services orApplications
 Lots of deceptions possible.
 Low IT cost
 Low Risk to Enterprise Networks
 Dynamic: easy to morph on-the-fly
 Need not be emulations!
× Cannot Engage with theAttacker
× If Emulated then Easy to fingerprint Deceptions
Key Challenge:
Odds of attacker identifying deceptions
Copyright AcalvioTechnologies 8
High Interaction Deceptions
Deploy real OS, Services, Applications
Deceptions are not finger-printable.
Possible to Engage with Attacker
× Only Few deceptions
× High Cost of licensing & maintaining
× Need Containment to reduce RISK
× Static: pre-build, unable to morph quickly
× Often used with Breadcrumbs to lead
attacker to Decoys. But then attacker needs
to find breadcrumbs first
Key Challenge:
Odds of Attacker/Malware running into the few deceptions
Copyright AcalvioTechnologies 9
Often we need both
Scale and Depth (Believable Deceptions)
Copyright AcalvioTechnologies 10
Static vs Dynamic Deceptions
Static Deceptions
• Hardly changes
• Easy to fingerprint & avoid
Dynamic Deceptions
Mimic Octopus:
Mimics upto 15 creatures
ActiveCamouflage:
Counter-illumination by Squids
• Changing always
• Hard to predict or identify
HoneyAnts
Copyright AcalvioTechnologies
11
Intelligence Component
Human only
• Expert decides type and number of
deceptions to deploy
• Manually/Automatically configures
traps atTime T0
Key Challenges:
• What happens atTimeT1 orT10 ?
• How many Experts can company
send to front-line for 24x7x365?
Human + AI based = Future
System recommends type, number,
placement, duration of deceptions.
System Responds to
• Events and Incidents
• Adversary Behavior
• When you are sleeping
Copyright AcalvioTechnologies 12
Some major Challenges in Cyber Security
Compromise Detection Identifying malicious intent
© AcalvioTechnologiesCompany 13
Alerts Deluge Too many False positives
DeceptionTechnology can help in all of above
Internal Facing vs External Facing
Deceptions
Internal Facing
• Good for Enterprises
• A new layer of Defense
• Acts like a motion detector inside
Enterprises
• Corporate Network
• Data Centers
• Detects attackers who have gone past
the perimeter defenses
• Few, High FidelityAlerts raised
• Can optionally Engage & Respond
External Facing
• Great for security researchers
• Typically deployed on the Internet or
in the DMZ.
• Lots of alerts per hour/day as there
are lots of malicious Attackers and
Bots on the Internet
• Often used to show demo of
DeceptionTechnologies
Copyright AcalvioTechnologies 14
Detecting Ransomware: current
approaches
AV and Sandbox approach
• Look for known Signatures
• Look for known C&C
 Low False +ve
× High False -ve
Data Science approach
• Look for Anomalous Behavior
• High File I/O
• Lots of different Files accessed
• Lots of crypto
× Anomaly ≠Threat
× High False +ve
15Copyright AcalvioTechnologies
Detecting Ransomware using Deceptions
• Leverages Decoys,
Breadcrumbs and Lures
• Set specific traps in specific
locations
• Monitor only activity against
decoys, breadcrumbs & lures
Auto Detects and confirms
Ransomware
Very Efficient and Accurate
16
Always High Fidelity Signals
Zero false +ve
Copyright AcalvioTechnologies
Protecting Secrets in
software is hard
Examples
Crypto keys
Passwords
Payment card
numbers
Copyright AcalvioTechnologies 17
THANKYOU
Copyright AcalvioTechnologies 18
• Raj Gopalakrishna
• raj@Acalvio.com
• AcalvioTechnologies Inc
CONTACT ACALVIO
IFYOU ARE LOOKING FOR
DECEPTION PRODUCT
Copyright AcalvioTechnologies 19

Deception Technology: Use Cases & Implementation Approaches

  • 1.
    DECEPTION TECHNOLOGIES Raj Gopalakrishna Co-founder &Chief Product Architect AcalvioTechnologiesCopyright AcalvioTechnologies 1
  • 2.
    Brief History ofDeception DeceptionTypes Under the Hood Some Use Cases Touch Points
  • 3.
    Deception over theyears • Millions of years in Natural World for survival/aggression • Millions of years in bacteria and virus to thrive • 1000s of years in Warfare/Military to attack or defend • Decades in Cyber Warfare • Attackers use Deception • Phishing, spoofing, encryption • Defender should use Deceptions • Honeypots, Cryptographic Camouflage • French Election used it recently Owl Butterfly for Survival 3Copyright AcalvioTechnologies Transmitter Passion Fruit Leaf with spots
  • 4.
  • 5.
    Breadcrumbs: Extend Deceptionsto Production Devices Many flavors and forms: 1. Registry entries 2. Files & Folders 3. Memory hashes 4. User Profiles 5. Browser cookies Few Challenges: 1. Need deployment Automation and Intelligence 2. Avoid Accidental Alerts by Users 5 DeceptionAnywhere or Everywhere Copyright AcalvioTechnologies
  • 6.
    Lures: Another powerfularrow in the quiver Deliberately placed 1. Vulnerabilities in OS, Application, Protocols 2. Weak configurations and permissions 3. Powerful fake Service Accounts 4. Shares 5. Interesting Data 6 Make Deceptions more attractive Copyright AcalvioTechnologies
  • 7.
    DecoyTypes Low Interaction Deceptions •Attacker typically cannot login • Emulated Hosts, Applications, Database Servers High Interaction Deceptions • Attacker can login – full interaction • RealVM Hosts, Applications, Database Servers, Shares Copyright AcalvioTechnologies 7
  • 8.
    Low Interaction Deceptions Deploy OS, Network services orApplications  Lots of deceptions possible.  Low IT cost  Low Risk to Enterprise Networks  Dynamic: easy to morph on-the-fly  Need not be emulations! × Cannot Engage with theAttacker × If Emulated then Easy to fingerprint Deceptions Key Challenge: Odds of attacker identifying deceptions Copyright AcalvioTechnologies 8
  • 9.
    High Interaction Deceptions Deployreal OS, Services, Applications Deceptions are not finger-printable. Possible to Engage with Attacker × Only Few deceptions × High Cost of licensing & maintaining × Need Containment to reduce RISK × Static: pre-build, unable to morph quickly × Often used with Breadcrumbs to lead attacker to Decoys. But then attacker needs to find breadcrumbs first Key Challenge: Odds of Attacker/Malware running into the few deceptions Copyright AcalvioTechnologies 9
  • 10.
    Often we needboth Scale and Depth (Believable Deceptions) Copyright AcalvioTechnologies 10
  • 11.
    Static vs DynamicDeceptions Static Deceptions • Hardly changes • Easy to fingerprint & avoid Dynamic Deceptions Mimic Octopus: Mimics upto 15 creatures ActiveCamouflage: Counter-illumination by Squids • Changing always • Hard to predict or identify HoneyAnts Copyright AcalvioTechnologies 11
  • 12.
    Intelligence Component Human only •Expert decides type and number of deceptions to deploy • Manually/Automatically configures traps atTime T0 Key Challenges: • What happens atTimeT1 orT10 ? • How many Experts can company send to front-line for 24x7x365? Human + AI based = Future System recommends type, number, placement, duration of deceptions. System Responds to • Events and Incidents • Adversary Behavior • When you are sleeping Copyright AcalvioTechnologies 12
  • 13.
    Some major Challengesin Cyber Security Compromise Detection Identifying malicious intent © AcalvioTechnologiesCompany 13 Alerts Deluge Too many False positives DeceptionTechnology can help in all of above
  • 14.
    Internal Facing vsExternal Facing Deceptions Internal Facing • Good for Enterprises • A new layer of Defense • Acts like a motion detector inside Enterprises • Corporate Network • Data Centers • Detects attackers who have gone past the perimeter defenses • Few, High FidelityAlerts raised • Can optionally Engage & Respond External Facing • Great for security researchers • Typically deployed on the Internet or in the DMZ. • Lots of alerts per hour/day as there are lots of malicious Attackers and Bots on the Internet • Often used to show demo of DeceptionTechnologies Copyright AcalvioTechnologies 14
  • 15.
    Detecting Ransomware: current approaches AVand Sandbox approach • Look for known Signatures • Look for known C&C  Low False +ve × High False -ve Data Science approach • Look for Anomalous Behavior • High File I/O • Lots of different Files accessed • Lots of crypto × Anomaly ≠Threat × High False +ve 15Copyright AcalvioTechnologies
  • 16.
    Detecting Ransomware usingDeceptions • Leverages Decoys, Breadcrumbs and Lures • Set specific traps in specific locations • Monitor only activity against decoys, breadcrumbs & lures Auto Detects and confirms Ransomware Very Efficient and Accurate 16 Always High Fidelity Signals Zero false +ve Copyright AcalvioTechnologies
  • 17.
    Protecting Secrets in softwareis hard Examples Crypto keys Passwords Payment card numbers Copyright AcalvioTechnologies 17
  • 18.
    THANKYOU Copyright AcalvioTechnologies 18 •Raj Gopalakrishna • raj@Acalvio.com • AcalvioTechnologies Inc
  • 19.
    CONTACT ACALVIO IFYOU ARELOOKING FOR DECEPTION PRODUCT Copyright AcalvioTechnologies 19