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Under the guideless:
DR.MAMATHA H.R
Associate Professor
Information Science
pesit
TEJESH S
1PI12IS421
 Instant messaging services are quickly becoming the most dominant form of
communication among customer around the word.
 Privacy has been important for the user and service provider.
 Offers end to end encryption .
 iMessage uses the APPLE PUSH
NOTIFICATION SERVICE(APNS) to
deliver text message and attachments
to users.
 When the device first registered with
apple ,a client certificate is created
and stored on the device.
 A persistent APNs connection is made
to apple over TCP port 5223.
 When TCP port 5223 is blocked ,the
APNS message stream shifts to using
TCP port 443.
 User action
1.start typing
2.stop typing
3.send text
4.send attachment
5.read recipient
 When TCP port 5223 is blocked ,the APNS message stream shifts to using TCP
port 443.
LEAKAGE:
• Data and Methodology
• Operating System
• User Action
• Message Attributes
• Collect Data from user actions.
• Collects 250 packets from each user on both devices and in both the direction.
• The text data is drawn from a set of over one million sentences and short phrases
in a variety of language.
• IOS appears to more efficiently compress the
plaintext , while OSX occupies a much larger
space.
• To identify the OS of observed devices, we use a
binomial naïve bayes classifier from the WEKA
machine learning .
• Its also possible to trace communications as it
passes through apple.
• We create Hash-based lookup table using each observed length in training
data as a key and store the associated class label.
• When a new packet arrives ,we check the look up table to retrieve the class
labels for its payload length.
• Each cluster represents a unique
character set used in language.
• Use WEKA multinomial naïve
Bayes.
 Classification of languages in
OSX data is better than IOS.
 OSX achieve accuracy of 95%.
 IOS achieve accuracy of 80%.
Traffic Analysis of encrypted messaging services : Apple imessage and beyond
Traffic Analysis of encrypted messaging services : Apple imessage and beyond

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Traffic Analysis of encrypted messaging services : Apple imessage and beyond

  • 1. Under the guideless: DR.MAMATHA H.R Associate Professor Information Science pesit TEJESH S 1PI12IS421
  • 2.  Instant messaging services are quickly becoming the most dominant form of communication among customer around the word.  Privacy has been important for the user and service provider.
  • 3.  Offers end to end encryption .  iMessage uses the APPLE PUSH NOTIFICATION SERVICE(APNS) to deliver text message and attachments to users.  When the device first registered with apple ,a client certificate is created and stored on the device.  A persistent APNs connection is made to apple over TCP port 5223.  When TCP port 5223 is blocked ,the APNS message stream shifts to using TCP port 443.
  • 4.  User action 1.start typing 2.stop typing 3.send text 4.send attachment 5.read recipient  When TCP port 5223 is blocked ,the APNS message stream shifts to using TCP port 443.
  • 5. LEAKAGE: • Data and Methodology • Operating System • User Action • Message Attributes
  • 6. • Collect Data from user actions. • Collects 250 packets from each user on both devices and in both the direction. • The text data is drawn from a set of over one million sentences and short phrases in a variety of language.
  • 7. • IOS appears to more efficiently compress the plaintext , while OSX occupies a much larger space. • To identify the OS of observed devices, we use a binomial naïve bayes classifier from the WEKA machine learning . • Its also possible to trace communications as it passes through apple.
  • 8. • We create Hash-based lookup table using each observed length in training data as a key and store the associated class label. • When a new packet arrives ,we check the look up table to retrieve the class labels for its payload length.
  • 9. • Each cluster represents a unique character set used in language. • Use WEKA multinomial naïve Bayes.
  • 10.  Classification of languages in OSX data is better than IOS.  OSX achieve accuracy of 95%.  IOS achieve accuracy of 80%.