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Marina Gavrilova
Scientific question:
If a person's photo in the system's database was taken 10 years ago, is it possible to
identify the person today?
Answer can be provided by next generation face reconstruction engines.
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Fusion
Biometric Fusion means integration of biometric information.
The goal of fusion scheme is to devise an appropriate
function that can optimally combine the information
rendered by the biometric subsystems.
Broadly classified as –
Prior-to-matching fusion and After-matching fusion
Humanoid robots are anthropomorphic robots (have human-like shape)
that include also human-like behavioral traits. The field of humanoid
robotics includes various challenging direct and inverse biometrics.
On the other hand, in relation to inverse biometrics, robots attempt
to generate postures, poses, face expressions to better communicate
their human masters (or to each other) the internal states [49]).Robots such as Kismet express calm, interest, disgust,
happiness,surprise, etc (see (MIT projects).
More advanced aspects include dialogue and logical reasoning similar to those of humans. As more robots would enter our society it will become useful to distinguish them among each other by robotic biometrics.
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More advanced aspects include dialogue and
logical reasoning similar to those of humans.
As more robots would enter our society it will become useful to distinguish them among each other by robotic biometrics.
Asimo (Honda) humanoid robot
http://en.wikipedia.org/wiki/ASIMO
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Email ◦ Changed the way we communicate in today’s
highly technical world What's wrong with the app of the Internet?
◦ Hard to know who sent an email◦ Spam
Unsolicited email Offensive Fraudulent (phishing) Malicious (viruses, worms, spyware, exploits, DoS)
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Email (E)
Signing AlgorithmPrivate key D
Signature (D(H(E)))
Public key E
If H`(E) = H(E) then message is authentic
E
Hash H (MD5, SHA-1, etc)
D(H(E)) Hash H
H`(E) H(E)
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PEM (Privacy Enhanced Mail) [3] – mid 1980◦ ASCII email messages◦ No centralized public key directory◦ Single root to issue CAs (Certificate Authority)
S/MIME (Secure Multipurpose Internet Mail Extension) [4] ◦ Accommodate any number of trusted CAs
PGP (Pretty Good Privacy) [5]◦ Web of trust◦ Widely used
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Garfinkel [6] presented a new approach to solve most of the usability issues
Used only for encryption Outgoing email
◦ Looks up users public keys in a local database◦ Appends the user’s public key to the email header
Incoming email◦ Stores public keys found in the email header
Vulnerable to man-in-the-middle attacks
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Brown and Snow [7] presented a similar approach but adds digital signatures
Proxy-based approach sitting between the mail client and mail server
Encrypts and signs all outgoing emails Decrypts and verifies all incoming emails
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Idea◦ Use fingerprints instead of private keys
Primary goals◦ Secure access to email accounts◦ Provide an easier way to sign and verify emails◦ Solve the usability issues
Implemented as an email client called SEFR SEFR asks you to present your fingerprint
◦ When you access it and try to view your inbox◦ When you try to send an email
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Components◦ Database: used to store user’s fingerprints and
account information dbs2.cpsc.ucalgary.ca
◦ Enroller: used to enroll new users◦ Receiver: used to download the user’s inbox
Using POP (Post Office Protocol) [1] Gmail’s POP server – pop.gmail.com Port 995
◦ Sender: used to send emails Using SMTP (Simple Mail Transfer Protocol) [2] Gmail’s SMTP server – smtp.gmail.com Port 465
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Accounts on Gmail◦ Two accounts were created for testing and
experimentation purposes amaobied sefr.obied
Issues◦ Gmail servers requires the use of SSL
OpenSSL Base 64 encoding
◦ Fingerprint scanner in the BT lab No API Used fingerprint image paths
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Signing messages◦ When a user tries to send an email, SEFR asks the
user to present his/her fingerprint. If the fingerprint is stored in the database, SEFR does the following: Transforms the email message (e.g., get rid of
newlines, tabs, spaces, etc) Create a hash using SHA-1 of the transformed
message Store the sender’s email address, receiver’s email
address and hash in the database
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Verifying messages◦ When SEFR tries to verify an email, SEFR
automatically does the following: Transforms the messages (e.g., get rid of newlines,
tabs, spaces, etc) Creates a hash using SHA-1 of the transformed
message Extracts the sender’s email address, receiver’s email
address from the email header Checks if the sender’s email address is associated
with the receiver’s email address and hash value in the database
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Using biometric authentication to access Web-based system◦ Online banking
Defeating Spam◦ Bill Gates said “Two years from now, spam will be
solved”
The issue of protecting privacy in biometric systems has inspired the area of so-called cancelable biometrics. It was first initiated by The Exploratory Computer Vision Group at IBM T.J. Watson Research Center and published in [2].
Cancelable biometrics aim to enhance the security and privacy of biometric authentication through generation of “deformed“ biometric data, i.e. synthetic biometrics.
Instead of using a true object (finger, face), thefingerprint or face image is intentionally distorted in a
repeatable manner, and this new print or image is used.
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The features of the new generation of lie detectors include:
(a) Architectural characteristics (highly parallel configuration),
(b) Artificial intelligence support of decision making, and
(c) New paradigms (non-contact testing scenario, controlled dialogue
scenarios, flexible source use, and the possibility of interaction through an artificial intelligence supported machine-human interface).
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The idea of modeling biometric data for decision making support
enhancement at checkpoints is explored, in particular, at theBiometric Technologies Laboratory at the University of
Calgary(http://enel.btlab.ucalgary.ca).
Simulators of biometric data are emerging technologies foreducational and training purposes (immigration control,
bankingservice, police, justice, etc.). They emphasize decision-
making skillsin non-standard and extreme situations.
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