5 research outputs found
Vulnerability analysis of cyber-behavioral biometric authentication
Research on cyber-behavioral biometric authentication has traditionally assumed naΓ―ve (or zero-effort) impostors who make no attempt to generate sophisticated forgeries of biometric samples. Given the plethora of adversarial technologies on the Internet, it is questionable as to whether the zero-effort threat model provides a realistic estimate of how these authentication systems would perform in the wake of adversity. To better evaluate the efficiency of these authentication systems, there is need for research on algorithmic attacks which simulate the state-of-the-art threats.
To tackle this problem, we took the case of keystroke and touch-based authentication and developed a new family of algorithmic attacks which leverage the intrinsic instability and variability exhibited by users\u27 behavioral biometric patterns. For both fixed-text (or password-based) keystroke and continuous touch-based authentication, we: 1) Used a wide range of pattern analysis and statistical techniques to examine large repositories of biometrics data for weaknesses that could be exploited by adversaries to break these systems, 2) Designed algorithmic attacks whose mechanisms hinge around the discovered weaknesses, and 3) Rigorously analyzed the impact of the attacks on the best verification algorithms in the respective research domains.
When launched against three high performance password-based keystroke verification systems, our attacks increased the mean Equal Error Rates (EERs) of the systems by between 28.6% and 84.4% relative to the traditional zero-effort attack.
For the touch-based authentication system, the attacks performed even better, as they increased the system\u27s mean EER by between 338.8% and 1535.6% depending on parameters such as the failure-to-enroll threshold and the type of touch gesture subjected to attack. For both keystroke and touch-based authentication, we found that there was a small proportion of users who saw considerably greater performance degradation than others as a result of the attack. There was also a sub-set of users who were completely immune to the attacks.
Our work exposes a previously unexplored weakness of keystroke and touch-based authentication and opens the door to the design of behavioral biometric systems which are resistant to statistical attacks
ΠΠΎΠ»ΠΎΠ΄Π΅ΠΆΡ ΠΈ ΡΠΎΠ²ΡΠ΅ΠΌΠ΅Π½Π½ΡΠ΅ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΎΠ½Π½ΡΠ΅ ΡΠ΅Ρ Π½ΠΎΠ»ΠΎΠ³ΠΈΠΈ: ΡΠ±ΠΎΡΠ½ΠΈΠΊ ΡΡΡΠ΄ΠΎΠ² XVI ΠΠ΅ΠΆΠ΄ΡΠ½Π°ΡΠΎΠ΄Π½ΠΎΠΉ Π½Π°ΡΡΠ½ΠΎ-ΠΏΡΠ°ΠΊΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΊΠΎΠ½ΡΠ΅ΡΠ΅Π½ΡΠΈΠΈ ΡΡΡΠ΄Π΅Π½ΡΠΎΠ², Π°ΡΠΏΠΈΡΠ°Π½ΡΠΎΠ² ΠΈ ΠΌΠΎΠ»ΠΎΠ΄ΡΡ ΡΡΡΠ½ΡΡ , 3-7 Π΄Π΅ΠΊΠ°Π±ΡΡ 2018 Π³., Π³. Π’ΠΎΠΌΡΠΊ
Π‘Π±ΠΎΡΠ½ΠΈΠΊ ΡΠΎΠ΄Π΅ΡΠΆΠΈΡ Π΄ΠΎΠΊΠ»Π°Π΄Ρ, ΠΏΡΠ΅Π΄ΡΡΠ°Π²Π»Π΅Π½Π½ΡΠ΅ Π½Π° XVI ΠΠ΅ΠΆΠ΄ΡΠ½Π°ΡΠΎΠ΄Π½ΠΎΠΉ Π½Π°ΡΡΠ½ΠΎ-ΠΏΡΠ°ΠΊΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΊΠΎΠ½ΡΠ΅ΡΠ΅Π½ΡΠΈΠΈ ΡΡΡΠ΄Π΅Π½ΡΠΎΠ², Π°ΡΠΏΠΈΡΠ°Π½ΡΠΎΠ² ΠΈ ΠΌΠΎΠ»ΠΎΠ΄ΡΡ
ΡΡΠ΅Π½ΡΡ
Β«ΠΠΎΠ»ΠΎΠ΄Π΅ΠΆΡ ΠΈ ΡΠΎΠ²ΡΠ΅ΠΌΠ΅Π½Π½ΡΠ΅ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΎΠ½Π½ΡΠ΅ ΡΠ΅Ρ
Π½ΠΎΠ»ΠΎΠ³ΠΈΠΈΒ», ΠΏΡΠΎΡΠ΅Π΄ΡΠ΅ΠΉ Π² Π’ΠΎΠΌΡΠΊΠΎΠΌ ΠΏΠΎΠ»ΠΈΡΠ΅Ρ
Π½ΠΈΡΠ΅ΡΠΊΠΎΠΌ ΡΠ½ΠΈΠ²Π΅ΡΡΠΈΡΠ΅ΡΠ΅ Π½Π° Π±Π°Π·Π΅ ΠΠ½ΠΆΠ΅Π½Π΅ΡΠ½ΠΎΠΉ ΡΠΊΠΎΠ»Ρ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΎΠ½Π½ΡΡ
ΡΠ΅Ρ
Π½ΠΎΠ»ΠΎΠ³ΠΈΠΉ ΠΈ ΡΠΎΠ±ΠΎΡΠΎΡΠ΅Ρ
Π½ΠΈΠΊΠΈ. ΠΠ°ΡΠ΅ΡΠΈΠ°Π»Ρ ΡΠ±ΠΎΡΠ½ΠΈΠΊΠ° ΠΎΡΡΠ°ΠΆΠ°ΡΡ Π΄ΠΎΠΊΠ»Π°Π΄Ρ ΡΡΡΠ΄Π΅Π½ΡΠΎΠ², Π°ΡΠΏΠΈΡΠ°Π½ΡΠΎΠ² ΠΈ ΠΌΠΎΠ»ΠΎΠ΄ΡΡ
ΡΡΠ΅Π½ΡΡ
, ΠΏΡΠΈΠ½ΡΡΡΠ΅ ΠΊ ΠΎΠ±ΡΡΠΆΠ΄Π΅Π½ΠΈΡ Π½Π° ΡΠ΅ΠΊΡΠΈΡΡ
: Β«ΠΠΎΠΌΠΏΡΡΡΠ΅ΡΠ½ΠΎΠ΅ ΠΌΠΎΠ΄Π΅Π»ΠΈΡΠΎΠ²Π°Π½ΠΈΠ΅ ΠΈ ΠΈΠ½ΡΠ΅Π»Π»Π΅ΠΊΡΡΠ°Π»ΡΠ½ΡΠΉ Π°Π½Π°Π»ΠΈΠ· Π΄Π°Π½Π½ΡΡ
Β», Β«ΠΠ²ΡΠΎΠΌΠ°ΡΠΈΠ·Π°ΡΠΈΡ ΠΈ ΡΠΏΡΠ°Π²Π»Π΅Π½ΠΈΠ΅ Π² ΡΠ΅Ρ
Π½ΠΈΡΠ΅ΡΠΊΠΈΡ
ΡΠΈΡΡΠ΅ΠΌΠ°Ρ
Β», Β«Π ΠΎΠ±ΠΎΡΠΎΡΠ΅Ρ
Π½ΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΠΈ ΠΌΠ΅Ρ
Π°ΡΡΠΎΠ½Π½ΡΠ΅ ΡΠΈΡΡΠ΅ΠΌΡΒ», Β«Π¦ΠΈΡΡΠΎΠ²ΠΈΠ·Π°ΡΠΈΡ, IT ΠΈ ΡΠΈΡΡΠΎΠ²Π°Ρ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΠΊΠ°Β», Β«ΠΠΎΠΌΠΏΡΡΡΠ΅ΡΠ½Π°Ρ Π³ΡΠ°ΡΠΈΠΊΠ° ΠΈ Π΄ΠΈΠ·Π°ΠΉΠ½Β». Π‘Π±ΠΎΡΠ½ΠΈΠΊ ΠΏΡΠ΅Π΄Π½Π°Π·Π½Π°ΡΠ΅Π½ Π΄Π»Ρ ΡΠΏΠ΅ΡΠΈΠ°Π»ΠΈΡΡΠΎΠ² Π² ΠΎΠ±Π»Π°ΡΡΠΈ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΎΠ½Π½ΡΡ
ΡΠ΅Ρ
Π½ΠΎΠ»ΠΎΠ³ΠΈΠΉ, ΡΡΡΠ΄Π΅Π½ΡΠΎΠ² ΠΈ Π°ΡΠΏΠΈΡΠ°Π½ΡΠΎΠ² ΡΠΎΠΎΡΠ²Π΅ΡΡΡΠ²ΡΡΡΠΈΡ
ΡΠΏΠ΅ΡΠΈΠ°Π»ΡΠ½ΠΎΡΡΠ΅ΠΉ
ΠΠΎΠ»ΠΎΠ΄Π΅ΠΆΡ ΠΈ ΡΠΎΠ²ΡΠ΅ΠΌΠ΅Π½Π½ΡΠ΅ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΎΠ½Π½ΡΠ΅ ΡΠ΅Ρ Π½ΠΎΠ»ΠΎΠ³ΠΈΠΈ: ΡΠ±ΠΎΡΠ½ΠΈΠΊ ΡΡΡΠ΄ΠΎΠ² XVI ΠΠ΅ΠΆΠ΄ΡΠ½Π°ΡΠΎΠ΄Π½ΠΎΠΉ Π½Π°ΡΡΠ½ΠΎ-ΠΏΡΠ°ΠΊΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΊΠΎΠ½ΡΠ΅ΡΠ΅Π½ΡΠΈΠΈ ΡΡΡΠ΄Π΅Π½ΡΠΎΠ², Π°ΡΠΏΠΈΡΠ°Π½ΡΠΎΠ² ΠΈ ΠΌΠΎΠ»ΠΎΠ΄ΡΡ ΡΡΡΠ½ΡΡ , 3-7 Π΄Π΅ΠΊΠ°Π±ΡΡ 2018 Π³., Π³. Π’ΠΎΠΌΡΠΊ
Π‘Π±ΠΎΡΠ½ΠΈΠΊ ΡΠΎΠ΄Π΅ΡΠΆΠΈΡ Π΄ΠΎΠΊΠ»Π°Π΄Ρ, ΠΏΡΠ΅Π΄ΡΡΠ°Π²Π»Π΅Π½Π½ΡΠ΅ Π½Π° XVI ΠΠ΅ΠΆΠ΄ΡΠ½Π°ΡΠΎΠ΄Π½ΠΎΠΉ Π½Π°ΡΡΠ½ΠΎ-ΠΏΡΠ°ΠΊΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΊΠΎΠ½ΡΠ΅ΡΠ΅Π½ΡΠΈΠΈ ΡΡΡΠ΄Π΅Π½ΡΠΎΠ², Π°ΡΠΏΠΈΡΠ°Π½ΡΠΎΠ² ΠΈ ΠΌΠΎΠ»ΠΎΠ΄ΡΡ
ΡΡΠ΅Π½ΡΡ
Β«ΠΠΎΠ»ΠΎΠ΄Π΅ΠΆΡ ΠΈ ΡΠΎΠ²ΡΠ΅ΠΌΠ΅Π½Π½ΡΠ΅ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΎΠ½Π½ΡΠ΅ ΡΠ΅Ρ
Π½ΠΎΠ»ΠΎΠ³ΠΈΠΈΒ», ΠΏΡΠΎΡΠ΅Π΄ΡΠ΅ΠΉ Π² Π’ΠΎΠΌΡΠΊΠΎΠΌ ΠΏΠΎΠ»ΠΈΡΠ΅Ρ
Π½ΠΈΡΠ΅ΡΠΊΠΎΠΌ ΡΠ½ΠΈΠ²Π΅ΡΡΠΈΡΠ΅ΡΠ΅ Π½Π° Π±Π°Π·Π΅ ΠΠ½ΠΆΠ΅Π½Π΅ΡΠ½ΠΎΠΉ ΡΠΊΠΎΠ»Ρ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΎΠ½Π½ΡΡ
ΡΠ΅Ρ
Π½ΠΎΠ»ΠΎΠ³ΠΈΠΉ ΠΈ ΡΠΎΠ±ΠΎΡΠΎΡΠ΅Ρ
Π½ΠΈΠΊΠΈ. ΠΠ°ΡΠ΅ΡΠΈΠ°Π»Ρ ΡΠ±ΠΎΡΠ½ΠΈΠΊΠ° ΠΎΡΡΠ°ΠΆΠ°ΡΡ Π΄ΠΎΠΊΠ»Π°Π΄Ρ ΡΡΡΠ΄Π΅Π½ΡΠΎΠ², Π°ΡΠΏΠΈΡΠ°Π½ΡΠΎΠ² ΠΈ ΠΌΠΎΠ»ΠΎΠ΄ΡΡ
ΡΡΠ΅Π½ΡΡ
, ΠΏΡΠΈΠ½ΡΡΡΠ΅ ΠΊ ΠΎΠ±ΡΡΠΆΠ΄Π΅Π½ΠΈΡ Π½Π° ΡΠ΅ΠΊΡΠΈΡΡ
: Β«ΠΠΎΠΌΠΏΡΡΡΠ΅ΡΠ½ΠΎΠ΅ ΠΌΠΎΠ΄Π΅Π»ΠΈΡΠΎΠ²Π°Π½ΠΈΠ΅ ΠΈ ΠΈΠ½ΡΠ΅Π»Π»Π΅ΠΊΡΡΠ°Π»ΡΠ½ΡΠΉ Π°Π½Π°Π»ΠΈΠ· Π΄Π°Π½Π½ΡΡ
Β», Β«ΠΠ²ΡΠΎΠΌΠ°ΡΠΈΠ·Π°ΡΠΈΡ ΠΈ ΡΠΏΡΠ°Π²Π»Π΅Π½ΠΈΠ΅ Π² ΡΠ΅Ρ
Π½ΠΈΡΠ΅ΡΠΊΠΈΡ
ΡΠΈΡΡΠ΅ΠΌΠ°Ρ
Β», Β«Π ΠΎΠ±ΠΎΡΠΎΡΠ΅Ρ
Π½ΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΠΈ ΠΌΠ΅Ρ
Π°ΡΡΠΎΠ½Π½ΡΠ΅ ΡΠΈΡΡΠ΅ΠΌΡΒ», Β«Π¦ΠΈΡΡΠΎΠ²ΠΈΠ·Π°ΡΠΈΡ, IT ΠΈ ΡΠΈΡΡΠΎΠ²Π°Ρ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΠΊΠ°Β», Β«ΠΠΎΠΌΠΏΡΡΡΠ΅ΡΠ½Π°Ρ Π³ΡΠ°ΡΠΈΠΊΠ° ΠΈ Π΄ΠΈΠ·Π°ΠΉΠ½Β». Π‘Π±ΠΎΡΠ½ΠΈΠΊ ΠΏΡΠ΅Π΄Π½Π°Π·Π½Π°ΡΠ΅Π½ Π΄Π»Ρ ΡΠΏΠ΅ΡΠΈΠ°Π»ΠΈΡΡΠΎΠ² Π² ΠΎΠ±Π»Π°ΡΡΠΈ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΎΠ½Π½ΡΡ
ΡΠ΅Ρ
Π½ΠΎΠ»ΠΎΠ³ΠΈΠΉ, ΡΡΡΠ΄Π΅Π½ΡΠΎΠ² ΠΈ Π°ΡΠΏΠΈΡΠ°Π½ΡΠΎΠ² ΡΠΎΠΎΡΠ²Π΅ΡΡΡΠ²ΡΡΡΠΈΡ
ΡΠΏΠ΅ΡΠΈΠ°Π»ΡΠ½ΠΎΡΡΠ΅ΠΉ