Actively Securing Wireless Communications using ZeroForcing Beamforming Narendra Anand Rice University Sung Ju Lee HP Labs Edward Knightly Rice University Motivation Indoors eg ID: 272327
Download Presentation The PPT/PDF document "STROBE" is the property of its rightful owner. Permission is granted to download and print the materials on this web site for personal, non-commercial use only, and to display it on your personal computer provided you do not modify the materials and that you retain all copyright notices contained in the materials. By downloading content from our website, you accept the terms of this agreement.
Slide1
STROBEActively Securing Wireless Communications using Zero-Forcing Beamforming
Narendra AnandRice UniversitySung-Ju LeeHP LabsEdward KnightlyRice UniversitySlide2
Motivation
Indoors (eg. Coffee Shop)
APSlide3
Motivation
Indoors (eg. Coffee Shop)
IU
APSlide4
Motivation
Indoors (eg. Coffee Shop)
IU
E
E
APSlide5
Motivation
Indoors (eg. Coffee Shop)
IU
E
E
APSlide6
Motivation
Indoors (eg. Coffee Shop)
IU
E
E
AP
WEP/WPASlide7
Motivation
Indoors (eg. Coffee Shop)
IU
E
E
AP
Omnidirectional
WEP/WPASlide8
Motivation
Indoors (eg. Coffee Shop)
IU
E
E
AP
Omnidirectional
WEP/WPASlide9
Motivation
Indoors (eg. Coffee Shop)
IU
E
E
AP
Omnidirectional
WEP/WPASlide10
Motivation
Indoors (eg. Coffee Shop)
IU
E
E
AP
Omnidirectional
WEP/WPA
Problem:
Omnidirectional
Transmissions broadcast signal energy everywhere allowing any user in range to overhear the transmission.Slide11
Motivation
Indoors (eg. Coffee Shop)
IU
E
E
APSlide12
Motivation
Indoors (eg. Coffee Shop)
IU
E
E
AP
Potential Solution:
Keep signal away from E with
Single-User Beamforming or
Directional AntennaSlide13
Motivation
Indoors (eg. Coffee Shop)
IU
E
E
AP
Potential Solution:
Keep signal away from E with
Single-User Beamforming or
Directional AntennaSlide14
Motivation
Indoors (eg. Coffee Shop)
IU
E
E
AP
Potential Solution:
Keep signal away from E with
Single-User Beamforming or
Directional Antenna
**
Beampatterns
for
Illustration purposes only.Slide15
E
Motivation
Indoors (
eg
. Coffee Shop)
IU
E
AP
Potential Solution:
Keep signal away from E with
Single-User Beamforming or
Directional Antenna
LOS
**
Beampatterns
for
Illustration purposes only.Slide16
E
Motivation
Indoors (
eg
. Coffee Shop)
IU
E
AP
Potential Solution:
Keep signal away from E with
Single-User Beamforming or
Directional Antenna
Multi-Path
LOS
**
Beampatterns
for
Illustration purposes only.Slide17
E
Motivation
Indoors (
eg
. Coffee Shop)
IU
E
AP
Potential Solution:
Keep signal away from E with
Single-User Beamforming or
Directional Antenna
Multi-Path
LOS
Problem:
Single Target directional methods are agnostic to user locations other than IU. Multi-path effects and knowledge of IU location can be used to compromise the transmission.
**
Beampatterns
for
Illustration purposes only.Slide18
Solution
Slide19
SolutionProblem:
How can we reliably keep eavesdroppers from decoding the IU’s data?
Slide20
SolutionProblem:
How can we reliably keep eavesdroppers from decoding the IU’s data?Solution: Simultaneously Blind (actively interfere) Eavesdroppers while serving the IU.
Slide21
SolutionProblem:
How can we reliably keep eavesdroppers from decoding the IU’s data?Solution: Simultaneously Blind (actively interfere) Eavesdroppers while serving the IU.How: By leveraging the multi-stream/user abilities of recent multi-antenna technologies (802.11n/ac)
Slide22
SolutionProblem:
How can we reliably keep eavesdroppers from decoding the IU’s data?Solution: Simultaneously Blind (actively interfere) Eavesdroppers while serving the IU.How: By leveraging the multi-stream/user abilities of recent multi-antenna technologies (802.11n/ac)AP creates simultaneous streams
Slide23
SolutionProblem:
How can we reliably keep eavesdroppers from decoding the IU’s data?Solution: Simultaneously Blind (actively interfere) Eavesdroppers while serving the IU.How: By leveraging the multi-stream/user abilities of recent multi-antenna technologies (802.11n/ac)AP creates simultaneous streamsUse one for IU
Slide24
SolutionProblem:
How can we reliably keep eavesdroppers from decoding the IU’s data?Solution: Simultaneously Blind (actively interfere) Eavesdroppers while serving the IU.How: By leveraging the multi-stream/user abilities of recent multi-antenna technologies (802.11n/ac)AP creates simultaneous streamsUse one for IUUse remaining to Blind Eavesdroppers
Slide25
SolutionProblem:
How can we reliably keep eavesdroppers from decoding the IU’s data?Solution: Simultaneously Blind (actively interfere) Eavesdroppers while serving the IU.How: By leveraging the multi-stream/user abilities of recent multi-antenna technologies (802.11n/ac)AP creates simultaneous streamsUse one for IUUse remaining to Blind Eavesdroppers
S
TR
O
B
E
Slide26
SolutionProblem:
How can we reliably keep eavesdroppers from decoding the IU’s data?Solution: Simultaneously Blind (actively interfere) Eavesdroppers while serving the IU.How: By leveraging the multi-stream/user abilities of recent multi-antenna technologies (802.11n/ac)AP creates simultaneous streamsUse one for IUUse remaining to Blind Eavesdroppers
S
TR
O
B
E
imultaneous
ansmissions
with
Slide27
SolutionProblem:
How can we reliably keep eavesdroppers from decoding the IU’s data?Solution: Simultaneously Blind (actively interfere) Eavesdroppers while serving the IU.How: By leveraging the multi-stream/user abilities of recent multi-antenna technologies (802.11n/ac)AP creates simultaneous streamsUse one for IUUse remaining to Blind Eavesdroppers
S
TR
O
B
E
imultaneous
ansmissions
with
rthogonally
linded
avesdroppersSlide28
E
STROBE Overview
Indoors (
eg
. Coffee Shop)
IU
E
AP
STROBE
**
Beampatterns
for
Illustration purposes only.Slide29
E
STROBE Overview
Indoors (
eg
. Coffee Shop)
IU
E
AP
STROBE
**
Beampatterns
for
Illustration purposes only.
Blinding
StreamsSlide30
E
STROBE Overview
Indoors (
eg
. Coffee Shop)
IU
E
AP
STROBE
**
Beampatterns
for
Illustration purposes only.
Blinding
StreamsSlide31
E
STROBE Overview
Indoors (
eg
. Coffee Shop)
IU
E
AP
STROBE
**
Beampatterns
for
Illustration purposes only.
Blinding
Streams
STROBE:
Slide32
E
STROBE Overview
Indoors (
eg
. Coffee Shop)
IU
E
AP
STROBE
**
Beampatterns
for
Illustration purposes only.
Blinding
Streams
STROBE:
Leverages existing multi-stream capabilities
Slide33
E
STROBE Overview
Indoors (
eg
. Coffee Shop)
IU
E
AP
STROBE
**
Beampatterns
for
Illustration purposes only.
Blinding
Streams
STROBE:
Leverages existing multi-stream capabilities
Cross-layer approach but requires minimal hardware modification (11n/ac compatible)
Slide34
E
STROBE Overview
Indoors (
eg
. Coffee Shop)
IU
E
AP
STROBE
**
Beampatterns
for
Illustration purposes only.
Blinding
Streams
STROBE:
Leverages existing multi-stream capabilities
Cross-layer approach but requires minimal hardware modification (11n/ac compatible)
Coexists with existing security protocolsSlide35
Background
Zero Forcing Beamforming (ZFBF)Assume 4 Tx Antennas and 3 single-antenna receivers
h
k'
s
– H for each
recv
.
Calculate weights with pseudo-inverse
w
j'
s
“Zero Interference” ConditionSlide36
Orthogonal Blinding
Slide37
Orthogonal BlindingLimited Channel State Information (CSI)
Slide38
Orthogonal BlindingLimited Channel State Information (CSI)
Only know IU’s channel (h vector)
Slide39
Orthogonal BlindingLimited Channel State Information (CSI)
Only know IU’s channel (h vector)Generate orthogonal h vectors using Gram-Schmidt
Slide40
Orthogonal BlindingLimited Channel State Information (CSI)
Only know IU’s channel (h vector)Generate orthogonal h vectors using Gram-Schmidt New H matrix is unitary (pseudo-inverse is complex conjugate transpose)
Slide41
Orthogonal BlindingLimited Channel State Information (CSI)
Only know IU’s channel (h vector)Generate orthogonal h vectors using Gram-Schmidt New H matrix is unitary (pseudo-inverse is complex conjugate transpose)Intended user’s steering weight is equivalent to SUBF
Slide42
Orthogonal BlindingLimited Channel State Information (CSI)
Only know IU’s channel (h vector)Generate orthogonal h vectors using Gram-Schmidt New H matrix is unitary (pseudo-inverse is complex conjugate transpose)Intended user’s steering weight is equivalent to SUBFEase of implementation/integration
Slide43
Orthogonal BlindingLimited Channel State Information (CSI)
Only know IU’s channel (h vector)Generate orthogonal h vectors using Gram-Schmidt New H matrix is unitary (pseudo-inverse is complex conjugate transpose)Intended user’s steering weight is equivalent to SUBFEase of implementation/integrationZFBF systems can use QR-decomposition (followed by backsubstitution) to calculate pseudo-inverse
Slide44
Orthogonal BlindingLimited Channel State Information (CSI)
Only know IU’s channel (h vector)Generate orthogonal h vectors using Gram-Schmidt New H matrix is unitary (pseudo-inverse is complex conjugate transpose)Intended user’s steering weight is equivalent to SUBFEase of implementation/integrationZFBF systems can use QR-decomposition (followed by backsubstitution) to calculate pseudo-inverseQR is used to implement Gram-Schmidt (existing silicon can be re-used for STROBE)Slide45
Experimental MethodologySTROBE implemented in
WARPLab using ZFBF testbed developed in:E. Aryafar, N. Anand, T. Salonidis, and E. Knightly. Design and experimental evaluation of multi-user beamforming in Wireless LANs. In Proc. ACM MobiCom, Chicago, Illinois, September 2010
Performance Metric: Received signal strength (dB)Slide46
Experimental MethodologySlide47
Experimental MethodologyUnrealistic scenario in which Eavesdroppers provide AP with their CSI to be precisely blinded.
Slide48
Experimental Methodology
FairnessNet transmit power equivalent for all schemes Slide49
ExperimentsSlide50
ExperimentsSlide51
ExperimentsSlide52
BaselineSlide53
Baseline
Slide54
Baseline
Slide55
Baseline
Omni
- In range clients receive transmission with high SINR, distance from transmitter is not always a good predictorSlide56
Baseline
Omni - In range clients receive transmission with high SINR, distance from transmitter is not always a good predictor
Slide57
Baseline
Omni - In range clients receive transmission with high SINR, distance from transmitter is not always a good predictor
SUBF – Maximizes SINR at IU but agnostic to signal energy afterwardsSlide58
Baseline
Omni - In range clients receive transmission with high SINR, distance from transmitter is not always a good predictor
SUBF – Maximizes SINR at IU but agnostic to signal energy afterwards
Slide59
Baseline
Omni - In range clients receive transmission with high SINR, distance from transmitter is not always a good predictor
SUBF – Maximizes SINR at IU but agnostic to signal energy afterwards
STROBE – Serves IU with high SINR, restricts E SINR to < 4dBSlide60
Baseline
Omni - In range clients receive transmission with high SINR, distance from transmitter is not always a good predictor
SUBF – Maximizes SINR at IU but agnostic to signal energy afterwards
STROBE – Serves IU with high SINR, restricts E SINR to < 4dB
Slide61
Baseline
Omni - In range clients receive transmission with high SINR, distance from transmitter is not always a good predictor
SUBF – Maximizes SINR at IU but agnostic to signal energy afterwards
STROBE – Serves IU with high SINR, restricts E SINR to < 4dB
CE
– Precise blinding of E comes at the cost of SINR served to IUSlide62
ExperimentsSlide63
Nomadic EavesdropperSlide64
Nomadic Eavesdropper
Omni
(dB)Slide65
Nomadic Eavesdropper
SUBF
Omni
(dB)Slide66
Nomadic Eavesdropper
DA
Omni
SUBF
(dB)Slide67
Nomadic Eavesdropper
STROBE
Omni
SUBF
DA
(dB)Slide68
ConclusionsVerified STROBE’s performance in indoor environments
Functionality does not degrade with relative eavesdropper positionSTROBE’s performance depends on indoor multi-path effectsVerified by outdoor testingSTROBE successfully withstands attacks from a nomadic eavesdropperOn average, STROBE provides the IU with a 15 dB stronger signal than the eavesdropperSlide69
All ExperimentsSlide70
Orthogonal Blinding
Slide71
Orthogonal BlindingLimited Channel State Information (CSI)
Slide72
Orthogonal BlindingLimited Channel State Information (CSI)
Only know IU’s channel (h vector)
Slide73
Orthogonal BlindingLimited Channel State Information (CSI)
Only know IU’s channel (h vector)Generate orthogonal h vectors using Gram-Schmidt Orthonormalization process
Slide74
Orthogonal BlindingLimited Channel State Information (CSI)
Only know IU’s channel (h vector)Generate orthogonal h vectors using Gram-Schmidt Orthonormalization processNew H matrix is unitary (pseudo-inverse is complex conjugate transpose)
Slide75
Orthogonal BlindingLimited Channel State Information (CSI)
Only know IU’s channel (h vector)Generate orthogonal h vectors using Gram-Schmidt Orthonormalization processNew H matrix is unitary (pseudo-inverse is complex conjugate transpose)Intended user’s steering weight is equivalent to SUBF
Slide76
Orthogonal BlindingLimited Channel State Information (CSI)
Only know IU’s channel (h vector)Generate orthogonal h vectors using Gram-Schmidt Orthonormalization processNew H matrix is unitary (pseudo-inverse is complex conjugate transpose)Intended user’s steering weight is equivalent to SUBFEase of implementation/integration
Slide77
Orthogonal BlindingLimited Channel State Information (CSI)
Only know IU’s channel (h vector)Generate orthogonal h vectors using Gram-Schmidt Orthonormalization processNew H matrix is unitary (pseudo-inverse is complex conjugate transpose)Intended user’s steering weight is equivalent to SUBFEase of implementation/integration
ZFBF systems can use QR-decomposition (followed by backsubstitution) to calculate pseudo-inverse Slide78
Orthogonal BlindingLimited Channel State Information (CSI)
Only know IU’s channel (h vector)Generate orthogonal h vectors using Gram-Schmidt Orthonormalization processNew H matrix is unitary (pseudo-inverse is complex conjugate transpose)Intended user’s steering weight is equivalent to SUBFEase of implementation/integration
ZFBF systems can use QR-decomposition (followed by backsubstitution) to calculate pseudo-inverseQR is used to implement Gram-Schmidt (existing silicon can be re-used for STROBE)Slide79
ExperimentsSlide80
Relative E Location: ProximitySlide81
Relative E Location: Proximity
Slide82
Relative E Location: Proximity
Omni - High SINR variability indicator of multipath effectsSlide83
Relative E Location: Proximity
Omni/SUBF - High SINR variability indicator of multipath effectsSlide84
Relative E Location: Proximity
Omni/SUBF
- High SINR variability indicator of multipath effects
Slide85
Relative E Location: Proximity
Omni/SUBF
- High SINR variability indicator of multipath effects
CE –
Precise blinding regardless of distance, consistent results regardless of multi-pathSlide86
Relative E Location: Proximity
Omni/SUBF
- High SINR variability indicator of multipath effects
CE –
Precise blinding regardless of distance, consistent results regardless of multi-path
Slide87
Relative E Location: Proximity
Omni/SUBF
- High SINR variability indicator of multipath effects
CE –
Precise blinding regardless of distance, consistent results regardless of multi-path
STROBE –
Mildly affected at close distances, consistent results regardless of multi-path, provides far greater SINR to IU than CESlide88
ExperimentsSlide89
Relative E Location: In-LineSlide90
Relative E Location: In-Line
Slide91
Relative E Location: In-Line
Omni – SINR not predicted by location in line
Slide92
Relative E Location: In-Line
Omni – SINR not predicted by location in line
SUBF – Single-target directional scheme; to defeat, get in LOS
Slide93
Relative E Location: In-Line
Omni – SINR not predicted by location in line
SUBF – Single-target directional scheme; to defeat, get in LOS
STROBE
– Multiple eavesdroppers in direct LOS between IU and Tx are successfully blinded
Slide94
Relative E Location: In-Line
Omni – SINR not predicted by location in line
SUBF – Single-target directional scheme; to defeat, get in LOS
STROBE
– Multiple eavesdroppers in direct LOS between IU and Tx are successfully blinded
CE
– Precise blinding comes at a price. Slide95
ExperimentsSlide96
Verifying necessity of Multi-PathSlide97
Verifying necessity of Multi-PathSlide98
Verifying necessity of Multi-Path
Outdoors
Slide99
Verifying necessity of Multi-Path
Outdoors
Multi-Stream methods fail outdoors
Slide100
Verifying necessity of Multi-Path
Outdoors
Multi-Stream methods fail outdoors
STROBE becomes directional
Slide101
Verifying necessity of Multi-Path
Outdoors
Multi-Stream methods fail outdoors
STROBE becomes directional
CE completely failsSlide102
Backup SlidesSlide103
Prior Work
Slide104
Prior WorkBeamforming-based multiple AP cooperation
Slide105
Prior WorkBeamforming-based multiple AP cooperation
Information theoretic multi-antenna security
Slide106
Prior WorkBeamforming-based multiple AP cooperation
J. Carey and D. Grunwald. Enhancing WLAN security with smart antennas: a physical layer response for information assurance. In Proc. IEEE Vehicular Technology Conference, September 2004. Information theoretic multi-antenna security
Slide107
Prior WorkBeamforming-based multiple AP cooperation
J. Carey and D. Grunwald. Enhancing WLAN security with smart antennas: a physical layer response for information assurance. In Proc. IEEE Vehicular Technology Conference, September 2004.S. Lakshmanan, C. Tsao, R. Sivakumar, and K. Sundaresan. Securing Wireless Data Networks against Eavesdropping using Smart Antennas. In The 28th International Conference on Distributed Computing Systems, Beijing, China, June 2008.Information theoretic multi-antenna security
Slide108
Prior WorkBeamforming-based multiple AP cooperation
J. Carey and D. Grunwald. Enhancing WLAN security with smart antennas: a physical layer response for information assurance. In Proc. IEEE Vehicular Technology Conference, September 2004.S. Lakshmanan, C. Tsao, R. Sivakumar, and K. Sundaresan. Securing Wireless Data Networks against Eavesdropping using Smart Antennas. In The 28th International Conference on Distributed Computing Systems, Beijing, China, June 2008.Information theoretic multi-antenna security S. Goel and R. Negi. Guaranteeing secrecy using artificial noise. IEEE Transactions on Communications, 7(6):2180–2189, June 2008.
Slide109
Prior WorkBeamforming-based multiple AP cooperation
J. Carey and D. Grunwald. Enhancing WLAN security with smart antennas: a physical layer response for information assurance. In Proc. IEEE Vehicular Technology Conference, September 2004.S. Lakshmanan, C. Tsao, R. Sivakumar, and K. Sundaresan. Securing Wireless Data Networks against Eavesdropping using Smart Antennas. In The 28th International Conference on Distributed Computing Systems, Beijing, China, June 2008.Information theoretic multi-antenna security S. Goel and R. Negi. Guaranteeing secrecy using artificial noise. IEEE Transactions on Communications, 7(6):2180–2189, June 2008.
L. Dong, Z. Han, A. Petropulu, and V. Poor. Improving wireless physical layer security via cooperating relays. IEEE Transactions on Signal Processing, 58(3):1875–1888, March 2010.