STROBE Actively Securing Wireless Communications using Zero-Forcing - PowerPoint Presentation

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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.