˜ e Public Security and Personal Privacy Survey · · 2016-07-22Biometric Technology in Hong...

12 July/August 2016 Copublished by the IEEE Computer and Reliability Societies 1540-7993/16/$33.00 © 2016 IEEE

SECURITY SMORGASBORD

� e Public Security and Personal Privacy Survey:Biometric Technology in Hong Kong

Qing-Yun Li and Lei Zhang | Hong Kong Polytechnic University

Although biometric techniques o� er robust and reliable authentication, they could violate personal privacy when used for public security. � is survey explores Hong Kong residents’ acceptance of biometric authentication and their thoughts on a new biometric method: fi nger-knuckle print recognition.

B iometric techniques are increasingly popular in public security–related applications, such as cus-

toms control, building entrance control, and terror-ist identi� cation. Compared to traditional methods such as keys and identity cards, biometrics o� er much more robust and reliable authentication of individuals. Nonetheless, the personal nature of widely used meth-ods, including � ngerprint, face, iris, retina, palm print, hand geometry, hand vein, and � nger surface,1–8 means that individuals’ personal privacy can be potentially violated when using biometrics for public security. In Western countries, there have been many investiga-tions and debates about the large-scale use of biomet-rics in public security applications. Hong Kong (HK) lacks clear policies about the proper use of biometric technology. For example, in July 2009, the O� ce of the Privacy Commissioner for Personal Data made a state-ment on biometrics’ inadequacy as a means for access control and a� endance management. Moreover, some legislative councilors have indicated that HK’s current information security laws and regulations are unclear and outdated.

Our research—supported by an HK government Public Policy Research grant—investigated HK resi-dents’ and organizations’ major concerns about biomet-ric techniques. We also collected information to help biometrics researchers develop new techniques that users will easily accept. A� er discussions with survey design experts, we derived the following study questions:

■ What is the central factor when people think about biometric techniques?

■ What subgroups and modularity exist in people’s concerns?

■ What are the pa� erns of interaction between subgroups? ■ What is the overall structure of people’s opinions?

To answer these questions, we performed descrip-tive statistical, co-word, and social network analyses. Co-word analysis, a prominent bibliometric technique, provides a more intuitive, realistic picture of biometric techniques9–11 and has been widely used in theoreti-cal and empirical studies of technology foresight, for example, environmental acidi� cation, scientometrics,

www.computer.org/security 13

information retrieval, biological safety, autism, stem cell research, modern engineering, chemical engineering, arts, and economics.9,11–16

Survey and Descriptive Statistical AnalysisWe developed a 33-question online and paper survey to investigate the current use of biometric technology in HK society, and HK residents’ acceptance of biomet-ric authentication. Survey items were derived from an extensive review of relevant literature and news articles, and focused on

■ the factors influencing residents’ decisions to adopt biometric verification applications,

■ their understanding of biometric verification applications,

■ their attitudes toward existing biometric technologies (such as fingerprints) and their privacy and data pro-tection concerns, and

■ finger-knuckle print (FKP) verification.17

A total of 500 individuals completed the survey: 400 paper surveys were collected between 17 August 2012 and 30 July 2013, and 100 online surveys were collected between 17 September and 30 December 2012.

In the first part of the survey, we gathered basic infor-mation about the participants to see whether there were

correlations between their preferences and their back-grounds. The questions in the second part helped us determine their knowledge of biometric verification. We then surveyed participants’ opinions about biomet-ric verification and fingerprint verification—the most popular and representative applications nowadays—in the third part. Finally, we asked for participants’ thoughts about the newly developed FKP verification to help fine-tune and optimize the technique.

Results are summarized in Tables 1 through 3. As Table 1 shows, the 287 male and 213 female participants ranged in age from 18 to approximately 53 years old.

Knowledge of Biometric VerificationTo gauge participants’ knowledge of biometric verifica-tion, we presented them with a news article about a man who boarded an international flight in disguise.18 Table 2 shows that most participants (63 percent) believe that biometric methods are more reliable than traditional ones. But they still have concerns about the security, accuracy, and speed of verification methods. Approxi-mately 55 percent believe that biometrics are totally accurate; another 30 percent think that although bio-metrics are probably not completely accurate, they’re accurate enough to be useful in many applications. Our survey also found that participants most value biomet-ric techniques’ security (83 percent), accuracy (79 per-cent), and ease of use (35 percent). Researchers should

Table 1. Profile of survey participants.

Characteristic Result

Age (years) 18 to approximately 53

Sex 287 males and 213 females

Education level 70 percent had a university/college degree or higher

Table 2. Participants’ knowledge of biometric verification.

Question

Response (%)

Yes No No comment

Do you know people who don’t look like the photos on their passport or ID card? 58.4 41.6 NA

From your daily life, do you know what biometric verification is (for example, fingerprint verification, hand geometric verification)?

77.2 22.8 NA

Did you know that some unique biometric features and fingerprint ridge arrangement remain unchanged during an individual’s lifetime?

40.6 59.4 NA

Do you think biometric verification is more reliable than nonbiometric verification (including traditional face-to-face verification)?

63.2 24.6 12.2

Do you believe that biometrics can be totally accurate? 55.8 13.4 30.8

Biometrics will be maintained in secure databases. Would you be willing to have your biometric information cataloged?

53.6 14.8 31.6

14 IEEE Security & Privacy July/August 2016


take these criteria into account when launching verifica-tion techniques. The survey also shows that most par-ticipants (53 percent) are willing to provide biometric information in secure databases for verification.

Fingerprint SecurityAfter reading a news story about stolen fingerprints in China,19 77 percent of participants reported that they think fingerprint recognition technology isn’t reliable and 80 percent that using a fingerprint verification application will make personal fingerprint information susceptible to theft (see Table 3). Therefore, 65 percent of participants would agree to use an extra biometric method to cross-reference fingerprints for higher secu-rity. Although only about half the participants (57 per-cent) had used fingerprint verification previously, most had positive feelings toward this technique.

Participants also read about fingerprint verification via e-Channel, a popular verification service for leaving or entering HK. About 82 percent of participants have

used the e-Channel service, and 39 percent have expe-rienced the e-Channel scanner not being able to verify their fingerprints. Approximately half of the partici-pants don’t think the Immigration Department’s use of e-Channel fingerprint verification is enough, and nearly half aren’t completely satisfied with the security level and speed of the current fingerprint verification system. To improve the security and reliability of e-Channel, 63 percent of users agree that more than one biometric ver-ification method (for example, fingerprint recognition plus iris recognition and facial recognition) should be implemented at border crossings.

Online Finger-Knuckle Print Identification SystemBefore completing the survey, participants were intro-duced to a new biometric authentication system based on FKP imaging.17 The system was developed for online personal authentication. FKP refers to the image pat-tern of the outer surface around the phalange joint of

Table 3. Participants’ understanding of fingerprint security.

Question

Response (%)

Yes No No comment

Do you use fingerprint recognition technology in your daily life? 57.0 43.0 NA

Do you think that current fingerprint recognition technology is reliable? 22.6 77.4 NA

Laptops and thumb drives now normally feature fingerprint recognition security systems. Will this security protection method be a major factor for you when purchasing these products?

61.4 38.6 NA

After reading this news, are you afraid that personal fingerprint information is liable to theft after using fingerprint verification applications?

80.4 19.6 NA

Do you think the fingerprint verification used in banking is safe? 17.4 72.0 10.6

Would you suggest that banks replace the current fingerprint verification by introducing a new biometric verification method?

65.4 29.4 5.2

Have you used the e-Channel service while leaving or entering Hong Kong? 82.4 17.6 NA

Have you ever experienced the e-Channel scanner being unable to verify your fingerprint?

39.2 60.8 NA

What do you think about the speed of e-Channel’s fingerprint verification? Fast: 57.2Moderate: 16.0

Slow: 26.8

NA NA

After reading this news, do you think the Immigration Department’s safeguard measures (e-Channel fingerprint verification) are enough?

45.8 50.6 0.6

Apart from personal privacy concerns, would personal hygiene be a factor in not choosing e-Channel to cross borders? (e-Channel requires physical contact between a thumb and a scanner.)

37.8 62.2 NA

After reading this news, are you satisfied with the e-Channel service’s recent fingerprint verification technology?

46.4 20.0 33.6

To improve e-Channel’s security and reliability, do you agree that more than one biometric verification method (for example, fingerprint recognition plus iris recognition and facial recognition) should be implemented at border crossings?

63.4 23.0 13.6


one’s finger, which is formed by slightly bending the fin-ger knuckle.

As Table 4 shows, 70 percent of participants would prefer technology that doesn’t require physical contact. Specifically, 59 percent would accept using skin texture on finger knuckles as a sample, which is a contact-free verification method. Only 29 percent wouldn’t agree with replacing current fingerprint technology with an FKP imaging system.

Results show that FKP technology could dominate the biometric verification market if it fulfills users’ basic requirements for accuracy, speed, and security. It could be widely used for enforcing security and reliably iden-tifying any individual for the following reasons:

■ FKPs vary widely. No two people have identical knuckle prints.

■ FKPs are highly consistent. A person’s FKP might change in scale but not in relative appearance.

■ FKPs don’t require the finger to contact a surface. ■ A small, inexpensive, and fast FKP imaging device has

already been developed successfully.

Social Network AnalysisTo explore the results more deeply, we also conducted a social network analysis. We specifically investigated network structure, node closeness centrality, and mod-ularity distribution. This allowed us to understand, for example, the structured relationship among the survey parts and the clusters of greatest concern to participants.

Because few survey participants selected “no com-ment,” we included all such responses in the “no” cat-egory for convenient calculation. Co-word analysis reveals the relationship among different questions

and calculates the frequency of the occurrence and co-occurrence of statements. The occurrence fre-quency reflects how many people agree with a ques-tion (with two possible statements: agree and disagree), and the co-occurrence of multiple statements in the same survey reflects the correlation between the statements. The more frequently a pair of answers co-occurs, the more correlated the statements are. For example, if many respondents selected “yes” for question 1 and “yes” for question 2, we can say that the connection between these responses is strong. An equivalence index eij then calculates the statements’ relationship as follows:

2ij

iji j

ce

c c=

⋅ ,

where cij is the number of participants whose statements i and j co-occur, and ci and cj represent the numbers of participants whose statements i and j occur, respec-tively. The more the statements co-occur, the closer eij is to 1; if the statements are never associated, eij equals 0.

Network Overview Figure 1 presents the relation among statements regard-ing the respondents’ general understanding of bio-metric verification. Each node’s size corresponds to its frequency (that is, how many people selected it) and the link width represents the equivalence index among dif-ferent statements.

On the basis of the largest node and its connections with the other nodes in Figure 1, we can conclude that most participants know what biometric verification is,

Table 4. Participants’ reactions to finger-knuckle print identification system.

Questions

Response (%)

Yes No No comment

If there was a new biometric technology that didn’t require physical contact, would you adopt it?

70.6 20.4 29.0

If this new biometric technology required sampling the skin texture of your finger’s first joint, would you accept and adopt this technology?

59.6 40.4 NA

Would you agree with this new biometric technology replacing the e-Channel service’s current fingerprint verification?

53.4 29.2 17.4

Apart from personal verification, how else could this new biometric verification method be implemented?

NA NA NA

If a device, such as a laptop, mobile phone, or thumb drive, featured this new biometric technology, would this be a strong selling point?

57.2 42.8 NA

How much would you be willing to spend [in Hong Kong dollars] to purchase this new biometric technology?

0–100: 66.4 101–200: 21.4 201–300: 12.2

NA NA



believe that biometric methods are more reliable than traditional ones and can be totally accurate, agree that people don’t always look like their passport or ID pho-tos, and are willing to have their biometric information cataloged in a database.

Figure 2 displays the relation structure among the top 10 statements that participants responded to about fingerprint verification security. It shows that most par-ticipants have used the e-Channel service’s fingerprint verification. However, they are afraid that personal

Figure 1. Relation structure for survey questions regarding participants’ general understanding of biometric verification. Node size corresponds to frequency and link width represents the equivalence index among different statements.

Believe that biometrics can be totally accurate

Some friends look like the photos on their passport/ID card

Agree that biometric verification is more reliable than nonbiometric verification (including traditional face-to-face verification)

Willing to have biometric information cataloged in database

Don’t know some biometric features and ridge arrangement remain permanent during one’s lifetime

Know some biometric features and ridge arrangement are unique to each individual

Know what biometric verification is (fingerprint verification, hand geometric verification)

Don’t know what biometric verification is

Don’t agree that recent fingerprint recognition technology is reliable

Some friends don’t look like the photos on their passport/ID card

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fingerprint information is liable to theft after using such applications and don’t think that fingerprint recogni-tion technology is reliable. The strong connections also show that participants agree that more than one bio-metric verification method should be implemented at border crossings.

The largest node in Figure 3 indicates that most participants would prefer a biometric technology that doesn’t need physical contact and would accept and use an FKP technology that samples the skin texture of the first joint of their finger. They would also want this technology to be inexpensive: most report that they would spend HK$0–$100 to purchase such technol-ogy. Most participants also agree that FKP technology should replace the e-Channel service’s current finger-print verification.

Closeness CentralityCloseness centrality, a network node centrality measure, is defined as the inverse of the distance of each node to every other node in the network, which is the sum of dis-tances to all other nodes. Thus, this measure expresses the average distance from each node to every other node in the network. High closeness centrality nodes tend to be important influencers in their local network community.

Normalized scores with nodes are shown in Figure 4. The scores are bound between 0 and 1—it’s 0 if a

node is an isolate, and 1 if a node directly connects to all the others. Figure 4 shows that the statement regard-ing adoption of a new biometric technology to replace e-Channel’s current fingerprint verification is common among the respondents and is close to all the other state-ments. It’s in a key position to monitor network informa-tion flow—it has the best visibility in the subnetwork.

Modularity Structure AnalysisModularity measures the structure of networks or graphs. Specifically, it measures the strength of net-works divided into modules (also called groups, clus-ters, or communities) and the appearance of densely connected groups of vertices with only sparser connec-tions between groups. We used the Clauset-Newman-Moore algorithm in our study.20

The modularity structure in Figure 5 shows two groups: people who don’t care about biometric verifica-tion technology and don’t want to use the new technol-ogy, and people who want to use the new technology and would spend up to $300 to purchase it.

Figure 6 displays nodes for two other clear modular-ity groups: one containing people who know about and trust biometric verification technology, and the other, people who believe the opposite.

Finally, Figure 7 shows nodes separated into two modularity groups—those who have experience with

Figure 2. Relation structure for 10 survey questions regarding fingerprint verification. Most participants have used the e-Channel service’s fingerprint verification. However, they are afraid that personal fingerprint information is liable to theft after using such applications and don’t think that fingerprint recognition technology is reliable.

Personal hygiene isn’t a factor in choosing e-Channel to cross borders

Agree that more than one biometric verification method (fingerprint recognition plus iris recognition and facial recognition)should be implemented at border crossings

�e e-Channel scanner never failed to verify user’s fingerprint

Afraid personal fingerprint information is liable to theft after using fingerprint verification applications

Don’t think the fingerprint verification used in banking is safe

Spend $0 on buying products with fingerprint security verificationDon’t think the recent fingerprint recognition technology is reliable

Suggest banks replace the current fingerprint verification by inventing or introducing new biometric verification methods

�e security protection method is a major factor when purchasing laptops and thumb drives

Used e-Channel service while leaving or entering Hong Kong



e-Channel’s fingerprint verification and those who don’t. To present the modularity more clearly, we removed rarely chosen statements. This figure also high-lights that people who have used the e-Channel finger-print verification service would prefer to spend $50 or less on a fingerprint verification product.

T his work can help biometrics researchers under-stand HK residents’ and organizations’ major

concerns regarding biometrics technology adoption as well as provide them with valuable information for improving and developing new biometric techniques. Moreover, this study could help support the govern-ment’s decisions regarding the future deployment of biometric technologies in HK.

AcknowledgmentsHong Kong Research Grants Council Public Policy Research grant PolyU5019-PPR-11 supported this work.

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10. S. Hsin-Ning and L. Pei-Chun, “Mapping Knowledge Structure by Keyword Co-occurrence: A First Look at Journal Papers in Technology Foresight,” Scientometrics,

Figure 3. Relation structure for survey questions regarding public acceptance of a new biometric verification technology. Most participants would prefer a biometric technology that doesn’t need physical contact and would accept and use an FKP technology that samples the skin texture of the first joint of their finger. They would also want this technology to be inexpensive.

Want to use a new biometric technology that doesn’t require physical contact

�e security protection method isn’t a factor when purchasing laptops and thumb drives

Would spend $101–$200 on purchasing this new biometric technology



Would accept and adopt a technology that requires sampling the skin texture of the first joint of a finger

�is new biometric technology is a strong selling point for purchasing

Agree that this new biometric technology should be adopted to replace the current fingerprint verification on the e-Channel service

Don’t agree that this new biometric technology should be adopted to replace the current fingerprint verification on the e-Channel service

Don’t want to use a new biometric technology that doesn’t require physical contact

Wouldn’t accept and adopt a technology that requires sampling the skin texture of the first joint of a finger


vol. 85, no. 1, 2010, pp. 65–79.11. J.P. Courtial, “A Coword Analysis of Scientometrics,”

Scientometrics, vol. 31, no. 3, 1994, pp. 251–260.

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Figure 4. Closeness centrality regarding acceptance of a new biometric verification technology. The statement regarding adoption of a new biometric technology to replace e-Channel’s current fingerprint verification is common among the respondents and is close to all the other statements. It’s in a key position to monitor network information flow—it has the best visibility in the subnetwork.












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in Stem Cells Field Based on Subject Heading Weighting,” Scientometrics, vol. 88, no. 1, 2011, pp. 133–144.

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Figure 5. Modularity structure regarding acceptance of a new biometric verification technology. Two modularity group nodes emerge: G1 is people who don’t care about biometric verification technology and don’t want to use the new technology, and G2 is people who want to use the new technology and would spend up to $300 to purchase it.











G1

G2


Figure 6. Modularity structure for participants’ general understanding of biometric verification. There are two modularity group nodes: G1 contains people who know about and trust biometric verification technology, and G2 includes people who believe the opposite.

Don’t know what biometric verification is

Know what biometric verification is (fingerprint verification, hand geometric verification)

Willing to have biometric information cataloged in database

Not willing to have biometrics information cataloged in database

Don’t agree that recent fingerprint recognition technology is reliable

Some friends don’t look like the photos on their passport/ID card

Some friends look like the photos on their passport/ID card

Don’t believe that biometrics can be totally accurateBelieve that biometrics can be totally accurate

G1G2Know some biometric features and ridge arrangement are unique to each individual

Agree that biometric verification is more reliable than nonbiometric verification(including traditionalface-to-face verification)

Don’t know some biometric features and ridge arrangement remain permanentduring one’s lifetime


J. American Society for Information Science, vol. 24, no. 4, 2007, pp. 265–269.

17. L. Zhang et al., “Online Finger-Knuckle-Print Verification for Personal Authentication,” Pattern Recognition, vol. 43, no. 7, 2010, pp. 2560–2571.

18. S. Zamost, “Exclusive: Man in Disguise Boards Interna-tional Flight,” CNN, 5 Nov. 2010; http://edition.cnn.com /2010/WORLD/americas/11/04/canada.disguised .passenger.

19. “Stolen Fingerprints in China,” China Times, 2010; www .chinatimes.cc/article/12368.html.

20. A. Clauset, M.E.J. Newman, and C. Moore, “Finding Community Structure in Very Large Networks,” Physi-cal Review E, vol. 70, no. 066111, 2004; http://dx.doi.org /10.1103/PhysRevE.70.066111.

Qing-Yun Li is a PhD student in the Department of Computing at the Hong Kong Polytechnic University and an IT officer with the University of Hong Kong. His research interests include pattern recognition, sequential pattern mining, context mining, and big data visualization. Li received an MSc in pattern rec-ognition from Northeastern University, China. Con-tact him at [email protected].

Lei Zhang is a professor in the Department of Com-puting at the Hong Kong Polytechnic University. His research interests include computer vision, pattern recognition, image and video processing, and biometrics. Zhang received PhD degrees in control theory and engineering from Northwest-ern Polytechnical University, China. He’s an associ-ate editor of IEEE Transactions on Image Processing, IEEE Transactions on Circuits and Systems for Video

Technology, and Image and Vision Computing. He’s published more than 200 papers and was selected by Thomson Reuters as a 2015 highly cited researcher. Contact him at [email protected].

Figure 7. Simplified modularity structure for fingerprint verification security, including those who have experience with e-Channel’s fingerprint verification and those who don’t.

G1

G2

Personal hygiene isn’t a factor in choosing e-Channel to cross bordersAgree that more than one biometric verification method (fingerprint recognition plus iris recognition and facial recognition)

should be implemented at border crossings

�e speed of fingerprint verification of e-Channels is fast

Used e-Channel service while leaving or entering Hong Kong

Don’t think that fingerprint verification technology is reliable

Don’t think the fingerprint verification used in banking is safe

Spend $0 on buying products with fingerprint security verification

Don’t think the safeguard measures by the Immigration Department (e-Channel fingerprint verification) are enough

Suggest banks replace the current fingerprint verification by inventing or introducing new biometric verification methods

Satisfied with recent fingerprint verification technology of the e-Channel service

�e security protection method is a major factor when purchasing laptopsand thumb drives

�e e-Channel scanner never failed to verify user’s fingerprint

Never use fingerprint recognition technology in daily life

Afraid personal fingerprint information is liable to theft after using fingerprint verification applications

Agree that the safeguard measures by the Immigration Department (e-Channel fingerprint verification) are enough

Have experienced fingerprint recognition technology in daily life

Level: PhD degree

Maximum employment: 38 hours per week (1 FTE)

Duration of contract: Fixed appointment

Salary scale: € 5219 to € 7599 per month gross

Contact Prof. R. L. Lagendijk +31 (0)15-2783731 [email protected]

For more information and the requirements, visit: www.jobsindelft.com or http://cys.ewi.tudelft.nl/cys/vacancies

Associate/Full Professor of Cyber Security The cyber security section of the Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) focuses on network security, secure data processing, and situation awareness in cyberspace. The section’s research and education portfolio is rich and deals with several perspectives on cyber security. We value the diversity of our portfolio within the scope of theory and engineering of cyber security for distributed systems and networks in a socio-technical context.

The Assoc./Full Professor of cyber security will function as the mainstay for cyber security research and education, without assuming that (s)he is expert in all aspects of the section’s scope. (S)he will be employed at the EEMCS Faculty and will continue the commenced strategy to leverage the complementary expertise at the Faculties of EEMCS and Technology, Policy and Management (TPM). The aim is the creation of joint research projects as well as education and technology transfer activities, thus combining the computer science and socio-technical perspective on cyber security.

˜ e Public Security and Personal Privacy Survey · · 2016-07-22Biometric Technology in Hong...

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