CN100583765C - Biological safety level model and its setting method and device - Google Patents
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Abstract
The present invention discloses a biosafety level template and the setting method and a device; the present invention is used for promoting the security of the biological identification process. The template comprises the biosafety level and biological parameter information; the biosafety level comprises the parameter information unique identifier; the biological parameter comprises the biological types and/or biological algorithm and/or algorithmic error match value. The method comprises the strategy for obtaining the user choice; the obtainment of biological parameter information; the confirmation of security level value; distribution of the parameter information unique identification for the biosafety level template; the formation of biosafety level templates according to the parameter information unique identification, security level, strategy and biological parameter information. In addition, the present invention also correspondingly provides a setting device. The present invention can effectively promote the security of the identification process.
Description
Technical field
The present invention relates to the data security field, relate in particular to a kind of biological safety level model and establishing method thereof and device.
Background technology
Along with the network fast development, network more and more merges with people's work and life, E-Government, teleworking, ecommerce have obtained a large amount of application, Web bank, online transactions etc. are also more general, therefore the authentication to the people also just seems extremely important, the first step that it or even other work begin.Authenticate in the conventional cipher mode, exist and to forget easily, the defective that is difficult to remedy such as stolen by others easily, fail safe can't be satisfactory, to such an extent as to network fraud in recent years, the phenomenon of account takeover is increasing.Therefore, the personal information guarantee of the higher security arrangement of development, authentication mechanism is imperative.
Biometrics identification technology is ripe gradually in recent years, and the particular surroundings of network ID authentication, and biometrics identification technology is applied in the authentication, utilizes the characteristics such as uniqueness, stability of biological characteristic, for information security provides guarantee.
Biological identification technology is meant and utilizes mankind itself's physiology or behavioural characteristic to carry out a kind of technology of identity validation, as fingerprint recognition, iris recognition, shape of face identification, train of thought identification etc.
Biometric authentication system must be created the biological characteristic masterplate earlier, and the masterplate of the biological attribute data that will newly collect when carrying out authentication and registered in advance storage mates, and sees whether matching result comes judged result in the effective range.
The fail safe of biometric authentication system represents that system's opposing is to the ability of any illegal attempt by authentication.To the destruction of biosystem fail safe from two aspects: imperfection that biosystem is intrinsic and illegal attack.These two kinds of factors all may cause a Verification System that the proof of identification of a mistake is provided, and accept disabled user's identity mistakenly.For the resource that is subjected to this Verification System protection, this will cause unauthorized access or destruction.
See also Fig. 1, biological authentification system may be subjected to the following attack:
1, the biological characteristic (spoofing attack) of forgery is provided in sensor side: what offer transducer is genuine biological the sign, but obtaining of characterizing is illegal, as plastic cement finger, the iris image printed etc.
2, resubmit the digital biometric data (Replay Attack) of storage in the past: walk around transducer, the digital biometric data of registration is in the past directly submitted to feature extractor.
3, the result of Cover Feature Extraction device: utilize trojan horse the result of the direct Cover Feature Extraction device of previously selected masterplate.
4, distort the biological characteristic statement: in the transmission between feature extractor and adaptation module, use the feature set of forging to replace the masterplate that obtains after the real acquisition process.
5, destroy adaptation: use trojan horse in matching module, to produce matching score.
6, attack the passage of depositing prestore masterplate and adaptation: in the transmission of the database of depositing masterplate and matching module, replace the masterplate that prestores with the masterplate of forging.
7, distort masterplate: revise the masterplate of depositing in the database (no matter whether being distributed system) in advance, what used so afterwards has been the masterplate of a forgery.
8, cover the result of decision: use the result of trojan horse modification or Replacement Decision module, or in Replacement Decision result in application apparatus transmission way.
In above-mentioned attack, 2～8 attack occurs in biosystem inside, wherein 2,4,6,8 mostly occurs in distributed system.
There are a lot of safe practices to be used to defend these attacks at present, in simple terms, guarantee that channel security and data encryption can defend the attack that takes place in the transmission course;
Solving the most frequently used method of Replay Attack is to increase timestamp in data, perhaps adopts password-acknowledgement mechanism when submitting biological characteristic to;
The software that anti-Trojan and virus are installed can prevent that trojan horse from disturbing verification process.To in the distributed biological authentification system between each parts data transmission safety protection some international standards or draft have been arranged, as ISO/IEC CD 24761.
But some above defense schemes all are from the Verification System outside, and do not set out by the aspect that improves the fail safe of data own, so the fail safe of biological identification process can not get effective raising.
Summary of the invention
The technical problem to be solved in the present invention provides a kind of biological safety level model and establishing method and device, the fail safe that can improve the biological identification process.
Biological safety level model provided by the invention comprises: biological safety level and biological parameter information; Described biological safety level comprises the parameter information unique identifier; Described biological parameter information comprises biotype, and/or biological algorithm, and/or algorithmic error matching rate value.
Alternatively, described masterplate also comprises: strategy.
Alternatively, described biological safety level also comprises: level of security.
Alternatively, described biological parameter information also comprises: level of security, and/or strategy, and/or relevant parameter.
Biological safety level model establishing method provided by the invention comprises: obtain the strategy that the user selects; Obtain biological parameter information; Determine security level values; Be biological safety level model allocation of parameters information unique identifier; According to described parameter information unique identifier, level of security, strategy and biological parameter information structuring biological safety level model.
Alternatively, the step of described definite security level values comprises: same biotype under acquisition strategy and the described strategy, the erroneous matching rate of same algorithm correspondence; It is related with policy condition number and erroneous matching rate that described security level values is set; Number and erroneous matching rate according to described policy condition are determined security level values.
Biological safety level model setting device provided by the invention comprises: allocation units, acquiring unit and structural unit; Described allocation units are used to biological safety level model allocation of parameters information unique identifier; Described acquiring unit is used for determining security level values, obtains the strategy of user's selection and obtains biological parameter information; Described structural unit is used for according to described parameter information unique identifier, level of security, strategy and biological parameter information structuring biological safety level model.
Above technical scheme as can be seen, the present invention has the following advantages:
Among the present invention, with parameter information unique identifier and the biological parameter information composition biological safety level that combines, the user finds corresponding biological parameter according to the parameter information unique identifier, so can distinguish the level of security of different biological informations, thereby improve the fail safe and the flexibility of biological identification process.
Description of drawings
The attack schematic diagram that Fig. 1 may be subjected to for biosystem in the prior art;
Fig. 2 (a)～(c) is a biological safety level model schematic diagram of the present invention;
Fig. 3 is a biological safety level model establishing method flow chart of the present invention;
Fig. 4 is a biological safety level model setting device schematic diagram of the present invention.
Embodiment
The invention provides a kind of biological safety level model and establishing method thereof and device, be used to improve the fail safe of biological identification process.
In the specific embodiment of the invention, biological safety level model is made of biological safety level, strategy and biological parameter information, concrete form such as Fig. 2 (a), Fig. 2 (b), shown in Fig. 2 (c), being understandable that the form of biological safety level model is not limited to these situations, can be other form equally.
With Fig. 2 (a) is example, and in the present embodiment, biological safety level model comprises:
Biological safety level: constitute by parameter information unique identifier and level of security.
Parameter information unique identifier: unique pairing various parameters of biological safety level of distinguishing, as hash value of biological parameter information and level of security etc., when reality is used, this is offered concrete client user or data designated storehouse together with level of security.
Level of security: identify the biological safety of representing under certain strategy and the biological parameter information.The foundation of determining the level of security height is: earlier according to strategy, the many more level of securitys of policy condition are high more; According to same biotype under a certain strategy, the pairing erroneous matching rate of same algorithm (FMR, False Match Rate) is worth again, and FMR value more little (guaranteeing under the available situation) safety is high more.The situation of last comprehensive this two aspect is determined the value of level of security.
Strategy: the strategy that strategy reflection user specifically selects for use, comprising: single mode biological identification, single mode biological identification+live body detection, multimode biological identification, multimode biological identification+live body detection etc. also can add other strategy as required.
Wherein, the single mode biological identification adopts single biotype to authenticate exactly, carries out authentication as independent use fingerprint, iris, train of thought etc.; It is exactly to require biometric reader to have the function of identification living body biological that live body detects; The multimode biological identification is exactly to use dissimilar biological or same biological different entities to carry out authentication simultaneously.
Biological parameter information: constitute by biotype, biological algorithm, algorithm FMR value and relevant parameter.
Biotype: identify the biological name that biological identification uses.As: fingerprint, iris, face etc. also comprise the combination (as fingerprint+iris) of various biologies.
Biological algorithm: employed biometric processing algorithm when carrying out bio-identification in the biological identification comprises living body biological masterplate Processing Algorithm and biological template matching algorithm.
Biological algorithm FMR: the pairing a series of values of certain biological algorithm, the erroneous matching rate of its reflection algorithm, this value is more little, and its authentication result is reliable more, so can use FMR to reflect the height of biological safety level.
Relevant parameter: use after giving over to,, can add as required as expansion.
According to above-mentioned form, provide the instantiation of a biological safety level tabulation below, as shown in the table:
Table 1
In last table, according to the ordering of row, from top to bottom, biological safety level raises gradually.
Wherein, Hash Value: Hash or secret value i, Hash or secret value j, Hash or secret value k, Hash or secret value l have nothing in common with each other.Parameter information unique identification value and relevant biological parameter information.
Level of security: level of security is related with strategy and FMR, and determine that specifically the foundation of level of security height can be: earlier according to strategy, the many more level of securitys of policy condition are high more; Again according to same biotype under a certain strategy, the pairing FMR value of same algorithm, FMR value more little (guaranteeing under the available situation) safety is high more, and the situation of last comprehensive this two aspect is determined the value of level of security.Be understandable that, can adjust related mode according to concrete needs equally, the value of the value reflection biological safety level of level of security.
Under strategy, it is generally acknowledged that the level of security increasing order is: single mode＜single mode+live body detection＜multimode＜multimode+live body detects, and can add strategy as required, and promptly the many more level of securitys of policy condition are high more.Be Ai＜Bj＜Ck＜D1.
Biological algorithm: for strategy is under the single mode situation, and same biotype may have corresponding a plurality of biometric processing algorithm, has multiple as the algorithm of handling fingerprint.For strategy is under the multimode situation, the biotype of like combinations, and combination that may corresponding multiple algorithm, can the alignment processing algorithm as fingerprint+iris combination: fingerprint algorithm 1+ iris algorithm 1 also can be fingerprint algorithm 2+ iris algorithm 2.
The FMR value: each algorithm or algorithm combination can corresponding a plurality of FMR values, can satisfy system can with condition under provide a series of value, the height of their decision level of securitys.
For example strategy is A, and biotype is B, and biological algorithm is C, and Dui Ying FMR value is 1,2,3 in this case, the height of these numerical value decision level of securitys.
Provide a concrete specific embodiment below, as shown in the table:
Table 2
| Hash value | Biological safety level | Strategy | Biotype | Biological algorithm | Algorithm FMR | Relevant parameter |
| Single mode (A) |
| HashA111 | A1 | Single mode (A) | Fingerprint | Fingerprint algorithm 1 | FMRA111 | |
| HashA112 | A2 | Single mode | Fingerprint | Fingerprint algorithm 1 | FMRA112 | |
| ... | ... | ... | ... | ... | ... | ... |
| HashA11i | Ai | Single mode | Fingerprint | Fingerprint algorithm 1 | FMRA11i | |
| HashA121 | A1 | Single mode | Fingerprint | Fingerprint algorithm 2 | FMRA121 | |
| HashA122 | A2 | Single mode | Fingerprint | Fingerprint algorithm 2 | FMRA122 | |
| ... | ... | ... | ... | ... | ... | ... |
| HashA12i | Ai | Single mode | Fingerprint | Fingerprint algorithm 2 | FMRA12i | |
| HashA211 | A1 | Single mode | Iris | Iris algorithm 1 | FMRA211 | |
| HashA212 | A2 | Single mode | Iris | Iris algorithm 1 | FMRA212 | |
| ... | ... | ... | ... | ... | ... | ... |
| HashA21i | Ai | Single mode | Iris | Iris algorithm 1 | FMRA21i | |
| HashA221 | A1 | Single mode | Iris | Iris algorithm 2 | FMRA221 | |
| HashA222 | A2 | Single mode | Iris | Iris algorithm 2 | FMRA222 | |
| ... | ... | ... | ... | ... | ... | ... |
| HashA22i | Ai | Single mode | Iris | Iris algorithm 2 | FMRA22i |
| ... | ... | ... | ... | ... | ... | ... |
| Single mode+live body (B) | Annotate: FMRA=FMRB | |||||
| HashB111 | B1 | Single mode+live body (B) | Fingerprint | Fingerprint algorithm 1 | FMRB111 | |
| HashB112 | B2 | Single mode+live body | Fingerprint | Fingerprint algorithm 1 | FMRB112 | |
| ... | ... | ... | ... | ... | ... | ... |
| HashB11i | Bi | Single mode+live body | Fingerprint | Fingerprint algorithm 1 | FMRB11i | |
| Hash121 | B1 | Single mode+live body | Fingerprint | Fingerprint algorithm 2 | FMRB121 | |
| HashB122 | B2 | Single mode+live body | Fingerprint | Fingerprint algorithm 2 | FMRB122 | |
| ... | ... | ... | ... | ... | ... | ... |
| HashB12i | Bi | Single mode+live body | Fingerprint | Fingerprint algorithm 2 | FMRB12i | |
| HashB211 | B1 | Single mode+live body | Iris | Iris algorithm 1 | FMRB211 |
| HashB212 | B2 | Single mode+live body | Iris | Iris algorithm 1 | FMRB212 | |
| ... | ... | ... | ... | ... | ... | ... |
| HashB21i | Bi | Single mode+live body | Iris | Iris algorithm 1 | FMRB21i | |
| HashB221 | B1 | Single mode+live body | Iris | Iris algorithm 2 | FMRB221 | |
| HashB222 | B2 | Single mode+live body | Iris | Iris algorithm 2 | FMRB222 | |
| ... | ... | ... | ... | ... | ... | ... |
| HashB22i | Bi | Single mode+live body | Iris | Iris algorithm 2 | FMRB22i | |
| ... | ... | ... | ... | ... | ... | ... |
| Multimode (C) | Annotate: FMR is the value after merging | |||||
| HashC111 | C1 | Multimode (C) | Fingerprint+iris | Fingerprint algorithm 1+ iris algorithm 1 | FMRC111 | |
| HashC112 | C2 | Multimode | Fingerprint+iris | Fingerprint algorithm 1+ iris algorithm 1 | FMRC112 |
| ... | ... | ... | ... | ... | ... | ... |
| HashC11i | Ci | Multimode | Fingerprint+iris | Fingerprint algorithm 1+ iris algorithm 1 | FMRC11i | |
| HashC121 | C1 | Multimode | Fingerprint+iris | Fingerprint algorithm 1+ iris algorithm 2 | FMRC121 | |
| HashC122 | C2 | Multimode | Fingerprint+iris | Fingerprint algorithm 1+ iris algorithm 2 | FMRC122 | |
| ... | ... | ... | ... | ... | ... | ... |
| HashC12i | Ci | Multimode | Fingerprint+iris | Fingerprint algorithm 1+ iris algorithm 2 | FMRC12i | |
| HashC131 | C1 | Multimode | Fingerprint+iris | Fingerprint algorithm 2+ iris algorithm 1 | FMRC131 | |
| HashC132 | C2 | Multimode | Fingerprint+iris | Fingerprint algorithm 2+ iris algorithm 1 | FMRC132 | |
| ... | ... | ... | ... | ... | ... | |
| HashC13i | Ci | Multimode | Fingerprint+iris | Fingerprint algorithm 2+ iris algorithm 1 | FMRC13i | |
| HashC211 | C1 | Multimode | Fingerprint+face | Fingerprint algorithm 1+facial algorithm 1 | FMRC211 |
| HashC212 | C2 | Multimode | Fingerprint+face | Fingerprint algorithm 1+facial algorithm 1 | FMRC212 | |
| ... | ... | ... | ... | ... | ... | ... |
| HashC21i | Ci | Multimode | Fingerprint+face | Fingerprint algorithm 1+facial algorithm 1 | FMRC21i | |
| HashC221 | C1 | Multimode | Fingerprint+face | Fingerprint algorithm 1+facial algorithm 2 | FMRC221 | |
| HashC222 | C2 | Multimode | Fingerprint+face | Fingerprint algorithm 1+facial algorithm 2 | FMRC222 | |
| ... | ... | ... | ... | ... | ... | ... |
| HashC22i | Ci | Multimode | Fingerprint+face | Fingerprint algorithm 1+facial algorithm 2 | FMRC22i | |
| HashC231 | C1 | Multimode | Fingerprint+face | Fingerprint algorithm 2+facial algorithm 1 | FMRC231 | |
| HashC232 | C2 | Multimode | Fingerprint+ | Fingerprint algorithm 2 | FMRC232 |
| Facial | + facial algorithm 1 | |||||
| ... | ... | ... | ... | ... | ... | ... |
| HashC23i | Ci | Multimode | Fingerprint+face | Fingerprint algorithm 2+facial algorithm 1 | FMRC23i | |
| ... | ... | ... | ... | ... | ... | ... |
See also Fig. 3, biological safety level model establishing method of the present invention comprises:
301, acquisition strategy;
Wherein, obtain the strategy that the user specifically selects for use, comprising: single mode biological identification, single mode biological identification+live body detection, multimode biological identification, multimode biological identification+live body detection etc. also can add other strategy as required.
Wherein, the single mode biological identification adopts single biotype to authenticate exactly, carries out authentication as independent use fingerprint, iris, train of thought etc.; It is exactly to require biometric reader to have the function of identification living body biological that live body detects; The multimode biological identification is exactly to use dissimilar biological or same biological different entities to carry out authentication simultaneously.
302, obtain biological parameter information;
Wherein, biological parameter information comprises: biotype and/or biological algorithm and/or algorithm FMR value, and/or relevant parameter.
Biotype: identify the biological name that biological identification uses.As: fingerprint, iris, face etc. also comprise the combination (as fingerprint+iris) of various biologies.
Biological algorithm: employed biometric processing algorithm when carrying out bio-identification in the biological identification comprises living body biological masterplate Processing Algorithm and biological template matching algorithm.
Biological algorithm FMR: the pairing a series of values of certain biological algorithm, the erroneous matching rate of its reflection algorithm, this value is more little, and its authentication result is reliable more, so can use FMR to reflect the height of biological safety level.
Relevant parameter: use after giving over to,, can add as required as expansion.
303, determine security level values;
Wherein, earlier according to strategy, the many more level of securitys of policy condition are high more; According to the pairing FMR value of same algorithm under a certain strategy, FMR value more little (guaranteeing under the available situation) safety is high more again.The situation of last comprehensive this two aspect is determined the value of level of security.
304, allocation of parameters information unique identifier;
Wherein, hash value or secret value that described parameter information unique identifier is biological parameter information and level of security are understandable that, equally can for other can unique identification biological parameter information identifier.
305, structure biological safety level model.
See also Fig. 4, biological safety level model setting device of the present invention comprises:
Acquiring unit 402 is used for determining security level values, obtains the strategy of user's selection and obtains biological parameter information;
More than a kind of biological safety level model provided by the present invention and establishing method thereof and device are described in detail, used specific case herein principle of the present invention and execution mode are set forth, the explanation of above embodiment just is used for helping to understand method of the present invention and core concept thereof; Simultaneously, for one of ordinary skill in the art, according to thought of the present invention, the part that all can change in specific embodiments and applications, in sum, this description should not be construed as limitation of the present invention.
Claims (6)
1, a kind of biological safety level model establishing method is characterized in that, comprising:
Obtain the strategy that the user selects;
Obtain biological parameter information;
Determine security level values;
Be biological safety level model allocation of parameters information unique identifier;
According to described parameter information unique identifier, level of security, strategy and biological parameter information structuring biological safety level model.
2, biological safety level model establishing method according to claim 1 is characterized in that, the step of described definite security level values comprises:
Same biotype under acquisition strategy and the described strategy, the erroneous matching rate of same algorithm correspondence;
It is related with policy condition number and erroneous matching rate that described security level values is set;
Number and erroneous matching rate according to described policy condition are determined security level values.
3, biological safety level model establishing method according to claim 1 is characterized in that, described biological parameter information comprises:
The biological name that uses in the biological identification, and/or employed biological algorithm when carrying out bio-identification in the biological identification, and/or the erroneous matching rate of biological algorithm.
4, biological safety level model establishing method according to claim 1 is characterized in that, described parameter information unique identifier is the Hash Value of biological parameter information and level of security.
5, biological safety level model establishing method according to claim 1 is characterized in that, described strategy comprises:
Single mode biological identification, single mode detect with live body and combine authentication, and multimode biological identification and multimode detect with live body and combine authentication.
6, a kind of biological safety level model setting device is characterized in that, comprising:
Allocation units, acquiring unit and structural unit;
Described allocation units are used to biological safety level model allocation of parameters information unique identifier;
Described acquiring unit is used for determining security level values, obtains the strategy of user's selection and obtains biological parameter information;
Described structural unit is used for according to described parameter information unique identifier, level of security, strategy and biological parameter information structuring biological safety level model.
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| CN200610136498A CN100583765C (en) | 2006-10-30 | 2006-10-30 | Biological safety level model and its setting method and device |
| EP07800922.2A EP2053777B1 (en) | 2006-08-18 | 2007-08-10 | A certification method, system, and device |
| JP2009524890A JP2010501103A (en) | 2006-08-18 | 2007-08-10 | Method and system for authentication |
| KR1020097005360A KR20090041436A (en) | 2006-08-18 | 2007-08-10 | A certification method, system, and device |
| PCT/CN2007/070446 WO2008022585A1 (en) | 2006-08-18 | 2007-08-10 | A certification method, system, and device |
| US12/388,315 US20090271635A1 (en) | 2006-08-18 | 2009-02-18 | Methods and systems for authentication |
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| NO344910B1 (en) * | 2016-01-12 | 2020-06-29 | Kk88 No As | Device for verifying the identity of a person |
| CN106203064B (en) * | 2016-07-20 | 2018-09-11 | 刘先利 | A kind of account and method of password authentication and system |
| CN107066866A (en) * | 2017-05-12 | 2017-08-18 | 深圳市乃斯网络科技有限公司 | The biometric discrimination method and system of intelligent terminal |
| CN109815853A (en) * | 2019-01-04 | 2019-05-28 | 深圳壹账通智能科技有限公司 | Biopsy method, device, computer equipment and storage medium |
| CN114708667B (en) * | 2022-03-14 | 2023-04-07 | 江苏东方数码系统集成有限公司 | Security method and system based on multiple biological recognition technology |
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