CN107493268B - A kind of difference method for secret protection based on front position vector - Google Patents
A kind of difference method for secret protection based on front position vector Download PDFInfo
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/04—Network architectures or network communication protocols for network security for providing a confidential data exchange among entities communicating through data packet networks
- H04L63/0407—Network architectures or network communication protocols for network security for providing a confidential data exchange among entities communicating through data packet networks wherein the identity of one or more communicating identities is hidden
- H04L63/0421—Anonymous communication, i.e. the party's identifiers are hidden from the other party or parties, e.g. using an anonymizer
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/04—Network architectures or network communication protocols for network security for providing a confidential data exchange among entities communicating through data packet networks
- H04L63/0428—Network architectures or network communication protocols for network security for providing a confidential data exchange among entities communicating through data packet networks wherein the data content is protected, e.g. by encrypting or encapsulating the payload
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/50—Network services
- H04L67/52—Network services specially adapted for the location of the user terminal
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W12/00—Security arrangements; Authentication; Protecting privacy or anonymity
- H04W12/02—Protecting privacy or anonymity, e.g. protecting personally identifiable information [PII]
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/02—Services making use of location information
- H04W4/029—Location-based management or tracking services
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Abstract
The invention discloses a kind of position data guard methods based on front position vector; the features such as abundant due to the high-dimensional of position data, temporal correlation and background knowledge; so that the secret protection of position data, which is faced with, protects different challenges from conventional privacy; for position data secret protection; the method that the present invention has used difference secret protection; from vector, random noise is added respectively to two dimensions of distance and angle, realizes ε-difference secret protection.The position data issued after difference secret protection processing had not only protected the individual privacy of user, but also has guaranteed the availability of position data.
Description
Technical field
The invention belongs to secret protection technical fields, more particularly, to a kind of difference privacy based on front position vector
Guard method.
Background technique
In recent years, location based service and various location technologies are widely used, wherein there is a large amount of user
Position data is collected.In order to preferably utilize the learning value and commercial value contained in position data, the user position of accumulation
It sets data and is distributed to academic and commercial undertaking, for carrying out the research such as urban planning, Behavior Pattern Analysis, business decision.Such as
What makes the individual privacy in position data publication be effectively protected, and is increasingly becoming the hot spot of research.And the higher-dimension of position data
The features such as degree, temporal correlation and background knowledge are abundant, so that the secret protection of position data is faced with and conventional privacy
Protect different challenges.
The current common method for secret protection based on position data mainly has following three kinds:
1, track suppression technology
Track suppression technology principle is all nodes that do not issue on all track or a track.If track
Some upper node contains a large amount of sensitive informations, and the threat that releasing can be such that track privacy leaks becomes larger, then we will inhibit
The publication of these nodes after removing these sensitive nodes, then issues track data.Under some extreme cases, whole track is all
It is that susceptibility is very high, then directly weeding out this track from track database.Also there is such case: cluster knot
Shu Shi, it may appear that several tracks do not include by some equivalence class, at this point, only this whole track is all weeded out.
2, the extensive technology in track
Towards the data being stored in relevant database, in the data publication stage, determining number is usually become packet
A section containing this number, after extensive in this way, attacker can not just learn specific numerical value.For example, the age sheet of Jack
Being determining 58 years old, but section [50-59] expression can be used.It is enlightened, when research track secret protection
When, some specific point can also be indicated with a room size appropriate.
3, false track data protection technique
Under the premise of not allowing the track data of publication to lose certain statistical properties, into initial trace data to be released, add
The nodes of locations of several vacations is added to reach disturbance purpose.False track data protection technique is easy to accomplish, and effect is obvious.It is logical
It crosses after false track data protection technique processing, the data track of publication had not only included truthful data point, but also included false data
Point protects true track data to a certain extent, and provides the availability of data.
However, the above-mentioned existing method for secret protection based on position data has the following problems:
1, Sensitive Attributes and non-sensitive attribute are uncertain: the Sensitive Attributes that are very difficult to define in track data and non-sensitive
Attribute, it is changed with the external information that different attackers possesses.Assuming that attacker A has grasped user a certain
Track in a period, then this path segment can only be divided into non-sensitive information for attacker A.But user
In the path segment in other times section for attacker A, sensitive information is still fallen within, it is necessary to be protected.Track number
According to complexity it is high, cause the problem to Sensitive Attributes and non-sensitive Attribute transposition.Therefore, in the data protection of track,
It is considered that the arbitrary node on track all has identical sensibility.
2, availability of data is lower: being applied in track data when extensive, extensive degree how to be selected just to become one
A stubborn problem.If the space of amplification is too big, the availability of data can be directly reduced.Practical application can generally consider
To true geographical environment, and with the variation of ambient enviroment, it should use different degrees of extensive space.It is extensive to lead
Cause information loss degree larger, availability of data reduces.
3, memory space is excessive: although false track data protection technique is relatively easily realized, not needing complicated process
Journey, but data false toward addition inside database always in this way, the memory space that will lead to database become larger, storage overhead
Become larger.
Summary of the invention
Aiming at the above defects or improvement requirements of the prior art, the present invention provides a kind of differences based on front position vector
Divide method for secret protection and system, it is intended that there are Sensitive Attributes in the existing location-based method for secret protection of solution
Uncertain, availability of data is too low and memory space is excessive problem.
To achieve the above object, according to one aspect of the present invention, it is hidden to provide a kind of difference based on front position vector
Private guard method, comprising the following steps:
(1) geometric locus that multiple position datas are constituted is obtained, and the geometric locus is sampled, to be sampled
Point set T={ (X0,Y0),(X1,Y1) ..., (Xn,Yn)}；Wherein n indicates the quantity of sampled point, and X and Y respectively indicate sampled point
Abscissa and ordinate；
(2) counter i=1 is set；
(3) judge whether i is less than or equal to n, be if it is transferred to step (4), otherwise enter step (9)；
(4) intermediate vector V is obtained according to sampled point set Ti=(Xi-X* i-1, Yi-Y* i-1), and obtain intermediate vector Vi's
Mould and angle, wherein X*And Y*Respectively indicate abscissa and ordinate of the sampled point after disturbance, and X* 0=X0, Y* 0=Y0；
(5) according to intermediate vector ViMould obtain laplacian distribution function, seek the anti-of the laplacian distribution function
Function, and random value ρ is obtained according to the inverse functioni；
(6) according to intermediate vector ViAngle obtain laplacian distribution function, seek the laplacian distribution function
Inverse function, and random value α is obtained according to the inverse functioni；
(7) the random value ρ obtained according to step (5) and step (6)iAnd αiObtain abscissa of the sampled point after disturbance
With ordinate X* iAnd Y* i；
(8) i=i+1, and return step (3) are set；
(9) according to new sampled point set the T*={ (X after disturbance* 0,Y* 0),(X* 1,Y* 1),…,(X* n,Y* n) acquisition pair
The geometric locus answered, and issued the geometric locus as private data on open platform.
Preferably, the period sampled to geometric locus is 1 second.
Preferably, intermediate vector ViMould ri=| Vi|, intermediate vector ViAngle, θi=Arg (Vi)；
Preferably, according to intermediate vector ViMould obtain laplacian distribution function are as follows:
Wherein random number ρi∈ [0,2M], ε indicate predefined privacy parameters,M
Indicate the half of maximum distance between adjacent coordinates point.
Preferably, random numberWhereinIt is 0
Random value between to 1.
Preferably, according to intermediate vector ViAngle obtain laplacian distribution function are as follows:
Wherein random number αi∈ [0,2 π], ε indicate predefined privacy parameters,π
It is pi.
Preferably, random numberWhereinIt is 0
Random value between to 1.
Preferably, abscissa X of the sampled point after disturbance* iWith ordinate Y* iRespectively equal to:
It is another aspect of this invention to provide that providing a kind of difference intimacy protection system based on front position vector, wrap
It includes:
First module, the geometric locus constituted for obtaining multiple position datas, and the geometric locus is sampled,
To obtain sampled point set T={ (X0,Y0),(X1,Y1) ..., (Xn,Yn)}；Wherein n indicates the quantity of sampled point, X and Y difference
Indicate the abscissa and ordinate of sampled point；
Second module, for counter i=1 to be arranged；
Third module is if it is transferred to the 4th module, otherwise enters the 9th mould for judging whether i is less than or equal to n
Block；
4th module, for obtaining intermediate vector V according to sampled point set Ti=(Xi-X* i-1, Yi-Y* i-1), and in acquisition
Between vector ViMould and angle, wherein X*And Y*Respectively indicate abscissa and ordinate of the sampled point after disturbance, and X* 0=
X0, Y* 0=Y0；
5th module, for according to intermediate vector ViMould obtain laplacian distribution function, seek the Laplce point
The inverse function of cloth function, and random value ρ is obtained according to the inverse functioni；
6th module, for according to intermediate vector ViAngle obtain laplacian distribution function, seek the Laplce
The inverse function of distribution function, and random value α is obtained according to the inverse functioni；
7th module, for the random value ρ according to the 5th module and the acquisition of the 6th moduleiAnd αiSampled point is obtained by disturbing
Abscissa and ordinate X after dynamic* iAnd Y* i；
8th module for i=i+1 to be arranged, and returns to third module；
9th module, for according to new sampled point set the T*={ (X after disturbance* 0,Y* 0),(X* 1,Y* 1),…, (X* n,
Y* n) corresponding geometric locus is obtained, and issued the geometric locus as private data on open platform.
In general, through the invention it is contemplated above technical scheme is compared with the prior art, can obtain down and show
Beneficial effect:
1, the present invention can solve the uncertain problem of Sensitive Attributes present in existing method: by step (1) to rail
Trace curve is sampled, and it is sensitive data that n data point coordinate of sampling, which is all regarded, and against n data point in step (7)
Noise processed is all added in place, therefore is difficult to determining problem there is no Sensitive Attributes.
2, the present invention can solve the too low problem of availability of data present in existing method: pass through setting in step (1)
The value of ε, so that random noise is calculated in step (7) by step (4) meets ε-difference secret protection, therefore,
The availability and privacy that can carry out equilibrium data by adjusting the value of ε, ensure that step (9) publication track data be
Within the scope of available.
3, the present invention can solve the excessive problem of memory space present in existing method: pass through step (1) to step
(9), the present invention carries out adding processing of making an uproar just for n data point of sampling, does not introduce new data point, therefore, data
Storage overhead relatively size.
4, the present invention can provide the secret protection level of quantization, facilitate the degree for comparing secret protection, moreover, this hair
It is bright to resist background knowledge attack.
Detailed description of the invention
Fig. 1 is the flow chart of the difference method for secret protection the present invention is based on front position vector.
Specific embodiment
In order to make the objectives, technical solutions, and advantages of the present invention clearer, with reference to the accompanying drawings and embodiments,
The present invention will be described in further detail.It should be appreciated that specific embodiment described herein is only used to explain this hair
It is bright, it is not intended to limit the present invention.In addition, technology involved in the various embodiments of the present invention described below is special
Sign can be combined with each other as long as they do not conflict with each other.
The present invention is realized in difference privacy theoretical basis, the position data after premenstrual position vector algorithm process,
All there is advantage from error and stability.
Difference secret protection provided by the invention can overcome background knowledge to attack, even if attacker has grasped part rail
Mark or enough background knowledges, can not also be inferred to true trace information.
In difference secret protection model, it can be assumed that attacker obtains in addition to target trajectory, all other
The information of track, adding up for these information is exactly so-called maximum background knowledge.When attacker possess maximum background knowledge this
Under the premise of one, privacy will not all be leaked, so can defend the attack based on background knowledge using difference method for secret protection.
Wherein difference privacy has sturdy Fundamentals of Mathematics as support, and stringent mathematical definition is defined to secret protection,
Derivation proof can be carried out by mathematical formulae, possess firm mathematical theory basis.
Secret protection level can be quantified with mathematic parameter, be current degree of protection by difference secret protection technology
One of highest method.This is also simultaneously quantitative evaluation foundation, allows same position data set under different parameter roles,
The secret protection that can be convenient comparison algorithm offer is horizontal.
Wherein, front position vector is from vector angle, by the point in upper one point to be output and current initial trace
Line gets up, and forms a vector.Front position vector operation adds noise toward two dimensions of angle and distance.
Front position vector is directed toward the vector in current home position as the ginseng of next vector using previous output position
Value is examined to add the disturbance of angle and distance, the laplacian distribution of different parameters is obeyed in the output that each pair of point is answered, and should
Parameter is determined by front position vector.
As shown in Figure 1, the present invention is based on the difference method for secret protection of front position vector the following steps are included:
(1) geometric locus that multiple position datas are constituted is obtained, and the geometric locus is sampled, is adopted with obtaining n
Sampling point set T={ (X0,Y0),(X1,Y1) ..., (Xn,Yn)}；Wherein n indicates the quantity of sampled point, and X and Y respectively indicate sampling
The abscissa and ordinate of point；
Specifically, the position data in this step can be driving trace, the run trace of people etc. of vehicle；
The period Int sampled to geometric locus is 1s.
(2) counter i=1 is set；
(3) judge whether i is less than or equal to n, be if it is transferred to step (4), otherwise enter step (9)；
(4) intermediate vector V is obtained according to sampled point set Ti=(Xi-X* i-1, Yi-Y* i-1), and obtain intermediate vector Vi's
Mould and angle, wherein X*And Y*Respectively indicate abscissa and ordinate of the sampled point after disturbance, and X* 0=X0, Y* 0=Y0；
Specifically, intermediate vector ViMould ri=| Vi|, intermediate vector ViAngle, θi=Arg (Vi)；
(5) according to intermediate vector ViMould obtain laplacian distribution function, seek the anti-of the laplacian distribution function
Function, and random value ρ is obtained according to the inverse functioni；
Specifically, according to intermediate vector ViMould obtain laplacian distribution function are as follows:
Wherein ρi∈ [0,2M], ε indicate predefined privacy parameters,
Value range is any positive number between 0 to 12, whereinM indicates adjacent coordinates
The half of maximum distance between point.
Random numberWhereinFor 0 to 1 it
Between random value；
(6) according to intermediate vector ViAngle obtain laplacian distribution function, seek the laplacian distribution function
Inverse function, and random value α is obtained according to the inverse functioni；
Specifically, according to intermediate vector ViAngle obtain laplacian distribution function are as follows:
Wherein αi∈ [0,2 π], ε indicate predefined privacy parameters,
Value range is any positive number between 0 to 12,Wherein π is pi.
Random numberWhereinFor 0 to 1 it
Between random value；
(7) the random value ρ obtained according to step (5) and step (6)iAnd αiObtain abscissa of the sampled point after disturbance
With ordinate X* iAnd Y* i；
Specifically, abscissa X of the sampled point after disturbance* iWith ordinate Y* iRespectively equal to:
(8) i=i+1, and return step (3) are set；
(9) according to new sampled point set the T*={ (X after disturbance* 0,Y* 0),(X* 1,Y* 1),…,(X* n,Y* n) acquisition pair
The geometric locus answered, and issued the geometric locus as private data on open platform.
As it will be easily appreciated by one skilled in the art that the foregoing is merely illustrative of the preferred embodiments of the present invention, not to
The limitation present invention, any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should all wrap
Containing within protection scope of the present invention.
Claims (9)
1. a kind of difference method for secret protection based on front position vector, which comprises the following steps:
(1) geometric locus that multiple position datas are constituted is obtained, and the geometric locus is sampled, to obtain sampled point set
T={ (X0,Y0),(X1,Y1) ..., (Xn,Yn)}；Wherein n indicates the quantity of sampled point, and X and Y respectively indicate the horizontal seat of sampled point
Mark and ordinate；
(2) counter i=1 is set；
(3) judge whether i is less than or equal to n, be if it is transferred to step (4), otherwise enter step (9)；
(4) intermediate vector V is obtained according to sampled point set Ti=(Xi-X* i-1, Yi-Y* i-1), and obtain intermediate vector ViMould and
Angle, wherein X* i-1And Y* i-1Respectively indicate abscissa and ordinate of (i-1)-th sampled point after disturbance, and X* 0=X0,
Y* 0=Y0；
(5) according to intermediate vector ViMould obtain laplacian distribution function, seek the inverse function of the laplacian distribution function,
And random value ρ is obtained according to the inverse functioni；
(6) according to intermediate vector ViAngle obtain laplacian distribution function, seek the anti-letter of the laplacian distribution function
Number, and random value α is obtained according to the inverse functioni；
(7) the random value ρ obtained according to step (5) and step (6)iAnd αiObtain abscissa of the ith sample point after disturbance
With ordinate X* iAnd Y* i；
(8) i=i+1, and return step (3) are set；
(9) according to new sampled point set the T*={ (X after disturbance* 0,Y* 0),(X* 1,Y* 1),…,(X* n,Y* n) obtain corresponding rail
Trace curve, and issued the geometric locus as private data on open platform.
2. difference method for secret protection according to claim 1, which is characterized in that the period sampled to geometric locus
It is 1 second.
3. difference method for secret protection according to claim 1, which is characterized in that intermediate vector ViMould ri=| Vi|, in
Between vector ViAngle, θi=Arg (Vi)。
4. difference method for secret protection according to claim 3, which is characterized in that according to intermediate vector ViMould obtain draw
This distribution function of pula are as follows:
Wherein random number ρi∈ [0,2M], ε indicate predefined privacy parameters,M table
Show the half of maximum distance between adjacent coordinates point.
5. difference method for secret protection according to claim 1, which is characterized in that random numberWhereinFor the random value between 0 to 1.
6. difference method for secret protection according to claim 1, which is characterized in that according to intermediate vector ViAngle obtain
Laplacian distribution function are as follows:
Wherein random number αi∈ [0,2 π], ε indicate predefined privacy parameters,π is
Pi.
7. difference method for secret protection according to claim 6, which is characterized in that random numberWhereinFor the random value between 0 to 1.
8. difference method for secret protection according to claim 1, which is characterized in that abscissa of the sampled point after disturbance
X* iWith ordinate Y* iRespectively equal to:
。
9. a kind of difference intimacy protection system based on front position vector characterized by comprising
First module, the geometric locus constituted for obtaining multiple position datas, and the geometric locus is sampled, to obtain
Sampled point set T={ (X0,Y0),(X1,Y1) ..., (Xn,Yn)}；Wherein n indicates the quantity of sampled point, and X and Y are respectively indicated and adopted
The abscissa and ordinate of sampling point；
Second module, for counter i=1 to be arranged；
Third module is if it is transferred to the 4th module, otherwise enters the 9th module for judging whether i is less than or equal to n；
4th module, for obtaining intermediate vector V according to sampled point set Ti=(Xi-X* i-1, Yi-Y* i-1), and obtain it is intermediate to
Measure ViMould and angle, wherein X*And Y*Respectively indicate abscissa and ordinate of the sampled point after disturbance, and X* 0=X0, Y* 0
=Y0；
5th module, for according to intermediate vector ViMould obtain laplacian distribution function, seek the laplacian distribution function
Inverse function, and according to the inverse function obtain random value ρi；
6th module, for according to intermediate vector ViAngle obtain laplacian distribution function, seek the laplacian distribution letter
Several inverse functions, and random value α is obtained according to the inverse functioni；
7th module, for the random value ρ according to the 5th module and the acquisition of the 6th moduleiAnd αiSampled point is obtained after disturbance
Abscissa and ordinate X* iAnd Y* i；
8th module for i=i+1 to be arranged, and returns to third module；
9th module, for according to new sampled point set the T*={ (X after disturbance* 0,Y* 0),(X* 1,Y* 1),…,(X* n,Y* n) obtain
Corresponding geometric locus is obtained, and is issued the geometric locus as private data on open platform.
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| CN110443060B (en) * | 2018-05-03 | 2023-06-20 | 创新先进技术有限公司 | Data processing method and device |
| CN108882152B (en) * | 2018-07-03 | 2020-12-22 | 安徽工业大学 | User privacy protection method based on path selection reporting |
| CN109508559B (en) * | 2018-11-02 | 2020-10-27 | 西安交通大学 | Multi-dimensional data local privacy protection method based on connection function in crowd sensing system |
| CN110213036B (en) * | 2019-06-17 | 2021-07-06 | 西安电子科技大学 | Safe data storage and calculation method based on fog calculation-edge calculation of Internet of things |
| CN110750806A (en) * | 2019-07-16 | 2020-02-04 | 黑龙江省科学院自动化研究所 | TP-MFSA (TP-Multi-function document analysis) inhibition release-based high-dimensional position track data privacy protection release system and method |
| CN110727957A (en) * | 2019-10-15 | 2020-01-24 | 电子科技大学 | Differential privacy protection method and system based on sampling |
| CN113761000A (en) * | 2020-06-05 | 2021-12-07 | 华为技术有限公司 | Data processing method and device, computing equipment and storage medium |
| CN112328714A (en) * | 2020-09-24 | 2021-02-05 | 南京航空航天大学 | Airport scene track data publishing method based on differential privacy |
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