CN106953876A - A kind of location privacy protection method based on semantic context - Google Patents
A kind of location privacy protection method based on semantic context Download PDFInfo
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- CN106953876A CN106953876A CN201710285679.7A CN201710285679A CN106953876A CN 106953876 A CN106953876 A CN 106953876A CN 201710285679 A CN201710285679 A CN 201710285679A CN 106953876 A CN106953876 A CN 106953876A
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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
- 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
Abstract
The invention discloses a kind of location privacy protection method based on semantic context, comprise the following steps：(1) center anonymous server initialization map datum, highway network is modeled as by map datum；(2) user initiates inquiry according to demand, by location information, inquires about content, privacy requirements and identity information are packaged into message Q and are sent to center anonymous server；(3) center anonymous server is according to Q, and analysis determines position Loc of the user on road network, the anonymous collection S={ Loc } of initialization, the anonymous collection ES={ } of initialization buffering and ES '={ S }.The present invention has the advantages that there is good effect in anonymous success rate and the anonymous aspect of collection size two of reduction.
Description
Technical field
The present invention relates to a kind of secret protection technology, more particularly to a kind of location privacy protection side based on semantic context
Method, the location privacy protection method based on semantic context and considers mobile subscriber in the hidden of different semantic locations to be a kind of
Private guard method.
Background technology
In Sci-Tech Level high today, location technology has been not limited solely to military use, with mobile device
Popularization be widely applied in people's daily life, such as navigate, inquiry etc..Based on location technology and mobile device, Yi Zhongxin
The request of data mode of type is arisen at the historic moment -- location Based service (Location-based Service：LBS) technology；The party
Formula provides the user all kinds of services according to the positioning of user.For example, user is opened after certain shopping application program, purchase system root
Recommend some close to retail shop's information of customer location according to the location information of user；For another example, user to it is a certain place after, spread out the map
Hotel near application program, inquiry, supermarket etc..Service change based on the positioning life style and trip mode of people,
But problem is also following, the premise that user enjoys the service of this class is to provide the positional information of itself, personal Query Information etc.,
This will directly or indirectly reveal user privacy information.For example, user Alice asks the hotel near its position, then may be used
The position where user can be exposed；For another example, user Alice is based on location navigation to certain section hospital, then can deduce user
It there may be health problem.
Accurate positional information may insure that user enjoys accurate location-based service, but accurate positional information may also be tight
The personal secrets of user are damaged again；How the service quality that balancing user secret protection degree is enjoyed with user is privacy in LBS
One of important subject of protection.For the Privacy Protection in LBS, scholars have carried out substantial amounts of research, and these grind
Study carefully the two categories below that can substantially classify：1) position of user is protected；2) identity of user is protected.False position, space conversion, concealment
Space etc. is the most frequently used location privacy protection method.False position refers to one false position of stochastic cook instead of the true of user
Inquiry is initiated in position, to ensure service quality, and this method would generally limit a scope, and the position of forgery is only capable of in the scope
It is interior；The main thought of space conversion is that user position is translated or rotated to obtain a new position, using new
Position replaces user position to initiate inquiry；The main thought in concealment space is to expand user position for an area
Domain, replaces user position to initiate to inquire about, generally also sets some other requirements to concealment space using the region, such as hidden
Number of users in space of hideing is no less than K.
For in terms of identity protection, conventional method has：Assumed name, Mixed Zone etc..Assumed name main thought is using forgery
Identity replace user real identification initiate inquiry；Mixed Zone refers to set some regions on road network, and user enters region
Following agreement is observed afterwards：Inquiry can not be initiated, carrying out identity with other users in region at random exchanges.When user leaves region
Afterwards, the user profile that attacker is seen not its true identity.
Although the above method protects the privacy information of user to a certain extent, also be present some weakness in what is had, hold
Easily utilized by attack；For example in false location method the position of institute's stochastic cook is likely located at irrational place, forbids Ru some
In the current river of ship；Space is hidden such as comprising irrational region, then attacker can reduce the area in concealment space, increased
Position the probability of user position.In addition, except number of users in region, section number crosses that I haven't seen you for ages causes privacy of user to reveal it
Outside, the semantic information in region is also to cause one of factor of privacy of user leakage, and such as user is for several times in some section hospital
Inquiry is initiated, attacker can then speculate that user may be temporarily in the hospitalize, so as to push away from this semantic locations of section hospital
Survey the user and there is health problem.In Existing methods, it is contemplated that the method for semantic factor is less, specific as follows：
1) Xue et al. article《Location Diversity:Enhanced Privacy Protection in
Location Based Services》Propose that the position of L different semantic types must be included in inquiry every time, so as to attack
Person can not learn that user initiates the semanteme of inquiring position, but this method is without considering the semantic sensitivity for a user of each position not
Same situation, is still easily penetrated by attacker's reasoning；
2) L.Byoungyoung et al. article《Protecting location privacy using location
semantics》Different semantemes are distinguished using the residence time of user, the semantic different position aggregation of selection L when anonymous
Together, so as to avoid privacy leakage, this method may also possess the identical residence time there is also limitation, different semantemes,
By being stopped 20 minutes at A during example morning 8, A is probably dining room, and user has dinner at A, is also likely to be school at A, and user escorts
People goes to school；Therefore, the residence time can not clearly distinguish all kinds of semantemes.
In addition in reality, mobile subscriber moves on road, but the cartographic model of above-mentioned work is all that Euclid is empty
Between model, and there is the region that many users can not reach in Euclidean space.Therefore scholars have also been proposed some combinations
The road network location privacy protection method semantic with position, for example：
3) Damiani M L et al. article《The PROBE Framework for the Personalized
Cloaking of Private Locations》The Probe models of proposition consider the accessed probability of each class semantic locations not
Together, all kinds of semantemes are described using popularity, and by semanteme be divided into it is sensitive with it is non-sensitive, then construct anonymous region and come
Realize protection privacy；
4) Li et al. article《Sensitive Semantics-Aware Personality Cloaking on
Road-Network Environment》It will be divided, be then directed to Thiessen polygon comprising the semantic road network figure in position
Sensitive and non-sensitive semantic locations distribution carries out secret protection.
Although the above method considers semantic situation in the environment of road network, just to reaching use in its implementation procedure
Family privacy requirements, have no and consider whether anonymous collection is optimal, situations such as anonymity collects size, if that is, anonymity is concentrated comprising substantial amounts of quick
Feel semantic locations, then need more non-sensitive semantic locations to be desalinated.Although the anonymous collection so constituted meets privacy
Demand, but it includes more position, causes communication overhead big with query cost, so as to influence the service quality of user.
Therefore, during algorithm for design, privacy of user demand is not only met, user is enjoyed higher clothes as far as possible
Business quality, that is, reduce period of reservation of number, reduces query cost.
The content of the invention
It is an object of the invention to the shortcoming for overcoming prior art, there is provided a kind of position based on semantic context with deficiency
Method for secret protection, the location privacy protection method is under road network environment, it is ensured that while user enjoys personalized secret protection,
The concept based on semantic susceptibility missing values is proposed, construction includes the less anonymous collection of sensitive semantic locations, to reduce anonymous collection
Size, reduce communication-cost and query cost, it is ensured that user enjoys the high service of quality.
The purpose of the present invention is achieved through the following technical solutions：A kind of location privacy protection side based on semantic context
Method, comprises the following steps：
(1) center anonymous server initialization map datum, highway network is modeled as by map datum；
(2) user initiates inquiry according to demand, by location information, inquires about content, privacy requirements and identity information are packaged into
Message Q is sent to center anonymous server；
(3) center anonymous server is according to Q, and analysis determines position Loc of the user on road network, the anonymous collection S=of initialization
{ Loc }, the anonymous collection ES={ } of initialization buffering and ES '={ S }.
The center anonymous server is according to the anonymous collection of following steps construction：
1) the anonymous element number for integrating ES ' of buffering is set as num, and ES ' all elements are arranged by missing values ascending order；For
Element S in ES 'i, wherein 1≤i≤num and SiFor set of node, traversal set SiIn all nodes neighbours, if set Si's
Interstitial content is mi, wherein 1≤i≤num, by set SiMiThe neighbours of individual node respectively with SiCombination, is obtainedIt is individual
New set, during combination, neighbours are preferential for intersection, next to that non-sensitive semantic locations, are finally sensitive semantic positions
Put, then by order of addition set of computations SjSensitivity rate rSj, such as rSjNo more than θ, S is returnedjAs anonymity collection, anonymity terminates,
WhereinOtherwise, ES=ES ∪ { Sj}；
2) clearing buffers anonymity collection ES '；Now, if | ES |>Cmax, selection missing values are smaller in the anonymous collection ES of buffering
Preceding Cmax element add ES '；Otherwise the whole elements of ES are added into ES '；Finally empty ES；
3) any one element S in the anonymous collection ES ' of buffering is judgediComprising nodes whether be more than Lmax, 1≤i≤
Cmax, SiFor set of node, such as SiComprising nodes be more than Lmax, algorithm terminate, anonymity failure, return empty set；Otherwise step is turned
It is rapid 1).
The location privacy protection method combines local optimum and global optimum by the way of the anonymous collection of buffering, with two
The buffering anonymity collection ES and ES ' of size is defined by the user to find optimal anonymous collection.
In step (3), when judging that anonymous collection is good and bad, it is proposed that the concept of anonymity collection popularity missing values, stream
The smaller anonymous collection of row degree degree missing values is better, and the calculating of missing values uses equation below：
Wherein, S collects to be anonymous, popS() represents to calculate the semantic popularity sum of a certain class, pop in anonymous collection Ss(Sens)
Represent semantic popularity sum sensitive to user in anonymous collection S；pops() represents the total popularity sums of anonymous collection S.
The present invention provides a kind of location privacy protection mechanism when mobile subscriber initiates to inquire about for mobile subscriber.The mechanism
Using the mode of popularity missing values, with reference to the anonymous collection of buffering, each round concentrates selection to be wanted closest to user from buffering is anonymous
The anonymous collection for the Sensitivity rate asked, that is, select the anonymous collection that missing values are minimum, integrates as candidate's anonymity as the anonymous collection of user's construction.
In mechanism, the size of the anonymous collection of buffering is specified according to the demand of user, meets its individual demand.It is anonymous using the mechanism
Server is in the anonymous collection of construction, it is ensured that have higher anonymous success rate, and in the case where ensureing privacy of user, institute's structure
The anonymous collection made is smaller, to reduce communication overhead and query cost during request service data, reduces the stand-by period of user, carries
The service quality that high user enjoys.Finally, the invention discloses the implementation procedure of mechanism, embodiment proves it in anonymous success rate
And the anonymous aspect of collection size two of reduction has preferable effect.
The present invention has the following advantages and beneficial effect relative to prior art：
The present invention is by the way of the anonymous collection of buffering, the method being combined using global optimum and local optimum, in internal memory
The anonymous collection for being intended to global optimum is constructed in the case of expense is less, on the premise of privacy of user requirement is met, to drop
The mean size of low anonymous collection, improves the service quality of user；Secondly, the present invention proposes the concept of missing values, and each round is preferential
Candidate's anonymity collection that missing values are minimum is selected, to shorten anonymous collection build time, anonymous success rate is improved.
Brief description of the drawings
Fig. 1 is user's query process schematic diagram of the present invention.
Fig. 2 is the detail flowchart of the inventive method.
Fig. 3 (a) is Ao Dengbao cities road net model used in the embodiment of the present invention.
Fig. 3 (b) is Road Network Sub-graph used in the embodiment of the present invention.
Embodiment
This section explain in detail the present invention specific algorithm process, then in conjunction with the embodiments and accompanying drawing the inventive method is made into
One step is explained.
Embodiment
The location privacy protection method based on semantic context of the present invention, proposes the anonymous mode set of buffering, is based on first
The anonymous collection of buffering, while help user completes anonymous collection construction, concentrates anonymity and includes less sensitive semantic locations, even if
Anonymity collection is relatively small, so that user can enjoy higher service quality.Because user is usually movable, the road on road
Pessimistic concurrency control is more tallied with the actual situation, therefore the present invention is modeled using road net model to map.Secondly, the inventive method considers
Position it is semantic, by the position on map it is semantic be attached on the road junction away from its nearest neighbours, i.e. part road junction
Comprising semantic information, this class road junction has certain sensitiveness for a user.User initiates inquiry in the present invention
The complete procedure of service is enjoyed as shown in figure 1, comprising the steps of.
The first step：User is positioned by mobile device active request positioner to user；
Second step：User initiates location-based privacy according to actual needs, to center anonymous server and inquired about；
3rd step：Center anonymous server is asked according to user, is the anonymous collection of user's construction, the construction process of anonymity collection is such as
Shown in Fig. 2；
4th step：Center anonymous server replaces user's actual position to initiate to inquire about to LBS service device using anonymous collection；
5th step：The inquiry that LBS service device is sent according to center anonymous server, searching database will be satisfactory
Data send back to center anonymous server；
6th step：Center anonymous server is by after the data filtering received, back to mobile subscriber.
The core methed of the present invention mainly acts on the 3rd step：Construction meets the optimal anonymous collection of privacy of user requirement.This
Invent the concept being related to or module is as follows.
Define 1：Semantic locations popularity, is represented with pop, weighs the probability that user appears in the semantic locations, pop ∈
[0,1)。
Define 2：Position semantic type, is represented with pt, the concrete meaning of descriptive semantics, such as hospital, school, public place of entertainment
Deng.
Define 3：Semantic locations road network, is represented with non-directed graph G=(V, E, pts, pops).Wherein：V is vertex set, each
Summit is a road junction；E is side collection, and each edge represents a section, is connected to two summits.Pts is the language of road network
Adopted type set, pops is the semantic popularity set of road network.In this method, the semantic locations information in section, which, to be attached to apart from this
On the nearest summit in position, i.e. part of nodes includes semantic information in V, arranges that the summit of undeliverable attached semantic information is referred to as " handing over
The cross road mouthful ", semantic summit attached is referred to as semantic locations.
Define 4：Anonymity collection, is represented with S, is G subset.
Define 5：The anonymous collection of buffering, anonymity collection is buffered, and its all elements is all candidate's anonymity collection.
Define 6：User profile, is represented using Pfile, Pfile=longitude, latitude, ID, PTs, θ,
Q, Lmax, Cmax }.Wherein longitude and latitude represents the longitude and latitude of user position；ID is user identity；PTs
For semantic type sensitive for a user；θ requires for anonymous collection S sensitivity value；Q inquires about for user；Lmax represents anonymous collection S
Middle element number is no more than Lmax, and Cmax represents that buffering anonymity leaves the number of element concentratedly no more than Cmax.
Define 7：Sensitivity rate (Sensitive ratio), is represented with r, the sensitivity for measuring anonymous collection.To given
Anonymous collection S Sensitivity rate rSDefined by formula 1：
rS=popS(Sens)/popS(), formula 1
Wherein, popS(Sens) popularity sum of the semantic type of anonymous collection S interior joints in PTs, pop are representedS(.)
Represent all node popularity sums in anonymous collection S.
Define 8：θ-secure anonymous collection, refers to anonymous collection of the Sensitivity rate no more than θ.
Define 9：Popularity missing values represent that anonymity collection S reaches that required popularity value is designated as dp before θ-safety with dpS,
It is defined as shown in Equation 2：
Module 1：Neighbours' searching modul.Search the adjacent node of all nodes in set.
Module 2：Sensitivity rate computing module.Anonymous collection S Sensitivity rate r is calculated according to formula 1S。
Module 3：Locating module.The longitude and latitude sent according to user determine user where position.
Major deployments of the present invention are in the anonymous server of center, and center anonymous server mainly completes following two work：
1) receive user's request, and be the optimal anonymous collection of user's construction；2), it is necessary to result after LBS service device returns to result
Filtered, the data for meeting user's requirement are only issued into user.Anonymity concentrates the node included more, and LBS service device needs
The inquiry of execution is more, and time loss is more, therefore the target of anonymous server is：How before privacy of user requirement is ensured
Put, selection as far as possible includes the minimum anonymous collection of nodes.This is also key problems-solving of the present invention.
Anonymous server is emulated using PC in the embodiment of the present invention, and in map simulator (Network-based
Generator of Moving Objects：NGMO performed in).The simulator in advance imports map datum, analog subscriber
Query process, and help user to complete the optimal anonymous construction collected.Its detailed process is as follows：
The first step：User sends request, including：Longitude, latitude, ID, PTs, θ, Q, Lmax, Cmax；
Second step：Center anonymous server initializing various variables, the anonymous collection S of definition, the anonymous collection ES of two bufferings and
ES ', the position Loc according to where the longitude and latitude of transmission determines user.S={ Loc }, ES={ }, ES '={ S }；
3rd step：The anonymous collection of construction, its idiographic flow such as Fig. 2, detailed step is as follows：
1) the anonymous element number for integrating ES ' of buffering is set as num, and ES ' all elements are arranged by missing values ascending order.For
Element S in ES 'i(1≤i≤num, SiFor set of node), travel through SiIn all nodes neighbours, if SiInterstitial content be mi(1
≤ i≤num), by SiMiThe neighbours of individual node respectively with SiCombination, is obtainedIndividual new set, during combination, neighbours
For the preferential of intersection, next to that non-sensitive semantic locations, are finally sensitive semantic locations, are then calculated by order of addition
SetSensitivity rate rSjIf, rSjNo more than θ, then S is returnedjAs anonymity collection, anonymity terminates.It is no
Then, ES=ES ∪ { Sj}。
2) clearing buffers anonymity collection ES '.If | ES |>Cmax, chooses the less preceding Cmax element of missing values in ES
Add ES '；Otherwise the whole elements of ES are added into ES ', ES={ }；
3) element S of any one in ES ' is judgedi(1≤i≤Cmax, SiBy set of node) whether the nodes that include be more than
Lmax, such as SiComprising nodes be more than Lmax, algorithm terminate, anonymity failure, return empty set.Otherwise turn 1).
After said process terminates, there are two kinds of results：1) one includes the set for being no more than Lmax element, anonymity success；
2) empty set, anonymity failure.The mode that above-mentioned steps employ the anonymous collection of buffering first constructs anonymous collection, meet user θ-
In the case of safety, the included number of vertex of anonymity collection is minimum.
The implementation process of embodiment is discussed below.The present embodiment includes two parts, and Part I is explained with styles of cases
Algorithm detailed process；Part II analyzes embodiment the simulation experiment result, including the anonymous success rate of algorithm and anonymous ensemble average it is big
It is small.
Fig. 3 (a) is the cartographic model used by this embodiment emulation platform NGMO.Fig. 3 (b) is certain part area in Fig. 3 (a)
The semantic road net model in domain.Its nodal community includes：Semantic type and nodal scheme.Semantic type H correspondences hospital, O correspondences are done
Public room, Sc correspondences school, E correspondences public place of entertainment, M correspondences supermarket, P correspondences park, I is represented without semantic road junction.
The user configuration information of Part I is as follows：PTs={ H, O }, θ=0.5, Lmax=3, Cmax=1；If user position
At v1 nodes, i.e. Fig. 3 (b) people shape figure；The popularity of used all kinds of semantic locations is set as { H=0.15, Sc=
0.2, O=0.25, E=0.15, M=0.15, P=0.1, I=0 }；
The first round, ES '={ S }, S={ v1 }, therefore set S neighbours are v2, v5.V2 is intersection, prioritizing selection v2
With the new set S of S compositions1={ v1, v2 }, now rS1=0.15/0.15=1>0.5, it is unsatisfactory for privacy requirements, ES=ES ∪
{S1}.Then v5 and set S is constituted into new set S2={ v1, v5 }, rS2=0.4/0.4=1>0.5, privacy requirements are unsatisfactory for,
ES=ES ∪ { S2, now ES={ { v1, v2 }, { v1, v5 } }, the anonymous collection ES ' of buffering is emptied.The anonymous collection of another buffering
Element number is 2 in ES, bigger than Cmax.Therefore Cmax addition ES ' before being picked out according to popularity missing values in wherein ES,
dpS1=0.15/0.5-0.15=0.15, dpS2=0.4/0.5-0.4=0.4.Due to dpS1<dpS2, select S1Hidden as more excellent
Name collection.Now, ES '={ { v1, v2 } }, ES={ }.Set S1In the positional number that includes be 2, less than Lmax, algorithm continues.
In second wheel, the anonymous collection ES ' of buffering only { v1, v2 }, then ES ' neighbours are v5, v3, v6.According to sensitivity,
Prioritizing selection v6 and S1The new set S of composition3={ v1, v2, v6 }, its Sensitivity rate rS3=0.15/0.4<0.5, set S3Reach that θ pacifies
Entirely, S therefore is directly returned3It is used as anonymity collection.Algorithm is terminated.
If the Sensitivity rate that set is now not present is no more than 0.5, need in the way of the first round, by { v1, v2, v5 },
{ v1, v2, v6 } is added to ES ' with the minimum set of Sensitivity rate missing values in { v1, v2, v3 }, then judges any one collection in ES '
Whether the nodes of conjunction such as not less than Lmax, continue executing with algorithm more than Lmax, until anonymous success；As more than Lmax if
Anonymity failure.
Part II：This part emulation user initiates inquiry, the performance of parser in every respect.Embodiment analog subscriber
Initiate inquiry 100,000 time, performance of the analysis embodiment of the present invention in terms of anonymous success rate with anonymous collection size.Table 1 is listed
The detail parameters of implementation process of the present invention：
Table 1
By embodiment center anonymous server execution after, shown in its simulation result table 2, table 2 represent anonymous success rate,
The relation table of anonymous ensemble average size and θ.
| θ | 0.2 | 0.4 | 0.6 | 0.8 |
| Anonymous success rate | 0.810345 | 0.982758 | 1 | 1 |
| Average anonymous collection size | 12.5957 | 6.6491 | 4.4482 | 4.3103 |
Table 2
Table 2 lists anonymous success rate and situation of change of the anonymous ensemble average size with θ.In terms of success rate, θ=
In the case of 0.2, i.e. susceptibility requirement is very strict, and success rate can reach more than 80%, when anonymity collection susceptibility is down to 0.6,
Success rate can reach very.In terms of anonymity collection size, in θ=0.2, the mean size of anonymity collection is only 12.5957.When
When Sensitivity rate requirement is reduced to 0.6, average anonymous collection size only 4.3103.Data above shows the present invention with higher success rate
While ensureing privacy of user, anonymous ensemble average size is greatly reduced so that LBS service device spends less on data query
Time, improve the service quality enjoyed of user.
In summary, the present invention proposes a kind of location privacy protection method based on semantic context, for Existing methods
The problem of only considering secret protection but without balancing user service quality, proposes the mode of the anonymous collection of buffering, protects first in method
It is optimal anonymous collection of user's construction comprising minimum position while demonstrate,proving privacy of user.This method is with higher anonymous success rate
While ensureing that privacy of user is safe so that anonymity collection size is relatively small, reduces period of reservation of number, improves user and enjoy
The quality serviced.
Above-described embodiment is preferably embodiment, but embodiments of the present invention are not by above-described embodiment of the invention
Limitation, other any Spirit Essences without departing from the present invention and the change made under principle, modification, replacement, combine, simplification,
Equivalent substitute mode is should be, is included within protection scope of the present invention.
Claims (4)
1. a kind of location privacy protection method based on semantic context, it is characterised in that comprise the following steps：
(1) center anonymous server initialization map datum, highway network is modeled as by map datum；
(2) user initiates inquiry according to demand, by location information, inquires about content, privacy requirements and identity information are packaged into message Q
It is sent to center anonymous server；
(3) center anonymous server is according to Q, and analysis determines position Loc of the user on road network, the anonymous collection S=of initialization
{ Loc }, the anonymous collection ES={ } of initialization buffering and ES '={ S }.
2. the location privacy protection method according to claim 1 based on semantic context, it is characterised in that in step
(1) in, the center anonymous server is according to the anonymous collection of following steps construction：
1) the anonymous element number for integrating ES ' of buffering is set as num, and ES ' all elements are arranged by missing values ascending order；For in ES '
Element Si, wherein 1≤i≤num and SiFor set of node, traversal set SiIn all nodes neighbours, if set SiNodes
Mesh is mi, wherein 1≤i≤num, by set SiMiThe neighbours of individual node respectively with SiCombination, is obtainedIndividual new collection
Close, during combination, neighbours are preferential for intersection, next to that non-sensitive semantic locations, are finally sensitive semantic locations, then
By order of addition set of computations SjSensitivity rate rSj, such as rSjNo more than θ, S is returnedjAs anonymity collection, anonymity terminates, whereinOtherwise, ES=ES ∪ { Sj}；
2) clearing buffers anonymity collection ES '；Now, if | ES |>Cmax, before selection missing values are less in the anonymous collection ES of buffering
Cmax element adds ES '；Otherwise the whole elements of ES are added into ES '；Finally empty ES；
3) any one element S in the anonymous collection ES ' of buffering is judgediComprising nodes whether be more than Lmax, 1≤i≤Cmax,
SiFor set of node, such as SiComprising nodes be more than Lmax, algorithm terminate, anonymity failure, return empty set；Otherwise go to step 1).
3. the location privacy protection method according to claim 1 based on semantic context, it is characterised in that in step
(3) in, local optimum and global optimum is combined by the way of the anonymous collection of buffering, is hidden with two bufferings that size is defined by the user
Name collection ES and ES ' finds optimal anonymous collection.
4. the location privacy protection method according to claim 1 based on semantic context, it is characterised in that in step
(3) in, when judging that anonymous collection is good and bad, it is proposed that the concept of anonymity collection popularity missing values, popularity degree missing values are got over
Small anonymous collection is better, and the calculating of missing values uses equation below：
Wherein, S collects to be anonymous, popS() represents to calculate the semantic popularity sum of a certain class, pop in anonymous collection Ss(Sens) represent
The semantic popularity sum sensitive to user in anonymity collection S；pops() represents the total popularity sums of anonymous collection S.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
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