CN110263674A - A kind of counterreconnaissance camouflage " contact clothing " generation method towards depth pedestrian weight identifying system - Google Patents
A kind of counterreconnaissance camouflage " contact clothing " generation method towards depth pedestrian weight identifying system Download PDFInfo
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Abstract
The invention discloses a kind of counterreconnaissances towards depth pedestrian weight identifying system to pretend " contact clothing " generation method, it proposes to minimize optimization method based on matching difference, and multiposition sampling is combined to generate can be changed across camera, noise pattern that position is expansible, so that in any position of pedestrian's weight identifying system monitoring area, identical noise pattern can not be mutually matched under different camera shootings, and with specific user's erroneous matching.In addition, this method incorporates physical environmental factors in noise pattern generating process, the robustness that noise is lost in printing and shooting process information is improved.The counterreconnaissance camouflage " contact clothing " that this method generates can make pedestrian's weight identifying system that can not correctly search to locate attacker, and fraud system is matched into the specific user being previously set.
Description
Technical field
The present invention designs artificial intelligent and safe field, in particular to a kind of counterreconnaissance towards depth pedestrian weight identifying system
Pretend " contact clothing " generation method.
Background technique
With the rapid development of mobile Internet, the lasting upgrading of hardware device, the production of mass data and algorithm are more
Newly, the development of artificial intelligence (AI) is irresistible, gradually permeates and change deeply the life of the mankind.Currently, the machine of being based on
The artificial intelligence technology of device study and deep learning is widely used in human-computer interaction, vision processing system, recommender system, safety
Every field, the application scenarios such as diagnosis and protection include unmanned, image recognition, malware detection, malious email mistake
Filter etc..It can be said that the arrival in artificial intelligence epoch and data calculate and the development of storage capacity promotes every field change.
It is a task of the matching across personage interested under camera that pedestrian identifies again, has in video monitoring and security fields and widely answers
With, such as suspect and missing crew's search, across camera pedestrian tracking, pedestrian activity's analysis etc..In recent years, with depth
Habit technology is quickly grown, and pedestrian's weight identifying system based on deep neural network achieves pedestrian's matching level close to the mankind,
And it is increasingly becoming main stream approach.
However, recent studies suggest that deep neural network is very fragile for specifically attacking: by input picture plus essence
Mankind's noise inconspicuous of heart building, can lure deep neural network to work with anomalous mode, this is to based on depth nerve
The types of applications of network constitutes potential threat, such as recognition of face, unmanned, malware detection.Since pedestrian identifies again
System widespread deployment in the security system and application, it is under attack to Guan Chong whether the depth of investigation pedestrian weight identifying system is easy
It wants.Once depth pedestrian weight identifying system to particular attack fragility, will have serious consequences and security threat, for example, crime point
Son, which can escape the search of law enforcement agency and positioning or spy, can invade monitored confidential areas.
Summary of the invention
The purpose of the invention is to overcome the limitation of the prior art, provide a kind of towards depth pedestrian's again identifying system
" contact clothing " generation method is pretended in counterreconnaissance.
A kind of counterreconnaissance camouflage " contact clothing " generation method towards depth pedestrian weight identifying system designed by the present invention,
It is characterized in that, comprises the following steps:
1) to given pedestrian's weight identifying system with whitepack access authority, setting attacker wants to be matched to specific
User；
2) photo group of the building attacker under each camera, designs the noise pattern generation side sampled based on multiposition
Method generates the expansible noise pattern in position；
3) the noise pattern generation method that can be changed across camera minimized based on matching difference, is made across attacking under camera
The person's of hitting image is located remotely from each other can not be by pedestrian's weight identifying system matching, and the image for making plus noise and specific user are by mistake
Match；
4) physical environmental factors are incorporated into noise pattern generating process, print noise pattern and be attached on clothes, to realize
Pedestrian's weight identifying system is attacked under reality scene.
Further, photo group detailed process of the building attacker under each camera are as follows:
Collect a large amount of attackers photo that different location is taken under monitoring camera, and the photo that every is shot
The photomontage that primary image converts is carried out, the above photo collectively forms noise spanning set.
Further, detailed process is as follows for the step 3):
By solving the optimization problem of the minimum of attacker's photo matching similarity under across camera shooting come iteratively
Find the variable noise pattern across camera；Specifically, for the photo shot from m group camera, and from specific
The photo I of user being takent, solve following optimization problem:
Wherein, target pedestrian weight identifying system is expressed as fθ(x, y)=sc, x are the image that system needs to inquire, and y is it
Pedestrian's photo that his camera is collected, θ is model parameter；x′iIt is that noise δ will be passed through and the consistent image of the person of being taken i becomes
It changes and is added to xiOn obtain；
Wherein, each iteration is from noise spanning set and specific user's photograph collection ItIn select at random photo constitute four-tuple Two photos for being attacker under same camera,It is attacker in other camera shootings
One photo of head, ItA photo in the photo group not shot for the specific user is minimized based on matching difference
Following optimization problem is solved across the noise pattern generation method that camera can be changed:
The noise of the generation gap between the feature for extracting same webcam photo of having the ability is smaller and smaller, while making across taking the photograph
The gap between feature extracted as head photo is increasing, and close with specific user's photo eigen.
Still further, the number of iterations is set as 750 times, or less than 750 in convergence complete iteration.
Further, smooth regular terms is added in the step 4):
TV (δ)=∑i,j((δi,j-δi+1,j)2+(δi,j-δi,j+1)2)。
Further, the value of noise is transformed into printer color value range in the step 4) and is printed.
Further, random image degenrate function is added in the step 4)Lose noise with height to information
Robustness.
Compared to the prior art the present invention, has the beneficial effect that
1) it proposes the novel camouflage towards depth pedestrian weight identifying system and breaks through method, it is complete by generation " contact clothing "
The counterreconnaissance camouflage of pairs of target pedestrian weight identifying system.
2) propose the optimization method that minimizes based on matching difference, generate the noise pattern variable across camera, make its
It can not match each other under the shooting of different cameras, and be matched with specific user.
3) multiposition sampling policy is considered in noise pattern generating process, the noise of generation is in any position of monitoring area
Attack effect can be reached by setting.
4) in order to improve noise pattern physical world robustness, physical environmental factors incorporate noise pattern by this method
Generating process keeps it still effective after printing and shooting process information are lost.
Detailed description of the invention
Fig. 1 is that " contact clothing " generation method frame is pretended in the counterreconnaissance towards depth pedestrian weight identifying system
Fig. 2 is the spoof attack schematic diagram towards depth pedestrian weight identifying system
Fig. 3 is the spoof attack example towards depth pedestrian weight identifying system
Specific embodiment
It is considered herein that the safety issue that depth pedestrian identifies again does not still attract attention, the meeting when being widely used
Potential security threat is brought, therefore is badly in need of a kind of counterreconnaissance camouflage " contact clothing " generation towards depth pedestrian weight identifying system
Method.
Counterreconnaissance towards depth pedestrian weight identifying system designed by the present invention pretends " contact clothing " generation method and includes
Following steps:
1) pedestrian's weight identifying system, input inquiry image are given, which exports the figure shot under other cameras
As the similarity and similarity ranking with query image.Attacker is able to access that the parameter and weight of object module, and sets
Attacker wants the specific user being matched to.
Target pedestrian weight identifying system can be expressed as fθ(x, y)=sc, wherein x is the image that system needs to inquire, and y is
Pedestrian's photo that other cameras are collected, θ are model parameter, and sc is the output of system, i.e., to carry out matched one group of photo (x,
Y) similarity score.The photo group G that the photo and system being queried are collected under other cameras is matched one by one, is exported similar
Highest photo is spent as final matching results, it may be assumed that
Y={ y1,y2,…,yK}s.tψ(fθ(x,yi))<K
Wherein K be default output match the highest photo number of score, ψ () by the photo group of collection according to
It is ranked up from high to low with score.Attacker is attack with trained pedestrian's weight identifying system neural network based
Target has whitepack access authority to object module, can access target model parameter and weight, and in setting system
Specific user, make attacker when being queried by system error hiding at the specific user.
2) building attacker collects photo group and photomontage group, designs the noise pattern generation side sampled based on multiposition
Method generates the expansible noise pattern in position, can reach attack effect in any position of monitoring area.
Constitute noise spanning set XcSpecifically: collect a large amount of attackers photograph that different location is taken under monitoring camera
Piece, and the photo that every shoots is subjected to the photomontage that primary image converts.Photomontage includes by image
The transformation gained such as translation, scaling and luminance transformation.
In the present embodiment, component noise spanning set under each camera specifically, be arranged different distance and angle 50
Sampled point collects the photo of 10 shootings in each sampled point respectively；The photo acquired for every randomly selects 5 kinds substantially
Image transformation generates 5 photomontages.For once attacking, building sum is the synthesis collection of 3000 photos.
3) the noise pattern generation method that can be changed across camera minimized based on matching difference, is made across attacking under camera
The person's of hitting image is located remotely from each other can not be by pedestrian's weight identifying system matching, and the image for making plus noise and specific user are by mistake
Match.
By solving the optimization problem of the minimum of attacker's photo matching similarity under across camera shooting come iteratively
Find the variable noise pattern across camera.Specifically, for the photo shot from m group camera, and from specific
The photo I of user being takent, solve following optimization problem:
Wherein x 'iIt is that noise δ will be passed through and the person of being taken i consistent image transformation is added to upper xiOn obtain.Optimizing
The difference of form and photo style of the noise pattern study across the person of being taken under camera is in the process to improve attacking for oneself
Ability is hit, the gap between feature that the photo that shoots attacker under across camera extracts is increasing, until can not be just
It is really mutually matched, and is all matched with the photo of specific user.
Two photos under same camera are randomly selected in spanning set every timeAnd one of other cameras
PhotoAnd the photo group I being taken in the system specific user of settingtA photo t is selected at randomiTo constitute a quaternary
Group Qi, this method be based on multiposition sampling policy, pass through the different Q of multiple groupsiNoise pattern is optimized iteratively to optimize,
The noise δ that the photo for shooting and synthesizing to multiple groups different location optimizes generation can be in any position quilt of monitoring area
Shooting can complete counterreconnaissance spoof attack.XcThe optimization problem of noise pattern will be used to solve to generate, each iteration to be from XcAnd
Specific user's photograph collection ItIn select at random photo constitute four-tupleMade by different four-tuples
The noise pattern of generation can be effective in any position of monitoring area.It will be based on multiposition sampling policy and the optimization problem knot
It closes, that is, produces and meet the expansible noise pattern that can be changed across camera of multiposition:
Wherein, λ1And λ2For hyper parameter, for controlling Different Optimization item to final result influence degree, in specific experiment I
Take λ1=0.25, λ1=0.2 generates noise pattern.The noise of generation is had the ability between the feature for extracting same webcam photo
Gap it is smaller and smaller, while keeping the gap between the feature extracted across webcam photo increasing, and and specific user
Photo eigen is close.By choosing different location and the photo of different synthetic method in spanning set, enable noise pattern
It is equally effective to the photo for the position shooting for not having " meeting ".Noise is generated with ADAM optimizer, parameter setting is as follows: study
Rate is 0.01, β1=0.9, β2=0.999.
4) consider printing and imaging error in physical world, physical environmental factors are incorporated into noise pattern generating process, it is raw
At the noise pattern of high robust, pedestrian's weight identifying system can be attacked under reality scene by printing and sticking " contact clothing ".
Consider printing and the active influence of shooting process noise pattern, physical environmental factors involvement noise pattern was generated
Journey generates the noise pattern of high robust, and so that noise is printed and is sticked can be to pedestrian's weight identifying system on the clothes of attacker
Carry out counterreconnaissance spoof attack.Firstly, this method exists in order to make the noise generated and clothes pattern seem same naturally smooth
Smooth regular terms is added in optimization problem:
Factor beta=0.001 in optimized-type is added in the regular terms.This method is by minimizing noise pattern adjacent pixel value
Between difference, the smoothness of noise is improved, so that attacker, which puts on " contact clothing ", to wake suspicion.Following determination can be beaten
The color gamut of printAnd by the value range of noiseInside bring error is printed to eliminate；Finally, due in shooting process
Environmental condition and camera device shoot noise to the loss of information, and Random Graph is added during noise generates in this method
As degenrate functionLose noise with high robust to information.In the present embodiment,
The present invention has the advantages that
1) it proposes the novel camouflage towards depth pedestrian weight identifying system and breaks through method, it is complete by generation " contact clothing "
The counterreconnaissance camouflage of pairs of target pedestrian weight identifying system.
2) propose the optimization method that minimizes based on matching difference, generate the noise pattern variable across camera, make its
It can not match each other under the shooting of different cameras, and be matched with specific user.
3) multiposition sampling policy is considered in noise pattern generating process, the noise of generation is in any position of monitoring area
Attack effect can be reached by setting.
4) in order to improve noise pattern physical world robustness, physical environmental factors incorporate noise pattern by this method
Generating process keeps it still effective after printing and shooting process information are lost.
Claims (7)
1. " contact clothing " generation method is pretended in a kind of counterreconnaissance towards depth pedestrian weight identifying system, it is characterised in that comprising such as
Lower step:
1) to given pedestrian's weight identifying system with whitepack access authority, setting attacker wants the specific use being matched to
Family；
2) photo group of the building attacker under each camera designs the noise pattern generation method sampled based on multiposition, raw
At the expansible noise pattern in position；
3) the noise pattern generation method that can be changed across camera minimized based on matching difference, is made across the attacker under camera
Image is located remotely from each other can not be by pedestrian's weight identifying system matching, and the image for making plus noise and specific user are by erroneous matching；
4) physical environmental factors are incorporated into noise pattern generating process, print noise pattern and be attached on clothes, to realize existing
Pedestrian's weight identifying system is attacked under real field scape.
2. " contact clothing " generation side is pretended in a kind of counterreconnaissance towards depth pedestrian weight identifying system as described in claim 1
Method, it is characterised in that: photo group detailed process of the building attacker under each camera are as follows:
A large amount of attackers photo that different location is taken under monitoring camera is collected, and the photo that every is shot carries out
The photomontage that primary image converts, the above photo collectively form noise spanning set.
3. " contact clothing " generation side is pretended in a kind of counterreconnaissance towards depth pedestrian weight identifying system as claimed in claim 2
Method, it is characterised in that: detailed process is as follows for the step 3):
It is iteratively found by solving the optimization problem of the minimum of attacker's photo matching similarity under across camera shooting
Variable noise pattern across camera；Specifically, for the photo shot from m group camera, and specific user is come from
The photo I being takent, solve following optimization problem:
Wherein, target pedestrian weight identifying system is expressed as fθ(x, y)=sc, x are the image that system needs to inquire, and y is other camera shootings
Pedestrian's photo that head is collected, θ is model parameter；x′iIt is that noise δ will be passed through and the person of being taken i consistent image transformation is added to
Upper xiOn obtain；
Wherein, each iteration is from noise spanning set and specific user's photograph collection ItIn select at random photo constitute four-tuple Two photos for being attacker under same camera,It is attacker in other camera shootings
One photo of head, ItA photo in the photo group not shot for the specific user is minimized based on matching difference
Following optimization problem is solved across the noise pattern generation method that camera can be changed:
Gap between the capable feature for extracting same webcam photo of the noise of generation is smaller and smaller, while making across camera
The gap between feature that photo extracts is increasing, and close with specific user's photo eigen.
4. " contact clothing " generation side is pretended in a kind of counterreconnaissance towards depth pedestrian weight identifying system as claimed in claim 3
Method, it is characterised in that: the number of iterations is set as 750 times, or less than 750 in convergence i.e. complete iteration.
5. " contact clothing " generation side is pretended in a kind of counterreconnaissance towards depth pedestrian weight identifying system as claimed in claim 2
Method, it is characterised in that: smooth regular terms is added in the step 4):
TV (δ)=∑i,j((δi,j-δi+1,j)2+(δi,j-δi,j+1)2)。
6. " contact clothing " generation side is pretended in a kind of counterreconnaissance towards depth pedestrian weight identifying system as claimed in claim 2
Method, it is characterised in that: the value of noise is transformed into printer color value range in the step 4) and is printed.
7. " contact clothing " generation side is pretended in a kind of counterreconnaissance towards depth pedestrian weight identifying system as claimed in claim 2
Method, it is characterised in that: random image degenrate function is added in the step 4)Lose noise with Gao Lu to information
Stick.
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