CN109257762A - Match electric terminal illegal wireless communication link detection method based on wireless signal strength Density Clustering Analysis - Google Patents
Match electric terminal illegal wireless communication link detection method based on wireless signal strength Density Clustering Analysis Download PDFInfo
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W24/00—Supervisory, monitoring or testing arrangements
- H04W24/08—Testing, supervising or monitoring using real traffic
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B17/00—Monitoring; Testing
- H04B17/30—Monitoring; Testing of propagation channels
- H04B17/309—Measuring or estimating channel quality parameters
- H04B17/318—Received signal strength
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W12/00—Security arrangements; Authentication; Protecting privacy or anonymity
- H04W12/12—Detection or prevention of fraud
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W36/00—Hand-off or reselection arrangements
- H04W36/0005—Control or signalling for completing the hand-off
- H04W36/0083—Determination of parameters used for hand-off, e.g. generation or modification of neighbour cell lists
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W48/00—Access restriction; Network selection; Access point selection
- H04W48/16—Discovering, processing access restriction or access information
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W48/00—Access restriction; Network selection; Access point selection
- H04W48/20—Selecting an access point
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Abstract
It is a kind of that electric terminal illegal wireless communication link detection method is matched based on wireless signal strength Density Clustering Analysis, when being with electric terminal without cell reselection, signal strength data in all wireless base stations that can be received 24 hours obtains Euclidean distance and average Euclidean formula distance between each base station radio signal strength, is used as Density Clustering radiuses for 2 times of the Euclidean distance that is averaged；The class cluster of cluster is formed using DBSCAN algorithm progress Density Clustering in conjunction with the Euclidean distance matched when electric terminal needs to carry out cell reselection between the wireless signal strength of each base station.If only one class cluster of cluster result and no noise spot, determine the cell base station of gravity treatment for normal Base Station；If cluster result includes multiple class clusters or noise spot, then the maximum class cluster of change in signal strength rate or noise spot are determined as pseudo-base station, forbid accessing such base station with electric terminal gravity treatment.This method can improve the identification and protective capacities to wireless pseudo-base station.
Description
Technical field
The invention belongs to system for distribution network of power communication and information technology fields, in particular to a kind of strong based on wireless signal
That spends Density Clustering Analysis matches electric terminal illegal wireless communication link detection method.
Background technique
With the quick raising of distributed energy permeability, to meet the needs of intermittent cleaning energy accesses on a large scale,
Researcher propose fusion with advanced power electronic technique, information technology and intelligent management technology, by a large amount of distributed generation resources,
Distributed energy storage device and all kinds of electric loads constitute the energy internet of the skeleton based on electric power networks.Energy internet
In, distributed energy resource system can realize hot and cold, electric collaboration Optimum utilization by the communication technology, improve efficiency of energy utilization, reduce
With energy cost；And source lotus production and marketing collaboration is promoted by Demand Side Response, intermittent cleaning energy consumption ability is significantly improved, is promoted
To the gradually substitution of traditional fossil energy.The safe and reliable communication of the user of dispersed distribution, energy storage device and power-supply system, are to reach
At the important foundation of preceding aim.
In recent years, increasingly multiple for the network attack of the industrial control systems such as electric power and the energy.In energy internet,
Match, is electric terminal substantial amounts, widely distributed, for cost consideration, it is impossible to is logical using the traditional private communication of electric system
Road, the overwhelming majority with electric terminal through radio communication base station access telco provider provide wireless virtual private networks, and whereby with
Distribution and metering system main website carry out two-way communication.It should be pointed out that if with electric terminal access pseudo-base station and establishing non-
Method wireless communication link, it would be possible to meet with man-in-the-middle attack.Although using symmetric cryptography mode with electric terminal to be encrypted
With authentication, it is possible to malicious code is injected to ammeter, when extensive controllable burden is by under malice control scene, it is also possible to
Directly threaten the safe and stable operation of power grid.Match electric terminal class of safety protection in energy internet to improve, it is necessary to
Study illegal wireless communication link detection method.
The GPRS communication pattern of 2G only has wireless base station to the unidirectional authentication of communication terminal, wirelessly with electric terminal access
Pseudo-base station may be accessed when virtual Private Network and meets with malicious attack.When carrying out attack destruction using pseudo-base station, attacker can be first
The carrier information of Target cell is measured and detected by signal collecting device.After detecting Target cell frequency point information, pseudo-base station
Consistent system broadcasts are set with operator by emitting in the special frequency channel range of Target cell using higher transmission power
Information.When receiving pseudo-base station system broadcasts with electric terminal, because GPRS lacks perfect wireless base station authentication mechanism, pseudo-base station
The parameter configuration of changeable GPRS cell reselection forces terminal to carry out cell reselection with transmission power is improved.Terminal accesses pseudo- base
After illegal wireless communication link is established at station, attacker can get the Identity Code (IMSI) and balance of plant identification code of terminal
(IMEI) key informations, so that the safety of the network communication between distribution terminal drastically reduces such as.Match electric terminal once breaking through
The single-point of key protects, and can directly attack with electric terminal.Although having carried out symmetric cryptography with electric terminal, it is no lack of use
Spain's ammeter of identical 128 symmetric cryptographies injects the precedent of malicious code after being cracked.
Mainly have in the measure that the mobile communication terminals such as mobile phone are used to resist pseudo-base station: the 1. broadcast letter of radio communication base station
It include base station location region code (Location Area Code, LAC), base station number (Cell ID, CID), signal strength in breath
(Received Signal Strength Indication, RSSI).For the communication terminal under the GPRS state of 2G that works
For, although lacking the network authentication to wireless base station side, terminal can also judge to receive according to the setting rule of base station information
The base station information identification arrived is abnormal, such as abnormal LAC, CID (such as LAC=10 or 10000, CID=10)；2. for satellite
The wireless communication terminals such as the mobile phone of positioning function can also be inquired according to base station number and obtain latitude and longitude of base station data, further according to certainly
The distance between body longitude and latitude location Calculation communication terminal and wireless base station.When distance significantly more than wireless base station signal emit away from
From when can be determined as pseudo-base station.It should be pointed out that aforementioned mobile phone terminal is used to resist the measure of pseudo-base station and is not suitable for
In with electric terminal.Because satellite positioning module is not configured with electric terminal, cannot using similar mobile phone terminal method according to
Itself latitude and longitude information differentiates the radio communication base station true and false.
With the signal for being likely to be received the multiple radio communication base stations in periphery in electric terminal operation.It is received with electric terminal
Each wireless base station wireless signal strength mainly and its at a distance from communication base station, weather (rain, mist, snow) and house block grade rings
Border factor is related.Because with electric terminal position and its with the distance between radio communication base station and whether block be to immobilize
, under conditions of weather condition is constant, the position locating for it is depended primarily on the received radio signal strength of electric terminal
It sets.In the case where radio communication base station distance and house stop factor permanence condition, the wireless signal strength that is received with electric terminal
It is mainly influenced by weather condition, and there is apparent correlation.When weather is good, each base station signal strength received compared with
Well, when misting rainy, each base station signal strength has obvious decaying.
Wireless communication pseudo-base station is the object that the telco providers such as China Telecom and China Mobile are sternly hit.It is beaten to escape
It hits, wireless communication pseudo-base station, which is often taken to shoot, changes a local way.Everywhere, after pseudo-base station booting, signal is strong
Degree can rise to from 0 to intensity the level for being apparently higher than normal wireless communication base station, to inveigle wireless communication terminal re-selecting cell to connect
Enter pseudo-base station.It is actual communication base station figure compared with pseudo-base station wireless signal strength, as seen from the figure, actual communication base referring to Fig. 1
Standing has notable difference with the wireless signal strength change curve of pseudo-base station, but the really wireless signal strength of radio communication base station
Variation tendency is close, inventors believe that it is possible that according to the variation tendency similitude of wireless signal strength carry out clustering,
Identify that class cluster similar in variation tendency is true wireless base station, and other change in signal strength rates it is big then can temporarily be considered as puppet
Base station.
When detecting pseudo-base station, keep the cluster radius of Density Clustering constant, until pseudo-base station access has been not detected
When, just update the cluster radius of Density Clustering.24 hours time windows are used when due to carrying out signal strength Density Clustering, it can be with
Detect that pseudo-base station signal strength jumping moment causes the difference with normal Base Station wireless signal strength, until jumping moment at any time
Between window roll throughput time window, i.e., 24 hours after jumping moment, just can no longer detect the presence of pseudo-base station, thus start more
The clustering parameter of new Density Clustering.For the radio communication base station restarted again by maintenance outage, because base station signal strength has mutation,
Also it will need to wait for just running for 24 hours and be accessed with electric terminal.
Summary of the invention
Certification, shortage detection identification are encrypted illegally the object of the present invention is to be directed to and rely only on key with electric terminal at present
The problem of wireless communication link technical method, proposes a kind of non-with electric terminal based on wireless signal strength Density Clustering Analysis
Method wireless communication link detection method avoids accessing illegal communication link with electric terminal, improves class of safety protection.
In order to achieve the above object, the technical scheme adopted by the invention is that: one kind is based on wireless signal strength Density Clustering point
Electric terminal illegal wireless communication link detection method is matched in analysis, and the method steps are as follows:
Step 1) selection one can detect that the wireless communication in 24 hours is gone in all wireless base stations of signal with electric terminal
Number intensity data, is normalized those wireless signal strength datas detected, calculates each within this time range
Euclidean distance and average Euclidean distance between the wireless signal strength data of wireless base station；Density Clustering parameter is set, that is, is set
The radius for determining Density Clustering is 2 times of average Euclidean distance of each wireless base station wireless signal strength, in the Density Clustering radius
Sample number is at least 2；
Step 2) determines whether cell reselection should be needed with electric terminal, enters step 1) if being not necessarily to gravity treatment, otherwise into
Enter step 3)；
Step 3) goes over the moment and the moment each in 24 hours when this needs to carry out cell reselection with electric terminal
The wireless signal strength data of wireless base station is normalized；It is strong to calculate different radio base station radio signal in this time
Euclidean distance of the degree between；And the Density Clustering parameter set in step 1) is combined to press existing DBSACAN Density Clustering
Algorithm is clustered；
Step 4) judges cluster result: if cluster result only has a kind of and do not include noise spot, determining gravity treatment
Cell base station be normal Base Station, enter step 1)；If cluster result has multiclass or comprising noise spot, determine in this time
The maximum a kind of or corresponding wireless base station of noise spot of wireless signal strength accumulated change amplitude is pseudo-base station, and keeps density poly-
Class parameter constant enters step and 2) detects whether there is pseudo-base station access again, when pseudo-base station access has been not detected, enters step
1)。
It is above-mentioned refer to those wireless signal strength datas detected are normalized, and to match electric terminal
Whether cell reselection is needed, the calculating of the Euclidean distance of each wireless base station wireless signal strength, and it is close by existing DBSACAN
It is all existing conventional techniques in the art that degree clustering algorithm, which carries out cluster,.
There are notable differences with variation tendency of the actual communication base station on wireless signal strength for pseudo-base station by the present invention
The characteristics of, when operating normally with electric terminal without cell reselection switching wireless base station, calculate each nothing in 24 hours in the past
Euclidean distance between line base station radio signal strength, and using 2 times of radiuses as Density Clustering of average Euclidean distance；It detects
It is strong to base station radio signal each in past 24 hours according to determining clustering parameter when base station need to be switched by meeting cell re-selection conditions
Degree is according to progress Density Clustering.Because real ones change in signal strength trend is close, and pseudo-base station sign mutation, if all base stations
It is clustered into a kind of and there is no noise spot, be then normal Base Station, wireless base station switching can be carried out；Otherwise will tire out within 24 hours in the past
The maximum class cluster of product change in signal strength or noise spot (form noise spot in the presence of single puppet base base station, 2 pseudo-base stations are only one
Class, therefore when pseudo-base station quantity is less than 2, it is possible to only form noise spot, rather than class cluster) it is determined as pseudo-base station, forbid
Such base station is accessed with electric terminal, to avoid access pseudo-base station.
It is whole with electricity consumption based on signal strength Density Clustering to provided by the invention in the following with reference to the drawings and specific embodiments
End illegal wireless communication link detection method is described in detail.
Detailed description of the invention
Fig. 1 is actual communication base station and pseudo-base station wireless signal strength curve disparity map.
Fig. 2 is DBSCAN algorithm cluster schematic diagram.
Fig. 3 is the actual wireless intensity curves of the wireless base station in embodiment.
Fig. 4 is the DBSCAN algorithm cluster schematic diagram of the wireless base station in embodiment.
Fig. 5 is cluster result analysis chart.
Specific embodiment
The following examples are only intended to illustrate the technical solution of the present invention more clearly, and cannot be used as a limitation the limitation present invention
Protection scope.
The present invention matches electric terminal illegal wireless communication link based on wireless signal strength Density Clustering Analysis to be a kind of
Detection method, this method mainly include the determination of wireless base station wireless signal strength historical time section width, for the period
Wireless signal strength data normalized, determines each clustering cluster at the signal strength Density Clustering based on DBSCAN clustering algorithm
Generic attribute so that cluster class cluster belonging to pseudo-base station be labeled as exception class so that adapted terminal equipment not gravity treatment connects
Enter pseudo-base station, the specific steps of which are as follows:
Step 1) selection one can detect that the wireless communication in 24 hours is gone in all wireless base stations of signal with electric terminal
Number intensity data, is normalized those wireless signal strength datas detected, calculates each within this time range
Euclidean distance and average Euclidean distance between base station radio signal strength data；Set Density Clustering parameter (Density Clustering half
Sample number in diameter and Density Clustering radius), that is, the radius of Density Clustering is set as between each wireless base station wireless strengths signal
2 times of average Euclidean distance, the sample number (sample number, that is, wireless base station number) in the Density Clustering radius is at least 2；
Whether step 2) judgement should need cell reselection with electric terminal, enter step 1) if being not necessarily to gravity treatment, otherwise into
Enter step 3)；
Step 3) goes over the moment and the moment each in 24 hours when this needs to carry out cell reselection with electric terminal
The wireless signal strength data of wireless base station is normalized；It is strong to calculate different radio base station radio signal in this time
Euclidean distance of the degree between；And the Density Clustering parameter set in step 1) is combined to press existing DBSACAN Density Clustering
Algorithm is clustered；
Step 4) judges cluster result: if cluster result only has a kind of and do not have noise spot, determining gravity treatment
Cell base station is normal Base Station, is entered step 1)；If cluster result has multiclass or comprising noise spot, nothing in this time is determined
The maximum a kind of or corresponding wireless base station of noise spot of line signal strength accumulated change amplitude is pseudo-base station, and keeps Density Clustering
Parameter constant enters step and 2) detects whether there is pseudo-base station access again, when pseudo-base station access has been not detected, enters step
1)。
Pseudo-base station will be invaded with electric terminal communication equipment it may first have to be forced and be carried out cell reselection access with electric terminal
Other base stations.If adapted terminal equipment can identify and refuse to access pseudo-base station, that is, it can guarantee and itself do not access illegal wireless
Communication link.Telco provider possesses complete technological means, can be pseudo- according to the base station signal tracking, positioning and the strike that detect
Base station.To escape strike, pseudo-base station dare not be stayed for a long time in same region, and the duration is shorter.Therefore, as long as at a whole day 24 hours
Period in do not access emerging pseudo-base station, can stop telco provider positioning, strike and remove pseudo-base station time,
Guarantee with electric terminal safety.
With electric terminal detect the absolute value of different communication base station radio signal strength by with electric terminal and base station it
Between distance influence, wireless signal strength absolute value distribution is more wide in range.Such as cluster is carried out using absolute value to be hardly formed
The density area of aggregation.In addition the present invention uses the variation tendency of wireless signal strength for according to cluster, it is therefore desirable to press first
(1) wireless signal strength data is normalized in formula:
x*=(x-min)/(max-min) (1)
In formula: min is the minimum value of wireless signal strength data sequence in 24 hour periods, and max is data sequence
Maximum value, x are former data, x*For the wireless signal strength data after normalization.
The class cluster similarity measurement of this method is determined using Euclidean distance.When operating normally without cell reselection, per a period of time
It carves and calculates in 24 hour periods before this and should match between all base station radio signal strength datas that electric terminal can detect
Euclidean distance and average Euclidean distance, and using 2 times of average Euclidean distance as the cluster radius for carrying out Density Clustering, to adapt to
Base station sparse region needs, it is at least 2 base stations in one kind that the class cluster smallest sample number that cluster is arranged, which is 2,.Because pseudo-base station is believed
Number variation tendency and other base stations are significantly different, and 2 samples that single pseudo-base station is possible to be not achieved class cluster requirement not will form
Class cluster, and isolated noise spot can be become.
It detects when needing to carry out cell reselection, the cluster radius and class cluster smallest sample number that utilization determines before this are to current
Wireless base station historical signal intensity data in 24 hours carries out the Density Clustering based on DBSCAN algorithm, forms all kinds of clusters
Cluster.
If cluster result only has a kind of and does not include noise spot, then determine that all base stations are normal Base Station, it can be with gravity treatment
Cell accesses other base stations.
If cluster result is multiclass or comprising noise spot, and class cluster belonging to the base station of cell reselection access or noise spot are
The maximum one kind of accumulated history change in signal strength then determines that it is pseudo-base station, and keeps the clustering parameter (cluster set before this
Minimum sample number in radius and cluster radius) it is constant, when waiting has not detected pseudo-base station access again, just update Density Clustering
Cluster radius, to restore the normal signal jumping phenomenon of the real ones such as normal operation after adapting to base station down maintenance.
As a kind of density clustering algorithm of classics, DBSCAN (Density Based Spatial Clustering of
Applications with Noise) it can be divided according to sample distribution density with any in having noisy state space
The class cluster of shape, can effectively solve the problem that need to preset number of clusters.DBSCAN algorithm is specific in data set by searching
Adjacent object of the object in sweep radius, when its surroundings quantity meet the formation of class cluster at least comprising number of objects when, will
These objects form a class cluster.Schematic diagram is clustered below in conjunction with the DBSCAN of Fig. 2, illustrates the basic characteristics of the algorithm:
● the radius of neighbourhood of its adjacent object cluster radius (Eps): is searched to data-oriented concentration special object.● class cluster
Minimum sample number；Be made of that data class cluster met adjacent object in certain an object and its cluster radius at least comprising object
It counts, is set as 3 in Fig. 2.
● kernel object: exists in the sample radius of neighbourhood and be no less than the several adjacent samples of the minimum sample of class cluster；In Fig. 2
A, b, c sample point is core point, cluster radius 3.
● noise object: the sample that each Density Clustering is not belonging in data set is noise sample, such as e sample point.
● density is reachable: the point and a in the radius neighborhood of core point a are reachable for direct density；The radius neighborhood of core point a
It is reachable for density between interior multiple point such as d, f；
● density is connected: sample a and sample f and sample b and sample f is that density is reachable in data set, but a and b density
It is unreachable, then claim a, b density to be connected.
In Fig. 2, scanning between all samples after Euclidean distance, be connected sample such as a, b, d, f, g of density forms a class cluster, c,
I, j, H-shaped only have 1 sample at a class cluster in the e radius of neighbourhood, for isolated noise spot.
Embodiment 1
The wireless signal that 6 wireless base stations are detected when a certain normal operation with electric terminal, is shown in Fig. 3, the past 24 is small
When interior each wireless base station signal strength data between Euclidean distance such as table 1, calculate the average value of Euclidean distance.It can by table 1
See that average Euclidean distance is about 1.0, selects 2.0 cluster radius as Density Clustering.
Table 1 operates normally moment Euclidean distance analytical table
| I=1 | I=2 | I=3 | I=4 | I=5 | I=6 | |
| I=1 | 0.969 | 0.918 | 0.898 | 1.015 | 0.973 | |
| I=2 | 0.969 | 0.850 | 0.857 | 0.859 | 0.885 | |
| I=3 | 0.918 | 0.850 | 0.941 | 0.809 | 0.891 | |
| I=4 | 0.898 | 0.857 | 0.941 | 0.947 | 1.086 | |
| I=5 | 1.015 | 0.859 | 0.809 | 0.947 | 0.944 | |
| I=6 | 0.973 | 0.885 | 0.891 | 1.086 | 0.944 | |
| Maximum Euclidean distance between real ones | 1.015 | 0.969 | 0.941 | 1.086 | 1.015 | 1.086 |
It detects when needing to carry out cell reselection to access other base stations, first to the moment and before in 24 hour periods
History wireless signal strength data be normalized, then calculate between each wireless base station wireless signal strength data
Euclidean distance such as table 2, the clustering parameter set further according to Euclidean distance between each base station and before this is (in cluster radius and cluster radius
Minimum sample number) carry out Density Clustering.As shown in Figure 4, wireless base station 1,2,3 is core point, cluster radius 2, wireless base station
1,2,3,4,5,6 be that density is connected, and is classified as one kind, and base station 7 is noise spot far from other sample points.In conjunction with Fig. 3, Fig. 4 and table
2 as it can be seen that wireless signal strength curve and real ones have notable difference, it is between real ones after the addition of pseudo-base station 7
Distance is all 7.0 or more, much larger than the maximum Euclidean distance between real ones.Under the pulling of No. 7 pseudo-base stations, real ones
2.0 or so are lifted to the mean value of the Euclidean distance of every other base station, and the average Europe of pseudo-base station and every other base station
Family name's distance is 7.735, hence it is evident that is higher than other websites.It obviously, can be according to wireless signal strength change curve by Density Clustering
Euclidean distance identify the pseudo-base station far from real ones.
2 cell reselection moment of table Euclidean distance analytical table
From the point of view of the data shown in the table 2, according to the average value of the Euclidean distance between pseudo-base station and other all base stations and
The mean value of Euclidean distance between real ones and other base stations, that is, can determine whether using each website be averaged Euclidean distance characterization move when
Between during window Density Clustering validity.
In order to verify the validity of proposed method over a longer period of time, start every 15 minutes by second day 00:00 in Fig. 5
Rolls forward mode is verified, and the average Euclidean distance by each website at each moment is drawn as shown in Figure 5.As seen from the figure,
The time segment length of history wireless signal strength data is 24 hours, and it is strong to induction signal that pseudo-base station appearance is covered in this 24 hours
Jumping moment is spent, the average Euclidean distance between 6 real ones and other all base stations is aggregated in the interval range of very little always
It is interior, and the average Euclidean distance of pseudo-base station is apparently higher than always real ones.Second day 23:45,24 hour periods are mobile
To after no longer covering first day 23:45 pseudo-base station signal jumping moment, the average Euclidean distance of pseudo-base station and real ones becomes
In consistent, No. 7 base stations are equal to real ones.At this time, it is believed that accessing without pseudo-base station, restore to roll update Density Clustering radius
Equal clustering parameters.
Claims (1)
1. a kind of match electric terminal illegal wireless communication link detection method based on wireless signal strength Density Clustering Analysis,
It is characterized in that, the method steps are as follows:
Step 1) selection one is strong with the wireless signal that electric terminal can detect that all wireless base stations of signal were gone in 24 hours
Those wireless signal strength datas detected are normalized in degree evidence, calculate each wireless within this time range
Euclidean distance and average Euclidean distance between base station radio signal strength data；Density Clustering parameter is set, i.e. setting density
2 times of average Euclidean distance of the radius of cluster between each wireless base station wireless signal strength, sample in the Density Clustering radius
This number is at least 2；
Step 2) determines whether cell reselection should be needed with electric terminal, enters step 1) if without gravity treatment, otherwise enters step
It is rapid 3)；
Step 3) goes over the moment and the moment each wireless in 24 hours when this needs to carry out cell reselection with electric terminal
The wireless signal strength data of base station is normalized；Calculate different radio base station radio signal strength number in this time
Euclidean distance between；And the Density Clustering parameter set in step 1) is combined to press existing DBSACAN density clustering algorithm
It is clustered；
Step 4) judges cluster result: if cluster result only has a kind of and do not include noise spot, determining the small of gravity treatment
Area base station is normal Base Station, is entered step 1)；If cluster result has multiclass or comprising noise spot, determine wireless in this time
The maximum a kind of or corresponding wireless base station of noise spot of signal strength accumulated change amplitude is pseudo-base station, and Density Clustering is kept to join
Number is constant, enters step and 2) detects whether there is pseudo-base station access again, when pseudo-base station access has been not detected, enters step 1).
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| CN110944333A (en) * | 2019-11-11 | 2020-03-31 | 南方电网科学研究院有限责任公司 | Power distribution and utilization terminal illegal wireless communication link detection method based on wireless signal strength accumulation change rate |
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| CN112153685A (en) * | 2019-06-26 | 2020-12-29 | 大唐移动通信设备有限公司 | RRC fault detection method and device |
| CN112954678A (en) * | 2021-01-26 | 2021-06-11 | 国网电力科学研究院有限公司 | Wireless signal fingerprint construction method and system for power wireless private network terminal |
| RU2795998C1 (en) * | 2022-02-21 | 2023-05-16 | Федеральное государственное казенное военное образовательное учреждение высшего образования "Военный учебно-научный центр Военно-воздушных сил "Военно-воздушная академия имени профессора Н.Е. Жуковского и Ю.А. Гагарина" (г. Воронеж) | Method for preventing unauthorized access to information of a cell phone subscriber |
Citations (17)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20050064922A1 (en) * | 2003-09-19 | 2005-03-24 | Owens William R. | Detector and method for detecting telephone-activated devices in idle state |
| EP2178222A1 (en) * | 2008-10-20 | 2010-04-21 | NTT DoCoMo, Inc. | Multi-antenna measurement method and multi-antenna measurement system |
| CN102970671A (en) * | 2012-11-27 | 2013-03-13 | 中国人民解放军信息工程大学 | Communication data acquisition method, pseudo base station and pseudo terminal |
| CN103648096A (en) * | 2013-12-11 | 2014-03-19 | 北京联合大学 | Method for rapidly detecting and positioning illegal base station intrusion |
| CN104168568A (en) * | 2014-08-28 | 2014-11-26 | 中国联合网络通信集团有限公司 | Mobile terminal and method for cell identity authentication through same |
| US9002359B1 (en) * | 2012-04-12 | 2015-04-07 | Sprint Spectrum L.P. | Method and system for intelligent determination of pseudonoise (PN) offsets |
| CN104602241A (en) * | 2014-12-25 | 2015-05-06 | 中国科学院信息工程研究所 | Determination method of pseudo base station and mobile terminal |
| CN104683984A (en) * | 2015-03-11 | 2015-06-03 | 无锡北邮感知技术产业研究院有限公司 | Wireless communication signal real-time monitoring and processing method and system |
| US20150160673A1 (en) * | 2013-12-07 | 2015-06-11 | Sergiy Vasylyev | Radio frequency occupancy sensing load control |
| CN104735648A (en) * | 2013-12-23 | 2015-06-24 | 中国移动通信集团上海有限公司 | Pseudo base station interference analyzing and monitoring method and device |
| CN104766427A (en) * | 2015-04-27 | 2015-07-08 | 太原理工大学 | Detection method for illegal invasion of house based on Wi-Fi |
| US20150319649A1 (en) * | 2011-12-19 | 2015-11-05 | Ofinno Technologies, Llc | Beamforming Handover Messaging in a Wireless Network |
| US20160066202A1 (en) * | 2014-08-31 | 2016-03-03 | Sriram Dayanandan | Methods and apparatuses for graphically indicating station efficiency and pseudo-dynamic error vector magnitude information for a network of wireless stations |
| CN105451332A (en) * | 2015-11-13 | 2016-03-30 | 中国石油大学(华东) | Mobile phone based method for positioning pseudo base station |
| CN105516986A (en) * | 2016-01-08 | 2016-04-20 | 中国联合网络通信集团有限公司 | Method for detecting pseudo base station, terminal, data processor and system |
| CN105744528A (en) * | 2016-04-29 | 2016-07-06 | 宇龙计算机通信科技(深圳)有限公司 | Fake base station identification method and device and terminal |
| CN105992210A (en) * | 2015-02-09 | 2016-10-05 | 中国移动通信集团湖北有限公司 | Mobile pseudo base station positioning method and system, positioning device and positioning server |
-
2018
- 2018-09-12 CN CN201811060770.XA patent/CN109257762B/en active Active
Patent Citations (17)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20050064922A1 (en) * | 2003-09-19 | 2005-03-24 | Owens William R. | Detector and method for detecting telephone-activated devices in idle state |
| EP2178222A1 (en) * | 2008-10-20 | 2010-04-21 | NTT DoCoMo, Inc. | Multi-antenna measurement method and multi-antenna measurement system |
| US20150319649A1 (en) * | 2011-12-19 | 2015-11-05 | Ofinno Technologies, Llc | Beamforming Handover Messaging in a Wireless Network |
| US9002359B1 (en) * | 2012-04-12 | 2015-04-07 | Sprint Spectrum L.P. | Method and system for intelligent determination of pseudonoise (PN) offsets |
| CN102970671A (en) * | 2012-11-27 | 2013-03-13 | 中国人民解放军信息工程大学 | Communication data acquisition method, pseudo base station and pseudo terminal |
| US20150160673A1 (en) * | 2013-12-07 | 2015-06-11 | Sergiy Vasylyev | Radio frequency occupancy sensing load control |
| CN103648096A (en) * | 2013-12-11 | 2014-03-19 | 北京联合大学 | Method for rapidly detecting and positioning illegal base station intrusion |
| CN104735648A (en) * | 2013-12-23 | 2015-06-24 | 中国移动通信集团上海有限公司 | Pseudo base station interference analyzing and monitoring method and device |
| CN104168568A (en) * | 2014-08-28 | 2014-11-26 | 中国联合网络通信集团有限公司 | Mobile terminal and method for cell identity authentication through same |
| US20160066202A1 (en) * | 2014-08-31 | 2016-03-03 | Sriram Dayanandan | Methods and apparatuses for graphically indicating station efficiency and pseudo-dynamic error vector magnitude information for a network of wireless stations |
| CN104602241A (en) * | 2014-12-25 | 2015-05-06 | 中国科学院信息工程研究所 | Determination method of pseudo base station and mobile terminal |
| CN105992210A (en) * | 2015-02-09 | 2016-10-05 | 中国移动通信集团湖北有限公司 | Mobile pseudo base station positioning method and system, positioning device and positioning server |
| CN104683984A (en) * | 2015-03-11 | 2015-06-03 | 无锡北邮感知技术产业研究院有限公司 | Wireless communication signal real-time monitoring and processing method and system |
| CN104766427A (en) * | 2015-04-27 | 2015-07-08 | 太原理工大学 | Detection method for illegal invasion of house based on Wi-Fi |
| CN105451332A (en) * | 2015-11-13 | 2016-03-30 | 中国石油大学(华东) | Mobile phone based method for positioning pseudo base station |
| CN105516986A (en) * | 2016-01-08 | 2016-04-20 | 中国联合网络通信集团有限公司 | Method for detecting pseudo base station, terminal, data processor and system |
| CN105744528A (en) * | 2016-04-29 | 2016-07-06 | 宇龙计算机通信科技(深圳)有限公司 | Fake base station identification method and device and terminal |
Non-Patent Citations (2)
| Title |
|---|
| 张平; 崔琪楣; 侯延昭; 徐瑨: "移动大数据时代:无线网络的挑战与机遇", 《科学通报》 * |
| 戴佳筑; 华亮: "路网环境下敏感位置匿名区域的生成方法", 《计算机科学》 * |
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112153685A (en) * | 2019-06-26 | 2020-12-29 | 大唐移动通信设备有限公司 | RRC fault detection method and device |
| CN112153685B (en) * | 2019-06-26 | 2022-02-25 | 大唐移动通信设备有限公司 | RRC fault detection method and device |
| CN110944333A (en) * | 2019-11-11 | 2020-03-31 | 南方电网科学研究院有限责任公司 | Power distribution and utilization terminal illegal wireless communication link detection method based on wireless signal strength accumulation change rate |
| CN110944333B (en) * | 2019-11-11 | 2023-08-29 | 南方电网科学研究院有限责任公司 | Illegal wireless communication link detection method for power distribution and utilization terminal based on wireless signal intensity cumulative change rate |
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| RU2795998C1 (en) * | 2022-02-21 | 2023-05-16 | Федеральное государственное казенное военное образовательное учреждение высшего образования "Военный учебно-научный центр Военно-воздушных сил "Военно-воздушная академия имени профессора Н.Е. Жуковского и Ю.А. Гагарина" (г. Воронеж) | Method for preventing unauthorized access to information of a cell phone subscriber |
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