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Explicit identifiers 7KXӝFWtQKÿӏQKGDQK ID, NAME
Quasi attributes 7KXӝFWtQKNKҧÿӏQK danh
%ҧQJ1 k-DQRQ\PLW\FiFORҥLWKXӝFWtQKWURQJGӳOLӋX
ID AGE SEX ZIP PHONE SALARY
%ҧQJ2 9tGөYӅEҧQJGӳOLӋXFKѭDÿѭӧFҭQGDQK
ID AGE SEX ZIP PHONE SALARY
%ҧQJ3 9tGө 1 YӅEҧQJGӳOLӋXÿѭӧFҭQGDQK
ID AGE SEX ZIP PHONE SALARY
%ҧQJ4 9tGө2 YӅEҧQJGӳOLӋXÿѭӧFҭQGDQK
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7 FyQKLӅXKѫQPӝWWKXӝFWtQKQKҥ\FҧPYLӋFKLӋQWKӵFP{KuQKO-GLYHUVLW\WUӣ QrQNKyNKăQKѫQ [11]
- t-FORVHQHVV0{KuQKO-GLYHUVLW\NK{QJTXDQWkPÿӃQVӵSKkQEӕFӫDFiFJLi WUӏWӭFOjÿӕLYӟLEҩWNǤPӝWWKXӝFWtQKQjRWKuVӵSKkQEӕFӫDFiFJLiWUӏ NK{QJÿѭӧF[pWWӟL7X\QKLrQWURQJWKӵFWӃWұSGӳOLӋXFyWKӇGj\KRһFWKѭD WUrQPӝWYjLWKXӝFWtQKTXDVLLGHQWLILHUQjRÿyQKӡÿyNҿWҩQF{QJFyWKӇWҩQ F{QJGӵDWUrQNLӃQWKӭFQӅQEDFNJURXQGNQRZOHGJHDWWDFNQKҵPVX\UDÿѭӧF WK{QJWLQQKҥ\FҧPGӵDWUrQSKkQEӕ0һWNKiFPӭFÿӝQKҥ\FҧPFӫDWKXӝF WtQKFNJQJW\WKXӝFYjRJLiWUӏFӫDQyYtGөWKXӝFWtQKOLrQTXDQÿӃQEӋQKWұW QӃXOjGѭѫQJWtQKWKuQKҥ\FҧPKѫQVRYӟLQӃXJLiWUӏOjkPWtQK9uQKӳQJOê GRQj\P{KuQKW-FORVHQHVVÿѭӧFÿӅ[XҩWYӟLêWѭӣQJFKtQKOjWURQJPӝWOӟS WѭѫQJÿѭѫQJJӗPNWKӵFWKӇVӵSKkQEӕJLiWUӏFӫDFiFWKXӝF WtQKQKҥ\FҧP SKҧLWѭѫQJWӵVӵSKkQEӕWRjQFөFFӫDFK~QJ>12]
1.4 6ӱGөQJF{QJQJKӋEORFNFKDLQ± smart contract Ĉk\OjPӝWKѭӟQJWLӃSFұQPӟLPӝWP{KuQKÿӇFKLDVҿGӳOLӋXGӵDWUrQF{QJQJKӋ EORFNFKDLQÿѭӧFJLӟLWKLӋXӣ>4]
2 %ҧRYӋWtQKULrQJWѭÿӕLYӟLFiFGҥQJGӳOLӋXNKiFQKDX
&iFSKѭѫQJSKiSEҧRYӋWtQKULrQJWѭKLӋQWҥLKҫXKӃWWұSWUXQJYjRFiFGҥQJGӳ OLӋXVӕQXPHULFDOQKѭWXәLWiFKRһFSKkQORҥLFDWHJRULFDOGDWDQKѭJLӟLWtQK7X\QKLrQ FiFGҥQJGӳOLӋXNKiFQKѭFKXӛLYăQEҧQôFNJQJ[XҩWKLӋQQKLӅXWURQJWKӵFWӃÿzLKӓL FiFJLҧLSKiSEҧRYӋWtQKULrQJWѭSKҧLÿiSӭQJÿѭӧF
- 'ӳOLӋXYăQEҧQWH[WĈѭӧF[HPOjGӳOLӋXQKLӅXFKLӅX
- 'ӳOLӋXFKXӛLVWULQJĈһFÿLӇPOjFyFKLӅXGjLNK{QJFӕÿӏQK
&iFJLҧLSKiSEҧRYӋWtQKULrQJWѭKLӋQWҥLQәLEұWOjҬQGDQKGӳOLӋXFKӍPӟLWұS WUXQJYjRFiFGӳOLӋXtWFKLӅXYjFy ÿӝGjLtWNKiFQKDXVӕORҥL
3 &iFNӻWKXұWҬQGDQKGӳOLӋXGӵDWUrQN-anonymity
- /ѭӧFEӓ6XSSUHVVLRQ/RҥLEӓKRjQWRjQJLiWUӏFӫDWKXӝFWtQK7URQJYtGө 1 FyWKӇWKҩ\ӣWKXӝFWtQK,'ÿѭӧFWKD\WKӃEҵQJGҩX
- 7әQJTXiWKyD*HQHUDOL]DWLRQĈӕLYӟLPӛLWKXӝFWtQK[k\GӵQJPӝWFk\SKkQFҩSWәQJTXiWWKXӝFWtQKGҥQJSKkQORҥLcategorical attribute KRһFÿӏQKQJKƭD
8 UDFiFPLӅQJLiWUӏÿӕLYӟLFiFWKXӝFWtQKVӕnumerical attribute 6DXÿyWKD\WKӃ JLiWUӏFӫDWKXӝFWtQKEҵQJJLiWUӏWәQJTXiWWUrQFk\SKkQFҩSKRһFPӝWPLӅQJLi WUӏWәQJTXiWKѫQ7KXӝFWtQKSEX YjAGE WURQJYtGө o 7әQJTXiWKyDWRjQFөF*OREDOJHQHUDOL]DWLRQ7әQJTXiWKyDGӵDWUrQJLi WUӏFӫDWRjQEӝWұSGӳOLӋXWӭFOjÿӕLYӟLPӛLWKXӝFWtQK FKӍFyPӝWJLiWUӏ WәQJTXiWWѭѫQJӭQJѬXÿLӇPFӫDFiFKQj\OjÿѫQJLҧQQKѭQJEOҥLPӭF ÿӝPҩWPiWGӳOLӋXFDR7LrXELӇXFyJLҧLWKXұW,QFRJQLWR>7] o 7әQJTXiWKyDFөFEӝ/RFDOJHQHUDOL]DWLRQ7әQJTXiWKyDGӵDWUrQJLiWUӏ FӫDFiFEҧQJKLWURQJQKyPOӟSWӭFOjPӝWWKXӝFWtQK FyWKӇÿѭӧFWәQJ TXiWWKjQKFiFJLiWUӏNKiFQKDXW\YjRQKyPOӟS&iFKQj\ÿҧPEҧR PӭFÿӝPҩWPiWGӳOLӋXtWKѫQ7әQJTXiWKyDWRjQFөFQKѭQJÿӝSKӭFWҥS YӅKLӋQWKӵFFDRKѫQ0ӝWQKѭӧFÿLӇPNKiFFӫDQyOjWҥRUDVӵNK{QJÿӗQJ QKҩWYӅJLiWUӏFӫDWKXӝFWtQKGRJLiWUӏFӫDQyFyWKӇOjJLiWUӏFөWKӇӣQKyP OӟSQj\QKѭQJOҥLOjPӝWJLiWUӏWәQJTXiWӣQKyPOӟSNKiF2.$>5] vj KACA [6] OjFiF ÿҥLGLӋQWLrXELӇX
- &iFJLҧLWKXұW/ѭӧFEӓYj7әQJTXiWKyDJL~SFKHJLҩXÿLFiFWK{QJWLQULrQJWѭ QKѭQJÿӗQJWKӡLÿmOjPJLҧP ÿLJLiWUӏFӫDGӳOLӋX%rQFҥQKÿyYLӋFNӃWKӧS FiFJLҧLWKXұW/ѭӧFEӓYj7әQJTXiWKyDQj\VDRFKRÿҥWKLӋXTXҧFNJQJOjPӝW YҩQÿӅFҫQJLҧLTX\ӃW%jLWRiQN-DQRQ\PLW\GӵDWUrQ/ѭӧFEӓYj7әQJTXiW KyDÿѭӧFFKӭQJPLQKOj13-NKy
- Microaggregation&KLDWұSGӳOLӋXUDWKjQKFiFOӟSYӟLtWQKҩWNWKӵFWKӇEҧQ
JKLVDRFKRFiFWKӵFWKӇEҧQJKLWURQJWӯQJOӟSOjWѭѫQJWӵQKDX VDXÿy7әQJ TXiWKyDquasi attribute FiFEҧQJKLWURQJPӛLQKyPGӵDYjRclass centroid [10]
- Anatomy ӻ WKXұW Qj\ [HP [pW ULrQJ ELӋW Gӳ OLӋX FӫD FiF WKXӝF WtQK TXDVL attribute YjFiFWKXӝFWtQKQKҥ\FҧP1yFKLDWұSGӳOLӋXUDOjPKDLEҧQJPӝW EҧQJÿӇOѭXFiFTXDVLattribute YjPӝWEҧQJÿӇOѭXFiFWKXӝFWtQKQKҥ\FҧPKDL EҧQJQj\ÿѭӧFOLrQNӃWWK{QJTXDgroup LGWURQJÿyPӛLgroup FyNWKӵFWKӇ
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.ӻWKXұWJRPFөPFOXVWHULQJOjPӝWWURQJQKӳQJFiFKWLӃSFұQSKәELӃQÿӕLYӟL k-DQRQ\PLW\WURQJÿy[HPEjLWRiQN-DQRQ\PLW\QKѭOjEjLWRiQJRPFөPWURQJÿyPӛL FөPFytWQKҩWNWKӵFWKӇEҧQJKLWѭѫQJWӵQKDX0ӝWKѭӟQJWLӃSFұQSKәELӃQOjJRP WұSGӳ OLӋXWKjQKFiFFөPYjVDXÿyiSGөQJ7әQJTXiWKyD*HQHUDOL]DWLRQ9LӋFFiF FөPFyFiFWKӵFWKӇJҫQJLӕQJQKDXJL~SJLҧPEӟWPҩWPiWGӳOLӋXNKLWKӵFKLӋQWәQJ TXiWKyD
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IL = (xmax-xmin) / (Max-Min) ĈӕLYӟLWKXӝFWtQKNLӇXQKmQFDWHJRULFDODWWULEXWHÿӇWtQKÿѭӧFÿӝPҩWPiWÿҫX WLrQFҫQ[k\GӵQJPӝWFk\SKkQORҥLQKѭ+uQKӢÿk\TX\ÿӏQKJLiWUӏVL]H\EҵQJVӕ QӕWOiFRQFKiXFӫDQӕW\Yj6L]HOjWәQJVӕQӕWOi
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10 ĈӝÿRPҩWPiWWUrQPӝWEҧQJKLÿѭӧc ttnh EҵQJFiFKFӝQJJӝSÿӝPҩWPiWWUrQ WӯQJWKXӝFWtQKYjWUrQFҧWұSGӳOLӋXEҵQJWәQJPҩWPiWFӫDPӑLEҧQJKL'ӵDWUrQKjP ÿRÿӝPҩWPiWQKѭYұ\JLҧLWKXұWҭQGDQKGӳOLӋXÿѭӧFÿѭDUDtrong [14] WUҧLTXDEӕQ JLDL ÿRҥQGrading, Centering, Clustering YjGeneralization (GCCG) JLҧL WKXұW Qj\ ÿӗQJWKӡLFNJQJÿѭӧFVRQJVRQJKyDPӝWVӕEѭӟFQKҵPFҧLWKLӋQKLӋXQăQJ
4 %ҧRYӋWtQKULrQJWѭWURQJ.KDLSKiGӳOLӋX/XұWNӃWKӧS
1KѭÿmJLӟLWKLӋXӣSKҫQI 1KLӋQQD\OѭӧQJGӳOLӋXQJj\FjQJ OӟQbig dataGүQ ÿӃQEQJQәQKXFҫXFKLDVҿGӳOLӋXGӳOLӋXPӣÿӇQKLӅXQJѭӡLFyWKӇVӱGөQJNKDL WKiF1KӳQJSKѭѫQJSKiSNKDLWKiFJLiWUӏFӫDGӳOLӋXWURQJQJӳFҧQKFӫDPi\WtQKFy WKӇJӑLFKXQJOjNKDLSKiGӳOLӋXGDWDPLQLQJ.KDLSKiGӳOLӋXQKҳPWӟLYLӋFWuPUD WURQJWұSGӳOLӋXQKӳQJPүXSDWWHUQKD\WUtFK[XҩWUDQKӳQJWK{QJWLQFytFK.KDLSKi GӳOLӋXEDRJӗPQKLӅXNӻWKXұWWURQJÿySKәELӃQOj
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- +ӗLTX\5HJUHVVLRQ7uPUDKjPELӇXGLӉQPӕLTXDQKӋJLӳDFiFELӃQGӳ OLӋX
- 3KiWKLӋQQJRҥLOӋAnomaly GHWHFWLRQ3KiWKLӋQFiFitem QJRҥLOӋYtGө WURQJFiFӭQJGөQJ intrusion detection hay fraud detection
- 7yPWҳW6XPPDUL]DWLRQ7ҥRUDPӝWFiFKELӇXGLӉQWyPOѭӧFFKRWұSGӳ OLӋXWURQJÿyEDRJӗPFҧYLӋFWUӵFTXDQKyDYjWҥRFiFEiRFiR
- /XұWNӃWKӧS$VVRFLDWLRQUXOH7uPUDTX\OXұWNӃWKӧSJLӳDKDLKD\QKLӅX item.ӻWKXұWQj\FQJYӟL3KkQORҥLOjFiFNӻWKXұWSKәELӃQQKҩWWURQJ
4.2 .KDLSKiGӳOLӋX/XұWNӃWKӧSYjYҩQÿӅEҧRYӋWtQKULrQJWѭ
/XұWNӃWKӧSOjPӝWWURQJQKӳQJNӻWKXұWNKDLSKiGӳOLӋXSKәELӃQQKҩW.KDLSKi GӳOLӋX/XұWNӃWKӧSKѭӟQJWӟLYLӋFWuPUDPӕLOLrQKӋOXұWJLӳDFiFitemset WURQJPӝW WұSJLDRGӏFKWUDQVDFWLRQ&KRFѫVӣGӳOLӋX7OjWұSFiFJLDRGӏFKW1, t2ôWn T = {t1, t2ôWn`7JӑLOjFѫVӣGӳOLӋXJLDRGӏFKWUDQVDFWLRQGDWDEDVH0ӛLJLDRGӏFKWi bao JӗPWұSFiFÿӕLWѭӧQJ,JӑLOjLWHPVHWI = {i1, i2ôLm`0ӝWitemset JӗPNitem JӑL Ojk-itemset /XұW;-!@ YӟLFiFFҧLWLӃQÿӇ JL~SFҧLWKLӋQKLӋXQăQJFӫDJLҧLWKXұW, QKӡÿy FyWKӇFKҥ\ WӕWKѫQWUrQFiFWұSGӳOLӋX OӟQ+ӑFYLrQJӑLJLҧLWKXұWQj\Oj U-M3AR
- *7ұSFiFQKyPgroupWҥRÿѭӧFWӯWұSGӳOLӋX'
- _J_.tFKWKѭӟFKD\VӕWKjQKYLrQWURQJQKyPEҧQJKLWXSOHJ
- k-safe group1KyPEҧQJKLWXSOHYӟLVӕWKjQKYLrQNK{QJQKӓKѫQN_J_! N
- k-unsafe group1KyPEҧQJKLWXSOHYӟLVӕWKjQKYLrQQKӓKѫQN_J_N
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16 0ӝWSKpSGLFKX\ӇQWXSOHJLӳDgroup gi YjJj FyêQJKƭDNKLPjVDXSKpSGL FKX\ӇQÿyWәQJRisk(g i ) + Risk(g j ) JLҧPÿLNKLÿytWQKҩWPӝWWURQJgroup Fy ÿӝUӫLURYӅ WUӣWKjQKsafe group KRһFJLҧLWiQKRjQWRjQ'RÿyWURQJFiF EѭӟFOһS ÿӇWuPNLӃm group JÿӇGLFKX\ӇQYӟLgroup 6HO*WӕLWKLӇXKjP5LVNOj PӝWWURQJQKӳQJÿLӅXNLӋQTXDQWUӑQJQKҩW
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3KҫQWLӃSWKHR WUuQKEj\PmJLҧFӫDJLҧLWKXұWU-M3AR
1 G = set of groups obtained from D (grouping tuples similar on quasi attributes)
2 Divide G into k-safe groups set SG, k-unsafe group set UG, k-unsafe small group set UG_SMALL (unsafe groups having length k/2)
3 Construct R_care from R_initial (rules may be affected in migration operations, each rule in R_care contains at least 1 quasi attribute)
4 Calculate budget Budget(r) for all the rule r in R_care
5 Sort groups in UG by length ascendingly
3 SelG = UG.pop(0) // Pop the first unsafe group
4 UG_BIG.remove(SelG); UG_SMALL.remove(SelG)
6 remaining_groups = UG_BIG + UG_SMALL + SG
8 remaining_groups = UG_SMALL + UG_BIG + SG
9 Find group g to migrate with SelG in remaining_groups g = find_group_to_migrate(SelG, remaining_groups)
10 if g is None: // No result, continue next iteration
11 UM.add(SelG); SelG = None // SelG will be dispersed
12 else: // There is a result, consider the pair (SelG, g)
13 If migrating n tuples from SelG to g:
14 Update budget of every rule r in
15 If migrating n tuples from g to SelG:
16 Update budget of every rule r in
SG.add(SelG); UG.remove(SelG);
UG_BIG.remove(SelG); UG_SMALL.remove(SelG)
UG_BIG.remove(g); UG_SMALL.remove(g)
19 if SelG is safe and g is safe: SelG = None
20 else: SelG = unsafe group in pair {SelG, g} endwhile
21 if |UM| > 0 for each um in UM: Pop um from UM; Disperse(um)
1 For each tuple t of other groups that has migrated into SelG:
2 Return t to its initial group; |g| += 1
3 Update budget of every rule r in R_affected(g, SelG):
5 For each remaining origin member t of SelG
6 g = find_group_to_move_dispersing(SG)
7 Update budget of every rule r in R_affected(SelG, g):
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