1. Data Protection and String Search in SDDS-2005
Riad Mokadem

2. SDDS-2005 Evolution of SDDS-2004 Existent Functions
Extension of algebraic signatures
Introduction of Pre-computed algebraic signature

3. Cumulative Algebraic Signature
Encoding data in servers
Protection against incidental viewing in servers
Fast manipulation of string
Encoding form directly in servers
The fastest technology in manipulation of characters.
Prefix search
Corruption protection ( future)
Data Compression ( future)

4. Applications Servers SDDS Data Grid P2P Systems XML data Search engine
MSN ?

5. Prototype SDDS 2005 Réseau Serveur Cases en RAM Client SDDS-CP
Applications
... de
Noms
d'index
RP* S

6. Problematic Encoding\ Decoding of data by client
- Data on clear viewing per on authorized administrator
- Storage dump…
No protection data
Encoding\ Decoding of data by client
Data encoded in servers
Different possibilities of search.

7. Data structure Encoding/decoding concerns non key data.
Encoding/decoding is transparent for servers.
Limit of 256B for data
actually

8. Search of string Aalgorithms: Boyer Moore, Karp Rabin… SDDS-2005:
No sent data to search.
Sending signature
Best confidentiality
Encoding
Pré- computed algebraic signatures

9. Cumulative signature algebraic signature (p1,p2,…,pn)= pi i
Structure of Galois field GF(2f ) f>>1
symbols of size f=8,16…
primitive element 
algebraic signature (p1,p2,…,pn)= pi i
Pre-computed signature
p’i=antilog (log pi+i) Encoding pi
p’’i= p’’i-1 XOR p’i
i=n-1
i=0

10. Encoding+ sent request
Cumulative signature
Encoding+ sent request
Comparison of signatures+ verification of collision
Result of search
Client
Décoding
Pré compute of signatures Gain of search time

11. Performances d’Encodage / Décodage
Size of record
Encoding time
Decoding time
Iinsertion time
100B
0.045ms
0.042ms
0.3ms
Fast Time encoding / decoding.
Signatures pre computed serach time reduced

12. SDDS-2005 String matching functions
Prefix search
String search
Sent of signature + size of data
Longest Prefix match
Longest common String
Sent of data to comparison

13. Cumulative signature Size of case Size of inserted data
Size of last record
Size of data to search
Offset of data in last record
Time of search Sign alg
Time of search Karp Rabin
Time of search sign cumulatives
100
250 25 10 5
205
151
147
200
368
275
268
500
1123
725
702
1000
2254
1580
1526
1) La solution d’envoi de ces messages par UDP, faite par ..
2) Preparer un tampon
Unifier les messages de supp et d’insertion du meme enreg e …

14. Performance(cumulative signature)
Record Position
Size of inserted data
Size of data to search r
Offset of string
Time of search (ms) 1
100 13 80
0.65
250 5
460
Record Position
Size of inserted data
Size of prefix
Time of search (ms) 1
100 20
0.369
250 37
Préfix Search
String match search
Record Position
Size of inserted data
Size of last record
Size of prefix to search
Offset prefix
in record
Time of search (ms) 1 50 25
0.48
99/100
250
453
Longest Prefix Match
Search time in 2 servers+ comparison = Search time in only one server
1) La solution d’envoi de ces messages par UDP, faite par ..
2) Preparer un tampon
Unifier les messages de supp et d’insertion du meme enreg e …
Ecord Position
Size of inserted data
Size of last record
Size of string to search
Offset of string
Time of search (ms) 1 22 10
0.658
100
200 35 20 4
672 15
625
250 45 8
407
Longest Common String

15. Cumulative signature }New Search Functions Reduction of search time:
-Existent Algorithms existents (30% algebraic signature, 5% Karp-Rabin, Size(Data) >32B…
Non encoded data
1) La solution d’envoi de ces messages par UDP, faite par ..
2) Preparer un tampon
Unifier les messages de supp et d’insertion du meme enreg e …
}New Search Functions

16. SDDS-2005 : Cumulative signatures
Opérationnel Functions (2005):
Prefix Search
String matching
Longest Prefix match
Longest Common String
1) La solution d’envoi de ces messages par UDP, faite par ..
2) Preparer un tampon
Unifier les messages de supp et d’insertion du meme enreg e …

17. Cumulative Signatures
Théory labour (2005):
- Comparison with Karp Rabin algorithm.
Remaining work:
- Data > 256B
- Performance mesures
- Amélioration of signature calculation time (Horner scheme, Broder table…)
-Data compression (prefix, suffix, full )
1) La solution d’envoi de ces messages par UDP, faite par ..
2) Preparer un tampon
Unifier les messages de supp et d’insertion du meme enreg e …

18. The end Merci Riad Mokadem