Strongly Separable Codes Ying Miao joint work with Minquan Cheng - - PowerPoint PPT Presentation

strongly separable codes
SMART_READER_LITE
LIVE PREVIEW

Strongly Separable Codes Ying Miao joint work with Minquan Cheng - - PowerPoint PPT Presentation

Strongly Separable Codes Ying Miao joint work with Minquan Cheng and Jing Jiang University of Tsukuba, Japan March 16, 2015, ALCOMA 15 1 1 Introduction Exam. 1.1 A (3 , 4 , 2) code C = { c 1 , c 2 , c 3 , c 4 } . c 1 c 2 c 3 c 4 c 1 c 2 c 3 ,


slide-1
SLIDE 1

Strongly Separable Codes

Ying Miao

joint work with Minquan Cheng and Jing Jiang University of Tsukuba, Japan March 16, 2015, ALCOMA 15

1

slide-2
SLIDE 2

1 Introduction

  • Exam. 1.1 A (3, 4, 2) code

C = {c1, c2, c3, c4}.

c1 c2 c3 c4 B B @ 1 1 1 1 1 1 C C A = ⇒ c1 8 > > < > > : 1 9 > > = > > ; c2 8 > > < > > : 1 9 > > = > > ; c3, 8 > > < > > : 1 9 > > = > > ; c4 8 > > < > > : 1 1 9 > > = > > ; c1 ∪ c2 8 > > < > > : 0, 1 0, 1 9 > > = > > ; c1 ∪ c3 8 > > < > > : 0, 1 0, 1 9 > > = > > ; c1 ∪ c4 8 > > < > > : 0, 1 0, 1 0, 1 9 > > = > > ; c2 ∪ c3 8 > > < > > : 0, 1 0, 1 9 > > = > > ; c2 ∪ c4 8 > > < > > : 1 0, 1 9 > > = > > ; c3 ∪ c4 8 > > < > > : 0, 1 1 9 > > = > > ;

2

slide-3
SLIDE 3

Question: Given a subset of

8 > > < > > : 0, 1 0, 1 0, 1 9 > > = > > ;

say,

8 > > < > > : 1 0, 1 9 > > = > > ;

Can we trace back to the codewords c2, c4 who produced it?

3

slide-4
SLIDE 4

Answer: Yes, we can. The subsets produced by up to two codewords are all distinct. Remark: Such kind of codes are used in multimedia fingerprinting where the identification of malicious authorized users taking part in the linear collusion attack is required to prevent pirate copies of multimedia contents.

4

slide-5
SLIDE 5

2 General Definitions and Tracing Properties

Let n, M, q be positive integers, and Q = {0, 1, . . . , q − 1}. A set C = {c1, c2, . . . , cM} ⊆ Qn is called an (n, M, q) code and each ci a codeword (or a fingerprint). ∀ C′ ⊆ C, define the descendant code of C′ as desc(C′) = C′(1) × · · · × C′(n), where C′(i) = {c(i) ∈ Q | c = (c(1), . . . , c(n))T ∈ C′}. Remark: desc(C′) consists of the n-tuples that could be produced by a coalition holding the codewords (fingerprints) in C′.

5

slide-6
SLIDE 6
  • Def. 2.1 Let C be an (n, M, q) code and t ≥ 2 be an integer.

C is a t-separable code, t-SC(n, M, q), if ∀ distinct C1, C2 ⊆ C with |C1| ≤ t, |C2| ≤ t, we have desc(C1) = desc(C2). Tracing: Given desc(C0), to trace C0, we need check desc(C′) for all C′ ⊆ C (separable code) with |C′| ≤ t, that is, the computational complexity of the tracing is O(M t). Question: Is it possible to find an efficient tracing, say, with computational complexity O(M)? Answer: In general, NOT. But in some cases, OK.

6

slide-7
SLIDE 7
  • Def. 2.2 Let C be an (n, M, q) code and t ≥ 2 be an integer.

C is a t-frameproof code, t-FPC(n, M, q), if ∀ C′ ⊆ C with |C′| = t, and ∀ c ∈ C \ C′, ∃ 1 ≤ i ≤ n s.t. c(i) ∈ desc(C′)(i).

  • Exam. 2.3 A 2-FPC(3, 3, 2) C. Any t-FPC(n, M, q) is a t-SC(n, M, q).

C = B B @ 1 1 1 1 C C A desc(C0) = 8 > > < > > : 0, 1 0, 1 9 > > = > > ;

Tracing: Given desc(C0), to trace C0, we eliminate all codewords c with c(i) ∈ desc(C0)(i). From the definition of FPC, the set of remaining codewords is necessarily C0. The computational complexity of the tracing is O(M).

7

slide-8
SLIDE 8

3 Strongly Separable Codes

Question: The constraints posed on frameproof codes are quite strong so that the number of codewords is not large enough. Can we find a new code weaker than a frameproof code but stronger than a separable code, so that the its computational complexity is the same with a frameproof code, i.e., O(M), but the number of codewords in such a code is larger than that of a frameproof code? Answer: Yes, we can.

8

slide-9
SLIDE 9
  • Def. 3.1 Let C be an (n, M, q) code and t ≥ 2 be an integer. C is a

strongly t-separable code, t-SSC(n, M, q), if ∀ C0 ⊆ C, |C0| ≤ t, we have ∩

C′∈S(C0)

C

′ = C0,

where S(C0) = {C

′ ⊆ C | desc(C ′) = desc(C0)}.

  • Exam. 3.2 A 2-SSC(3, 4, 2) C. Any t-SSC(n, M, q) is a t-SC(n, M, q).

C = B B @ 1 1 1 1 C C A desc(C0) = 8 > > < > > : 0, 1 0, 1 9 > > = > > ;

Tracing: Given desc(C0), to trace C0, we eliminate all codewords c with c(i) ∈ desc(C0)(i). The computational complexity of the tracing is O(M).

9

slide-10
SLIDE 10

It is obvious that the set

CL = B B @ 1 1 1 C C A

  • f remaining codewords necessarily contains C0. We have to find the

exact C0.

  • CL ∈ S(C0), that is, desc(CL) = desc(C0).
  • ∀ x ∈ C0 = ∩

C′∈S(C0)C′, ∃ 1 ≤ j ≤ n s.t. x(j) = 1, c(j) = 0, or

x(j) = 0, c(j) = 1 for any c ∈ CL \ {x}. Otherwise desc(CL \ {x}) =

desc(CL), i.e., CL \ {x} ∈ S(C0), so x ∈ T

C′∈S(C0)C′, a contradiction.

  • Any x ∈ C0 = ∩

C′∈S(C0)C′ is a colluder. Otherwise, ∀ C′ ∈ S(C0),

C′ \ {x} ∈ S(C0), so x ∈ T

C′∈S(C0)C′, a contradiction.

10

slide-11
SLIDE 11

It is obvious that the set

CL = B B @ 1 1 1 C C A = ⇒ C0 = B B @ 1 1 1 C C A

  • f remaining codewords necessarily contains C0. We have to find the

exact C0.

  • CL ∈ S(C0), that is, desc(CL) = desc(C0).
  • ∀ x ∈ C0 = ∩

C′∈S(C0)C′, ∃ 1 ≤ j ≤ n s.t. x(j) = 1, c(j) = 0, or

x(j) = 0, c(j) = 1 for any c ∈ CL \ {x}. Otherwise desc(CL \ {x}) =

desc(CL), i.e., CL \ {x} ∈ S(C0), so x ∈ T

C′∈S(C0)C′, a contradiction.

  • Any x ∈ C0 = ∩

C′∈S(C0)C′ is a colluder. Otherwise, ∀ C′ ∈ S(C0),

C′ \ {x} ∈ S(C0), so x ∈ T

C′∈S(C0)C′, a contradiction.

11

slide-12
SLIDE 12

4 Constructions

  • Thm. 4.1 (Concatenation) A t-SSC(n, M, q) implies a t-SSC

(nq, M, 2).

  • Thm. 4.2 A code C is a 2-SSC(2, M, q) iff it is a 2-SC(2, M, q).

Lemma 4.3 (Cheng et. al., 2012, 2015) Let k ≥ 2 be a prime power. Then ∃ optimal 2-SC(2, M ≈ q3/2, q) for any q ∈ {k2 − 1, k2 + k − 2, k2 + k − 1, k2 + k, k2 + k + 1}.

  • Coro. 4.4 Let k ≥ 2 be a prime power. Then ∃ optimal 2-SSC

(2, M ≈ q3/2, q) for any q ∈ {k2 − 1, k2 + k − 2, k2 + k − 1, k2 + k, k2 + k + 1}. Remark: A 2-FPC(2, M, q) can have at most 2q codewords (Blackburn, 2003), but the above 2-SSC(2, M, q) can have about q3/2 codewords.

12

slide-13
SLIDE 13

A Direct Construction Let q be a positive integer, s a non-negative integer, 0 ≤ s ≤ q, q − s

  • dd. Let Q = {∞0, . . . , ∞s−1} ∪ Zq−s.

Let

Mi = B B @ ∞i i ∞i i i ∞ 1 C C A Ms = B B @ · · · 1 · · · q − s − 1 2 · · · 2(q − s − 1) 1 C C A

Define Dj = {c + g | c ∈ Mj, g ∈ Zq−s}, and C = ∪

0≤j≤sDj.

  • Thm. 4.5 C is a 2-SSC(3, q2 + sq − 2s2, q).

13

slide-14
SLIDE 14
  • Coro. 4.6 ∀ q ∈ N, ∃ 2-SSC(3, 1

8(9q2 − w2), q), with m ≡ q

(mod 8), and w =    4 − m, if m ≡ 0 (mod 4), min{m, 8 − m},

  • therwise

Remark: A 2-FPC(3, M, q) can have at most q2 codewords (Bazrafshan-Tran van Trung, 2008), but the above 2-SSC(3, M, q) can have about 9

8q2 codewords. It is even possible to construct

2-SSC(3, M, q) with more codewords.

14

slide-15
SLIDE 15

Problem: What is the largest number of codewords in a t-SSC (n, M, q)?

15

slide-16
SLIDE 16

Any Questions? Thanks for Your Attention!

16