Tamper Detection and Localization for Categorical Data Using Fragile Watermarks

What is Digital watermarking? A digital watermark is technique of embedding an invisible signal directly into the data, thus providing a promising way to protect digital data from illicit copying and manipulation. A digital watermark is technique of embedding an invisible signal directly into the data, thus providing a promising way to protect digital data from illicit copying and manipulation.

Why is it required? It is used to detect data tampering and illicit copying of data. It is used to detect data tampering and illicit copying of data. It complements cryptography and steganography. It complements cryptography and steganography. Cryptography- once the encrypted data is decrypted, the data is clear and no longer under protection. Cryptography- once the encrypted data is decrypted, the data is clear and no longer under protection. Steganography :The problem is that it cannot extract the hidden data if the stego data undergo some distortions. Steganography :The problem is that it cannot extract the hidden data if the stego data undergo some distortions.

Applications Copy protection Copy protection Authentication Authentication Tamper detection Tamper detection

Classifications of Digital Watermarks Fragile watermarks for tamper detection Fragile watermarks for tamper detection Robust watermarks for ownership verification Robust watermarks for ownership verification

Difference between multimedia and Database Watermarking Multimedia data are highly correlated, there is a lot of redundant information present in multimedia data. Multimedia data are highly correlated, there is a lot of redundant information present in multimedia data. Database relations contain large number of independent tuples and all tuples are equally important. Database relations contain large number of independent tuples and all tuples are equally important.

Challenges Embedding watermarks in database relations is a challenging problem because there is little redundancy present in a database relation. Embedding watermarks in database relations is a challenging problem because there is little redundancy present in a database relation.

Watermark Embedding Algorithm Algorithm 1 Watermark embedding 1: For all k ∈ [1, g] qk = 0 2: for i = 1 to ω do 3: hi = HASH(K, ri.A1, ri.A2, · · ·, ri.Aγ) // row hash 4: hpi = HASH(K, ri.P ) // primary key hash 5: k = hpi mod g 6: ri → Gk 7: qk ++ 8: end for 9: for k = 1 to g do 10: watermark embedding in Gk // See Algorithm 2 11: end for

Watermark Embedding Algorithm(cont…) Algorithm 2 Watermark embedding in Gk sort tuples in Gk in ascendant order according to their primary key hash // Virtual operation H = HASH(K, h1, h2, · · ·, hqk) W = extractBits(H, qk/2) // See line for i = 1, i < qk, i = i + 2 do if (W[i/2] == 1 and hi hi+1) then switch the position of ri and ri end if end for extractBits(H, l) { 10: if length(H) ≥ l then W = concatenation of first l selected bits from H else m = l - length(H) W = concatenation of H and extractBits(H,m) end if return W }

Example Figure 1: A table before and after watermark embedding WM={0,1}

Watermark Detection Algorithm 3 Watermark detection 1: For all k ∈ [1, g] qk = 0 2: for i = 1 to ω do 3: hi = HASH(K, ri.A1, ri.A2, · · ·, ri.Aγ) // tuple hash 4: hp i = HASH(K, ri.P ) // primary key hash 5: k = hp i mod g 6: ri → Gk 7: qk ++ 8: end for 9: for k = 1 to g do 10: watermark verification in Gk // See Algorithm 4 11: end for

Watermark Detection Algorithm 4 Watermark verification in Gk 1: sort tuples in Gk in ascendant order according to their primary key hash // Virtual operation 2: H = HASH(K, h1, h2, · · ·, hqk) // hi(i = 1, · · · qk) is the tuple hash of ith tuple after ordering 3: W = extractBits(H, qk/2) //See line 9-16 in Algorithm 2 4: for i = 1, i < qk, i = i + 2 do 5: if hi ≤ hi+1 then 6: W[i/2] = 0 7: else 8: W[i/2] = 1 9: end if 10: end for 11: ifW == W then 12: V = TRUE 13: else 14: V = FALSE 15: end if