By Takashi Watanabe, Hiroto Nagayoshi, Hiroshi Sako (auth.), Kaushal Solanki, Kenneth Sullivan, Upamanyu Madhow (eds.)
This booklet constitutes the completely refereed post-workshop complaints of the tenth overseas Workshop on info Hiding, IH 2008, held in Santa Barbara, CA, united states, in may perhaps 2008.
The 25 revised complete papers awarded have been conscientiously reviewed and chosen from sixty four submissions. The papers are prepared in topical sections on anonymity and privateness, steganography, forensics, novel applied sciences and functions, watermarking, steganalysis, different hiding domain names, community safeguard, and fingerprinting.
Read Online or Download Information Hiding: 10th International Workshop, IH 2008, Santa Barbara, CA, USA, May 19-21, 2008, Revised Selected Papers PDF
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Extra resources for Information Hiding: 10th International Workshop, IH 2008, Santa Barbara, CA, USA, May 19-21, 2008, Revised Selected Papers
We will now summarise the batch steganography problem and point out some ambiguities in its statement; there follows a brief discussion of the appropriate interpretation of Kerckhoﬀs’ Principle in steganography. In Sect. 2 we pose the perturbation hiding problem, discuss its connection with batch steganography, and solve the problem for a class of cover families: it is best to spread payload equally between the cover objects, even though this denies the opportunity to keep the enemy guessing as to payload distribution.
29089 ... Table 3. 2-anonymized table Name Age Gender Home postal Occupation Company postal 3* 3* 4* 4* 2* 2* F F F F M M 48*** 48*** 1**** 1**** 61306 61306 Outdoor Outdoor Indoor Indoor Indoor Indoor 54832 54832 118** 118** 290** 290** Illness Anxiety Anxiety Sleeplessness Sleeplessness fever fever deﬁned the meaning of what being “well-represented” values, and a natural choice is by requiring the entropy of the attribute values is above certain threshold, say log2 . If the sensitive values are well represented, then we can have an upper bound on the chances that the adversary can successfully guess the correct value.
In: IEEE Transactions on Knowledge and Data Engineering, pp. 1010–1027 (2001) 44 C. -C. Chang 16. : Protecting privacy when disclosing information: kanonymity and its enforcement through generalization and suppression. Technical report, CMU, SRI (1998) 17. : Achieving k-anonymity privacy protection using generalization and suppression. International Journal of Uncertainty, Fuzziness and Knowledge-Based System, 571–588 (2002) 18. : k-anonymity: a model for protecting privacy. International Journal of Uncertainty, Fuzziness and Knowledge-Based System, 557–570 (2002) 19.
Information Hiding: 10th International Workshop, IH 2008, Santa Barbara, CA, USA, May 19-21, 2008, Revised Selected Papers by Takashi Watanabe, Hiroto Nagayoshi, Hiroshi Sako (auth.), Kaushal Solanki, Kenneth Sullivan, Upamanyu Madhow (eds.)