866 resultados para Information Security, Safe Behavior, Users’ behavior, Brazilian users, threats


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Dragon is a word-based stream cipher. It was submitted to the eSTREAM project in 2005 and has advanced to Phase 3 of the software profile. This paper discusses the Dragon cipher from three perspectives: design, security analysis and implementation. The design of the cipher incorporates a single word-based non-linear feedback shift register and a non-linear filter function with memory. This state is initialized with 128- or 256-bit key-IV pairs. Each clock of the stream cipher produces 64 bits of keystream, using simple operations on 32-bit words. This provides the cipher with a high degree of efficiency in a wide variety of environments, making it highly competitive relative to other symmetric ciphers. The components of Dragon were designed to resist all known attacks. Although the design has been open to public scrutiny for several years, the only published attacks to date are distinguishing attacks which require keystream lengths greatly exceeding the stated 264 bit maximum permitted keystream length for a single key-IV pair.

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Integral attacks are well-known to be effective against byte-based block ciphers. In this document, we outline how to launch integral attacks against bit-based block ciphers. This new type of integral attack traces the propagation of the plaintext structure at bit-level by incorporating bit-pattern based notations. The new notation gives the attacker more details about the properties of a structure of cipher blocks. The main difference from ordinary integral attacks is that we look at the pattern the bits in a specific position in the cipher block has through the structure. The bit-pattern based integral attack is applied to Noekeon, Serpent and present reduced up to 5, 6 and 7 rounds, respectively. This includes the first attacks on Noekeon and present using integral cryptanalysis. All attacks manage to recover the full subkey of the final round.

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Semi-automatic segmentation of still images has vast and varied practical applications. Recently, an approach "GrabCut" has managed to successfully build upon earlier approaches based on colour and gradient information in order to address the problem of efficient extraction of a foreground object in a complex environment. In this paper, we extend the GrabCut algorithm further by applying an unsupervised algorithm for modelling the Gaussian Mixtures that are used to define the foreground and background in the segmentation algorithm. We show examples where the optimisation of the GrabCut framework leads to further improvements in performance.

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Many jurisdictions have developed mature infrastructures, both administratively and legislatively, to promote competition. Substantial funds have been expended to monitor activities that are anticompetitive and many jurisdictions also have adopted a form of "Cartel Leniency Program", first developed by the US Federal Trade Commission, to assist in cartel detection. Further, some jurisdictions are now criminalizing cartel behaviour so that cartel participants can be held criminally liable with substantial custodial penalties imposed. Notwithstanding these multijurisdictional approaches, a new form of possibly anticompetitive behaviour is looming. Synergistic monopolies („synopolies‟) involve not competitors within a horizontal market but complimentors within separate vertical markets. Where two complimentary corporations are monopolists in their own market they can, through various technologies, assist each other to expand their respective monopolies thus creating a barrier to new entrants and/or blocking existing participants from further participation in that market. The nature of the technologies involved means that it is easy for this potentially anti-competitive activity to enter and affect the global marketplace. Competition regulators need to be aware of this potential for abuse and ensure that their respective competition frameworks appropriately address this activity. This paper discusses how new technologies can be used to create a synopoly.