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In the recent literature a new vulnerability of digital signature has been addressed, based on a novel mechanism (denoted Dalì attack) allowing ambiguous presentation of electronic documents. This mechanism operates by a non-trivial inclusion into a single polymorphic file of a pair of different contents, encoded through two different format types. In this paper we overcome the main limitation of the above attack, consisting in the necessity of having html among the two involved formats. Here, exploiting an unusual feature of the pdf standard, we are able to enhance the attack in such a way that the two filetypes, namely pdf and tiff, embedded into the polymorphic file are both extremely safe, allowing the attacker to produce a fake document that appears in a format widely accepted in the context of e-government activities both whenever it is signed and whenever it is fraudulently exploited. This significantly increases both the danger and the plausibility of the Dalì attack.

In everyday life it happens that a person has to reason out what other people think and how they behave, in order to achieve his goals. In other words, an individual may be required to adapt his behavior by reasoning about the others' mental state. In this paper we focus on a knowledge-representation language derived from logic programming which both supports the representation of mental states of individual communities and provides each with the capability of reasoning about others' mental states and acting accordingly. The proposed semantics is shown to be translatable into stable model semantics of logic programs with aggregates.

In the context of Knowledge Discovery in Databases, data reduction is a pre-processing step delivering succinct yet meaningful data to sequent stages. If the target of mining are data streams, then it is crucial to suitably reduce them, since often analyses on such data require multiple scans. In this chapter, we propose a histogram-based approach to reducing sliding windows supporting approximate arbitrary (i.e., non biased) range-sum queries. The histogram is based on a hierarchical structure (as opposed to the flat structure of traditional ones) and it results suitable to directly support hierarchical queries, such as drill-down and roll-up operations. In particular, both sliding window shifting and quick query answering operations are logarithmic in the sliding window size. Experimental analysis shows the superiority of our method in terms of accuracy w.r.t. the state-of-the-art approaches in the context of histogram-based sliding window reduction techniques.

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