In this work a new algorithm for encryption image is introduced. This algorithm makes it possible to cipher and decipher images by guaranteeing a maximum security. The algorithm introduced is based on stream cipher with nonlinear filtering function. The Boolean function used in this algorithm is resilient function satisfying all the cryptographic criteria necessary carrying out the best possibl...

We find linear (as well as quadratic) relations in a very large class of T-functions. The relations may be used in analysis of T-function-based stream ciphers.

Given a stream of data, a typical approach in streaming algorithms is to design a sophisticated algorithm with small memory that computes a specific statistic over the streaming data. Usually, if one wants to compute a different statistic after the stream is gone, it is impossible. But what if we want to compute a different statistic after the fact? In this paper, we consider the following fasc...

Data streaming applications are becoming more and more common due to the rapid development in the areas such as sensor networks, multimedia streaming, and on-line data mining, etc. These applications are often running in a decentralized, distributed environment. The requirements for processing large volumes of streaming data at real time have posed many great design challenges. It is critical t...

Preliminary algebraic analysis of the ZUC cipher indicates that the cipher may be vulnerable to algebraic attack. In this paper we present an alternative algebraic analysis method for the ZUC stream cipher, using a combiner to represent the nonlinear function. This approach can recover the initial state of ZUC from an observed 2 words of keystream, with a complexity of 2 operations. This method...

Continuous queries applied over nonterminating data streams usually specify windows in order to obtain an evolving –yet restricted– set of tuples and thus provide timely and incremental results. Although sliding windows get frequently employed in many user requests, additional types like partitioned or landmark windows are also available in stream processing engines. In this paper, we set out t...

Continuously monitoring large-scale aggregates over data streams is important for many stream processing applications, e.g. collaborative intelligence analysis, and presents new challenges to data management systems. The first challenge is to efficiently generate the updated aggregate values and provide the new results to users after new tuples arrive. We implemented an incremental aggregation ...