We study the space complexity of querying regular languages over data streams in the sliding window model. The algorithm has to answer at any point of time whether the content of the sliding window belongs to a fixed regular language. A trichotomy is shown: For every regular language the optimal space requirement is either in Θ(n), Θ(logn), or constant, where n is the size of the sliding window...

Blockchain technology is a core, underlying technology with promising application prospects in the banking industry. On one hand, the banking industry in China is facing the impact of interest rate liberalization and profit decline caused by the narrowing interest-rate spread. On the other hand, it is also affected by economic transformation, Internet development, and financial innovations. Hen...

This paper introduces a novel Management Traffic Clustering Algorithm (MTCA) based on a sliding window methodology for intrusion detection in 802.11 networks Active attacks and other network events such as scanning, joining and leaving in 802.11 WLANs can be observed by clustering the management frames in the MAC Layer. The new algorithm is based on a sliding window and measures the similarity ...

We use random linear network coding (RLNC) based scheme for multipath communication in the presence of lossy links with different delay characteristics to obtain ultra-reliability and low latency. A sliding window version of RLNC is proposed where the coded packets are generated using packets in a window size and are inserted among systematic packets in different paths. The packets are schedule...

Sliding super point is a special host de€ned under sliding time window with which there are huge other hosts contact. It plays important roles in network security and management. But how to detect them in real time from nowadays high-speed network which contains several distributed routers is a hard task. Distributed sliding super point detection requires an algorithm that can estimate the numb...

We propose online prediction algorithms for data streams whose characteristics might change over time. Our algorithms are applications of online learning with experts. In particular, our algorithms combine base predictors over sliding windows with different length as experts. As a result, our algorithms are guaranteed to be competitive with the base predictor with the best fixed-length sliding ...

With advanced information and communication technology, the organizations’ business model has undergone fundamental changes. These changes are also observed in the banking industry. This research aims at explaining the Iranian electronic banking business model and recognizing its challenges in the transformation to digital banking, which is considered as the research innovation. In terms of met...