Attackers can thoroughly figure out an original password from hash value when that is relatively simple and plain. However, those can be exposed to cyber-attacks utilizing password by cracking tool or hash-cracking online sites. These hash-based password schemes are comparatively simple and fast because those are based on text and famed cryptography. Call Now 9972364704 Download AbstractĪbstract: Traditional password conversion scheme for user authentication is to transform the passwords into hash values. Second, two algorithms (space pruning AprioriMR and top AprioriMR) that prune the search space by means of the well-known anti-monotone property are proposed. First, two algorithms with no pruning strategy are proposed, which extract any existing itemset in data. The proposed algorithms can be divided into three main groups. To this aim, a series of algorithms based on the MapReduce framework and the Hadoop open-source implementation have been proposed. The goal of this paper is to propose new efficient pattern mining algorithms to work in big data. Although many efficient algorithms have been developed in this regard, the growing interest in data has caused the performance of existing pattern mining techniques to be dropped. This task aims to extract item-sets that represent any type of homogeneity and regularity in data. Abstract: Pattern mining is one of the most important tasks to extract meaningful and useful information from raw data.
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