Computer Engineering / Bilgisayar Mühendisliği
Permanent URI for this collectionhttps://hdl.handle.net/11147/10
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Article Citation - WoS: 1Citation - Scopus: 2Dynamic Itemset Hiding Algorithm for Multiple Sensitive Support Thresholds(IGI Global, 2018) Öztürk, Ahmet Cumhur; Ergenç, BelginThis article describes how association rule mining is used for extracting relations between items in transactional databases and is beneficial for decision-making. However, association rule mining can pose a threat to the privacy of the knowledge when the data is shared without hiding the confidential association rules of the data owner. One of the ways hiding an association rule from the database is to conceal the itemsets (co-occurring items) from which the sensitive association rules are generated. These sensitive itemsets are sanitized by the itemset hiding processes. Most of the existing solutions consider single support thresholds and assume that the databases are static, which is not true in real life. In this article, the authors propose a novel itemset hiding algorithm designed for the dynamic database environment and consider multiple itemset support thresholds. Performance comparisons of the algorithm is done with two dynamic algorithms on six different databases. Findings show that their dynamic algorithm is more efficient in terms of execution time and information loss and guarantees to hide all sensitive itemsets.Article Citation - WoS: 1Citation - Scopus: 1Extended Adaptive Join Operator With Bind-Bloom Join for Federated Sparql Queries(IGI Global Publishing, 2017) Oğuz, Damla; Yin, Shaoyi; Ergenç, Belgin; Hameurlain, Abdelkader; Dikenelli, OğuzThe goal of query optimization in query federation over linked data is to minimize the response time and the completion time. Communication time has the highest impact on them both. Static query optimization can end up with inefficient execution plans due to unpredictable data arrival rates and missing statistics. This study is an extension of adaptive join operator which always begins with symmetric hash join to minimize the response time, and can change the join method to bind join to minimize the completion time. The authors extend adaptive join operator with bind-bloom join to further reduce the communication time and, consequently, to minimize the completion time. They compare the new operator with symmetric hash join, bind join, bind-bloom join, and adaptive join operator with respect to the response time and the completion time. Performance evaluation shows that the extended operator provides optimal response time and further reduces the completion time. Moreover, it has the adaptation ability to different data arrival rates.Article Citation - WoS: 3Citation - Scopus: 4Full-Exact Approach for Frequent Itemset Hiding(IGI Global Publishing, 2015) Ayav, Tolga; Ergenç, BelginThis paper proposes a novel, exact approach that relies on integer programming for association rule hiding. A large panorama of solutions exists for the complex problem of itemset hiding: from practical heuristic approaches to more accurate exact approaches. Exact approaches provide better solutions while suffering from the lack of performance and existing exact approaches still augment their methods with heuristics to make the problem solvable. In this case, the solution may not be optimum. This work present a full-exact method, without any need for heuristics. Extensive tests are conducted on 10 real datasets to analyze distance and information loss performances of the algorithm in comparison to a former similar algorithm. Since the approach provides the optimum solution to the problem, it should be considered as a reference method.