Innovative Information Industry Research Center

Shenzhen, China

Innovative Information Industry Research Center

Shenzhen, China

Time filter

Source Type

Lin J.C.-W.,Innovative Information Industry Research Center | Lin J.C.-W.,Harbin Institute of Technology | Gan W.,Innovative Information Industry Research Center | Hong T.-P.,National University of Kaohsiung | Hong T.-P.,National Sun Yat - sen University
Intelligent Data Analysis | Year: 2016

High-utility itemset mining (HUIM) has been recently studied to mine high-utility itemsets (HUIs) from the transactional database by considering more factors such as profit and quantity. Many approaches have been proposed for HUIM from a static database. Fewer studies have been developed to maintain the discovered HUIs in dynamic environment whether transaction insertion or transaction deletion. In the past, the FUP-HUI-DEL and PRE-HUI-DEL algorithms were respectively proposed to effectively maintain the discovered high transaction-weighted utilization itemsets (HTWUIs) and high-utility itemsets (HUIs) when the transactions are consequentially deleted from the original database. The original database is still, however, required to be rescanned when small transaction-weighted utilization itemsets in the original database are necessary to be maintained. In this paper, an efficient algorithm namely HUI-list-DEL is presented to discover HUIs by maintaining the built utility-list structure for transaction deletion in dynamic databases. Based on the designed algorithm, the HUIs can be directly produced without candidate generation or the numerous database scans. Two pruning strategies are also designed to speed up the maintenance approach of HUIs. Substantial experiments show that the proposed maintenance approach for transaction deletion significantly outperforms the previous approaches in terms of execution time, memory consumption and scalability. © 2016 - IOS Press and the authors. All rights reserved.


Lin C.-W.,Innovative Information Industry Research Center | Lin C.-W.,Harbin Institute of Technology | Gan W.,Innovative Information Industry Research Center | Hong T.-P.,National University of Kaohsiung | And 3 more authors.
Communications in Computer and Information Science | Year: 2014

Among various data mining techniques, sequential-pattern mining is used to discover the frequent subsequences from a sequence database. Most research handles the static database in batch mode to discover the desired sequential patterns. Transactions or customer sequences are, however, dynamically changed in real-world applications. In the past, the FUSP tree was designed to maintain and update the discovered information based on Fast UPdated (FUP) approach with sequence insertion and sequence deletion. The original customer sequences is still required to be rescanned if it is necessary. In this paper, the prelarge concept is adopted to maintain and update the built FUSP tree with sequence deletion. When the number of deleted customers is smaller than the safety bound of the prelarge concept, the original database is unnecessary to be rescanned but the sequential patterns can still be actually maintained and updated. Experiments are also conducted to show the performance of the proposed algorithm in terms of execution time and number of tree nodes. © Springer-Verlag Berlin Heidelberg 2014.


Li C.-R.,Fujian Normal University | Lin C.-W.,Innovative Information Industry Research Center | Lin C.-W.,Harbin Institute of Technology | Gan W.,Innovative Information Industry Research Center | And 2 more authors.
Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science) | Year: 2014

In the past, we proposed a pre-large FUSP tree to preserve and maintain both large and pre-large sequences in the built tree structure. In this paper, the pre-large concept is also adopted for maintaining and updating the FUSP tree. Only large sequences are kept in the built tree structure for reducing computations. The PreFUSP-TREE-MOD maintenance algorithm is proposed to reduce the rescans of the original database due to the pruning properties of pre-large concept. When the number of modified sequences is smaller than the safety bound of the pre-large concept, better results can be obtained by the proposed PreFUSP-TREE-MOD maintenance algorithm for sequence modification in the dynamic database. © Springer International Publishing Switzerland 2014.


Lin C.-W.,Innovative Information Industry Research Center | Lin C.-W.,Harbin Institute of Technology | Wu T.-Y.,Innovative Information Industry Research Center | Wu T.-Y.,Harbin Institute of Technology | And 3 more authors.
Proceedings - International Conference on Machine Learning and Cybernetics | Year: 2015

Fuzzy set theory was adopted to induce natural and understandable linguistic rules from the transactions with quantitative values. In the past, many algorithms were proposed to mine the desired fuzzy association rules from a static database. In real-world applications, transactions may, however, be inserted into or deleted from an original database. The discovered information is required to be re-mined in batch mode. In this paper, a maintenance algorithm for efficiently updating the discovered multiple fuzzy frequent itemsets is thus proposed. Based on the FUP2 concepts for transaction deletion, the proposed maintenance algorithm has better performance compared to the Apriori-based algorithm. © 2014 IEEE.


Lin C.-W.,Innovative Information Industry Research Center | Lin C.-W.,Harbin Institute of Technology | Gan W.,Innovative Information Industry Research Center | Hong T.-P.,National University of Kaohsiung | And 3 more authors.
Proceedings - International Conference on Machine Learning and Cybernetics | Year: 2015

Utility mining is used to measure the utility values of the purchased items from transactional database. It usually considers not only the occurrence frequencies of items but also the factors of profit, cost and quantity. In the past, many algorithms were proposed to mine high-utility itemsets from a static database. In real-world applications, transactions are usually inserted, deleted or modified in dynamic databases. In this paper, we propose a maintenance algorithm to handle transaction modification for efficiently updating the discovered high-utility itemsets. Experiments are conducted to show that the proposed approach has better performance than the two-phase algorithm in batch mode. © 2014 IEEE.


Lin C.-W.,Innovative Information Industry Research Center | Lin C.-W.,Harbin Institute of Technology | Hong T.-P.,National University of Kaohsiung | Hong T.-P.,National Sun Yat - sen University | And 2 more authors.
Proceedings - 2013 IEEE International Conference on Granular Computing, GrC 2013 | Year: 2013

In this paper, a GA-based privacy-preserving utility mining method is proposed to delete appropriate transactions for hiding sensitive high utility itemsets from a database. The downward closure property and the pre-large concepts are adopted in the proposed algorithm to reduce the cost of rescanning databases. Experiments are also conducted to evaluate the performance of the proposed approach in execution time and the amount of side-effects. © 2013 IEEE.


Lin J.C.-W.,Innovative Information Industry Research Center | Pan J.-S.,Innovative Information Industry Research Center | Gan W.,Innovative Information Industry Research Center | Lin J.C.-W.,Harbin Institute of Technology | And 3 more authors.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2014

High-utility itemsets mining (HUIM) is designed to solve the limitations of association-rule mining by considering both the quantity and profit measures. Most algorithms of HUIM are designed to handle the static database. Fewer research handles the dynamic HUIM with transaction insertion, thus requiring the computations of database rescan and combination explosion of pattern-growth mechanism. In this paper, an efficient incremental algorithm with transaction insertion is designed to reduce computations without candidate generation based on the utility-list structures. The enumeration tree and the relationships between 2-itemsets are also adopted in the proposed algorithm to speed up computations. Several experiments are conducted to show the performance of the proposed algorithm in terms of runtime, and memory consumption. © Springer International Publishing Switzerland 2014.


Chen C.-M.,Innovative Information Industry Research Center | Chen Y.-H.,Industrial Technology Research Institute of Taiwan | Lin Y.-H.,Carnegie Mellon University | Sun H.-M.,National Tsing Hua University
Expert Systems with Applications | Year: 2014

Recently, femtocell solutions have been attracting increasing attention since coverage for broadband radios can effectively eliminate wireless notspots. To restrict malicious subscribers from accessing femtocells, 3G/WiMAX standards introduce an access control strategy, called Closed Subscriber Group (CSG). However, CSG only prevents malicious clients, but not rouge femtocells. In 2009, Han et al. proposed the first mutual authentication mechanism. This mechanism does not consider the case that an attacker can locate femtocells in an unregistered area even these femtocells are legitimate. In this paper, we first define two attacks, sinkhole and wormhole attacks, in femtocell-enabled mobile networks. Then, we design two approaches based on distance bounding protocols and geographic information to defend against these two attacks. In our design, a subscriber can confirm whether or not the femtocell he connected with is physically-present. Experiment results demonstrate that the distance bounding protocol can estimate an approximate distance between a subscriber's device and the deployed femtocell. Moreover, femtocells that are deployed inside or outside can both be identified and distinguished without the bias of signal strength based on our design. © 2012 Elsevier B.V. All rights reserved.


He B.-Z.,National Tsing Hua University | Chen C.-M.,Innovative Information Industry Research Center | Su Y.-P.,National Tsing Hua University | Sun H.-M.,National Tsing Hua University
Expert Systems with Applications | Year: 2014

Recently, on-line social networking sites become more and more popular. People like to share their personal information such as their name, birthday and photos on these public sites. However, personal information could be misused by attackers. One kind of attacks called Identity Theft Attack is addressed in on-line social networking sites. After collecting the personal information of a victim, the attacker can create a fake identity to impersonate this victim and cheat the victim's friends in order to destroy the trust relationships on the on-line social networking sites. In this paper, we propose a scheme to protect users from Identity Theft Attacks. In our work, users' personal information can be still kept public. It means that this scheme does not violate the nature of the social networks. Compared with previous works, the proposed scheme incurs less overhead for users. Experimental results also demonstrate the practicality of the proposed scheme. © 2013 Elsevier Ltd. All rights reserved.

Loading Innovative Information Industry Research Center collaborators
Loading Innovative Information Industry Research Center collaborators