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Journal articles on the topic 'SENSITIVE RULES'

Author: Grafiati

Published: 11 September 2023

Last updated: 16 April 2024

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1

Wang, Hui. "Hiding Sensitive Association Rules by Sanitizing." Advanced Materials Research 694-697 (May 2013): 2317–21. http://dx.doi.org/10.4028/www.scientific.net/amr.694-697.2317.

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The goal of knowledge discovery is to extract hidden or useful unknown knowledge from databases, while the objective of knowledge hiding is to prevent certain confidential data or knowledge from being extracted through data mining techniques. Hiding sensitive association rules is focused. The side-effects of the existing data mining technology are investigated. The problem of sensitive association rule hiding is described formally. The representative sanitizing strategies for sensitive association rule hiding are discussed.

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Bansal, Meenakshi, Dinesh Grover, and Dhiraj Sharma. "Sensitivity Association Rule Mining using Weight based Fuzzy Logic." Global Journal of Enterprise Information System 9, no. 2 (June 28, 2017): 1. http://dx.doi.org/10.18311/gjeis/2017/15480.

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Mining of sensitive rules is the most important task in data mining. Most of the existing techniques worked on finding sensitive rules based upon the crisp thresh hold value of support and confidence which cause serious side effects to the original database. To avoid these crisp boundaries this paper aims to use WFPPM (Weighted Fuzzy Privacy Preserving Mining) to extract sensitive association rules. WFPPM completely find the sensitive rules by calculating the weights of the rules. At first, we apply FP-Growth to mine association rules from the database. Next, we implement fuzzy to find the sensitive rules among the extracted rules. Experimental results show that the proposed scheme find actual sensitive rules without any modification along with maintaining the quality of the released data as compared to the previous techniques.

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3

Wang, Hui. "Hiding Sensitive Association Rules by Adjusting Support." Advanced Materials Research 756-759 (September 2013): 1875–78. http://dx.doi.org/10.4028/www.scientific.net/amr.756-759.1875.

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Data mining technologies are successfully applied in lots of domains such as business, science research, health care, bioinformatics, financial forecasting and so on and so forth. Knowledge can be discovered by data mining and can help people to make better decisions and benefits. Association rule is one kind of the most popular knowledge discovered by data mining. While at the same time, some association rules extracted from data mining can be considered so sensitive for data holders that they will not like to share and really want to hide. Such kind of side effects of data mining is analyzed by privacy preserving technologies. In this work, we have proposed strategies by adjusting supports and quality measurements of sensitive association rules hiding.

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Rao, K. Srinivasa, CH Suresh Babu, A. Damodaram, and Tai-hoon Kim. "Distortion Technique for Hiding Sensitive Association Rules." International Journal of Multimedia and Ubiquitous Engineering 9, no. 10 (October 31, 2014): 57–66. http://dx.doi.org/10.14257/ijmue.2014.9.10.06.

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5

Whittle, P. "Entropy-minimising and risk-sensitive control rules." Systems & Control Letters 13, no. 1 (July 1989): 1–7. http://dx.doi.org/10.1016/0167-6911(89)90014-5.

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Jain, Dhyanendra. "Hiding Sensitive Association Rules Without Altering the Support of Sensitive Item(S)." International Journal of Artificial Intelligence & Applications 3, no. 2 (March 31, 2012): 75–84. http://dx.doi.org/10.5121/ijaia.2012.3207.

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7

Wang, Hui. "Strategies for Sensitive Association Rule Hiding." Applied Mechanics and Materials 336-338 (July 2013): 2203–6. http://dx.doi.org/10.4028/www.scientific.net/amm.336-338.2203.

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Data mining technologies are used widely while the side effects it incurred are concerned so seriously. Privacy preserving data mining is so important for data and knowledge security during data mining applications. Association rule extracted from data mining is one kind of the most popular knowledge. It is challenging to hide sensitive association rules extracted by data mining process and make less affection on non-sensitive rules and the original database. In this work, we focus on specific association rule automatic hiding. Novel strategies are proposed which are based on increasing the support of the left hand and decreasing the support of the right hand. Quality measurements for sensitive association rules hiding are presented.

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Gayathiri, P., and B. Poorna. "Effective Gene Patterned Association Rule Hiding Algorithm for Privacy Preserving Data Mining on Transactional Database." Cybernetics and Information Technologies 17, no. 3 (September 1, 2017): 92–108. http://dx.doi.org/10.1515/cait-2017-0032.

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Abstract Association Rule Hiding methodology is a privacy preserving data mining technique that sanitizes the original database by hide sensitive association rules generated from the transactional database. The side effect of association rules hiding technique is to hide certain rules that are not sensitive, failing to hide certain sensitive rules and generating false rules in the resulted database. This affects the privacy of the data and the utility of data mining results. In this paper, a method called Gene Patterned Association Rule Hiding (GPARH) is proposed for preserving privacy of the data and maintaining the data utility, based on data perturbation technique. Using gene selection operation, privacy linked hidden and exposed data items are mapped to the vector data items, thereby obtaining gene based data item. The performance of proposed GPARH is evaluated in terms of metrics such as number of sensitive rules generated, true positive privacy rate and execution time for selecting the sensitive rules by using Abalone and Taxi Service Trajectory datasets.

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9

Menon, Syam, Abhijeet Ghoshal, and Sumit Sarkar. "Modifying Transactional Databases to Hide Sensitive Association Rules." Information Systems Research 33, no. 1 (March 2022): 152–78. http://dx.doi.org/10.1287/isre.2021.1033.

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Although firms recognize the value in sharing data with supply chain partners, many remain reluctant to share for fear of sensitive information potentially making its way to competitors. Approaches that can help hide sensitive information could alleviate such concerns and increase the number of firms that are willing to share. Sensitive information in transactional databases often manifests itself in the form of association rules. The sensitive association rules can be concealed by altering transactions so that they remain hidden when the data are mined by the partner. The problem of hiding these rules in the data are computationally difficult (NP-hard), and extant approaches are all heuristic in nature. To our knowledge, this is the first paper that introduces the problem as a nonlinear integer formulation to hide the sensitive association rule while minimizing the alterations needed in the data set. We apply transformations that linearize the constraints and derive various results that help reduce the size of the problem to be solved. Our results show that although the nonlinear integer formulations are not practical, the linearizations and problem-reduction steps make a significant impact on solvability and solution time. This approach mitigates potential risks associated with sharing and should increase data sharing among supply chain partners.

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10

Wu, Yi-hung, Chia-ming Chiang, and Arbee Chen. "Hiding Sensitive Association Rules with Limited Side Effects." IEEE Transactions on Knowledge and Data Engineering 19, no. 1 (January 2007): 29–42. http://dx.doi.org/10.1109/tkde.2007.250583.

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11

Dehkordi, Mohammad Naderi, Kambiz Badie, and Ahmad Khadem Zadeh. "A new approach for sensitive association rules hiding." International Journal of Rapid Manufacturing 1, no. 2 (2009): 128. http://dx.doi.org/10.1504/ijrapidm.2009.029379.

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12

Schmid-Hempel, Paul, and Regula Schmid-Hempel. "Nectar-collecting bees use Distance-sensitive movement rules." Animal Behaviour 34, no. 2 (April 1986): 605–7. http://dx.doi.org/10.1016/s0003-3472(86)80131-2.

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13

Bonam, Janakiramaiah, and Ramamohan Reddy. "Balanced Approach for Hiding Sensitive Association Rules in Data Sharing Environment." International Journal of Information Security and Privacy 8, no. 3 (July 2014): 39–62. http://dx.doi.org/10.4018/ijisp.2014070103.

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Privacy preserving association rule mining protects the sensitive association rules specified by the owner of the data by sanitizing the original database so that the sensitive rules are hidden. In this paper, the authors study a problem of hiding sensitive association rules by carefully modifying the transactions in the database. The algorithm BHPSP calculates the impact factor of items in the sensitive association rules. Then it selects a rule which contains an item with minimum impact factor. The algorithm alters the transactions of the database to hide the sensitive association rule by reducing the loss of other non-sensitive association rules. The quality of a database can be well maintained by greedily selecting the alterations in the database with negligible side effects. The BHPSP algorithm is experimentally compared with a HCSRIL algorithm with respect to the performance measures misses cost and difference between original and sanitized databases. Experimental results are also mentioned demonstrating the effectiveness of the proposed approach.

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Mohan, S. Vijayarani, and Tamilarasi Angamuthu. "Association Rule Hiding in Privacy Preserving Data Mining." International Journal of Information Security and Privacy 12, no. 3 (July 2018): 141–63. http://dx.doi.org/10.4018/ijisp.2018070108.

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This article describes how privacy preserving data mining has become one of the most important and interesting research directions in data mining. With the help of data mining techniques, people can extract hidden information and discover patterns and relationships between the data items. In most of the situations, the extracted knowledge contains sensitive information about individuals and organizations. Moreover, this sensitive information can be misused for various purposes which violate the individual's privacy. Association rules frequently predetermine significant target marketing information about a business. Significant association rules provide knowledge to the data miner as they effectively summarize the data, while uncovering any hidden relations among items that hold in the data. Association rule hiding techniques are used for protecting the knowledge extracted by the sensitive association rules during the process of association rule mining. Association rule hiding refers to the process of modifying the original database in such a way that certain sensitive association rules disappear without seriously affecting the data and the non-sensitive rules. In this article, two new hiding techniques are proposed namely hiding technique based on genetic algorithm (HGA) and dummy items creation (DIC) technique. Hiding technique based on genetic algorithm is used for hiding sensitive association rules and the dummy items creation technique hides the sensitive rules as well as it creates dummy items for the modified sensitive items. Experimental results show the performance of the proposed techniques.

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15

Boddez, Yannick, Marc Patrick Bennett, Silke van Esch, and Tom Beckers. "Bending rules: the shape of the perceptual generalisation gradient is sensitive to inference rules." Cognition and Emotion 31, no. 7 (September 28, 2016): 1444–52. http://dx.doi.org/10.1080/02699931.2016.1230541.

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16

Khuda Bux, Naadiya, Mingming Lu, Jianxin Wang, Saajid Hussain, and Yazan Aljeroudi. "Efficient Association Rules Hiding Using Genetic Algorithms." Symmetry 10, no. 11 (November 2, 2018): 576. http://dx.doi.org/10.3390/sym10110576.

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In today’s world, millions of transactions are connected to online businesses, and the main challenging task is ensuring the privacy of sensitive information. Sensitive association rules hiding (SARH) is an important goal of privacy protection algorithms. Various approaches and algorithms have been developed for sensitive association rules hiding, differentiated according to their hiding performance through utility preservation, prevention of ghost rules, and computational complexity. A meta-heuristic algorithm is a good candidate to solve the problem of SARH due to its selective and parallel search behavior, avoiding local minima capability. This paper proposes simple genetic encoding for SARH. The proposed algorithm formulates an objective function that estimates the effect on nonsensitive rules and offers recursive computation to reduce them. Three benchmark datasets were used for evaluation. The results show an improvement of 81% in execution time, 23% in utility, and 5% in accuracy.

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17

Zwicky, Arnold M., Ellen M. Kaisse, and Michael Kenstowicz. "The phonology and syntax of wh-expressions in Tangale." Phonology Yearbook 4, no. 1 (May 1987): 229–41. http://dx.doi.org/10.1017/s0952675700000841.

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Study of the phonology-syntax interface has typically proceeded by asking the following question: what aspects of syntactic structure are relevant for the application of phonological rules? Several years’ study of the question by a number of persons (e.g. Kaisse 1985; Selkirk 1984) suggests that phonological rules may be sensitive, either directly or indirectly, to the surface-syntactic constituent structure – typically through extension of the notion of government or c-command. Phrasal phonological rules do not appear to be sensitive to differences in grammatical relations (e.g. subject vs. object) unless these are encoded as different surface constituent structures. Nor do phrasal phonological rules (as opposed to lexical rules) appear to be sensitive to different syntactic features such as [±noun] or [±wh].

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18

Iqbal, Khalid, Dr Sohail Asghar, and Dr Abdulrehman Mirza. "Hiding Sensitive XML Association Rules With Supervised Learning Technique." Intelligent Information Management 03, no. 06 (2011): 219–29. http://dx.doi.org/10.4236/iim.2011.36027.

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19

Clymer, John R., David J. Cheng, and Daniel Hernandez. "Induction of decision making rules for context sensitive systems." SIMULATION 59, no. 3 (September 1992): 198–206. http://dx.doi.org/10.1177/003754979205900308.

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20

Barca, Laura, Andrew W. Ellis, and Cristina Burani. "Context-sensitive rules and word naming in Italian children." Reading and Writing 20, no. 5 (November 28, 2006): 495–509. http://dx.doi.org/10.1007/s11145-006-9040-z.

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21

Talebi, Behnam, and Mohammad Naderi Dehkordi. "Sensitive association rules hiding using electromagnetic field optimization algorithm." Expert Systems with Applications 114 (December 2018): 155–72. http://dx.doi.org/10.1016/j.eswa.2018.07.031.

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22

Krishnamoorthy, Sathiyapriya, G. Sudha Sadasivam, M. Rajalakshmi, K. Kowsalyaa, and M. Dhivya. "Privacy Preserving Fuzzy Association Rule Mining in Data Clusters Using Particle Swarm Optimization." International Journal of Intelligent Information Technologies 13, no. 2 (April 2017): 1–20. http://dx.doi.org/10.4018/ijiit.2017040101.

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An association rule is classified as sensitive if its thread of revelation is above certain confidence value. If these sensitive rules were revealed to the public, it is possible to deduce sensitive knowledge from the published data and offers benefit for the business competitors. Earlier studies in privacy preserving association rule mining focus on binary data and has more side effects. But in practical applications the transactions contain the purchased quantities of the items. Hence preserving privacy of quantitative data is essential. The main goal of the proposed system is to hide a group of interesting patterns which contains sensitive knowledge such that modifications have minimum side effects like lost rules, ghost rules, and number of modifications. The proposed system applies Particle Swarm Optimization to a few clusters of particles thus reducing the number of modification. Experimental results demonstrate that the proposed approach is efficient in terms of lost rules, number of modifications, hiding failure with complete avoidance of ghost rules.

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23

B., Suma, and Shobha G. "Association rule hiding using integer linear programming." International Journal of Electrical and Computer Engineering (IJECE) 11, no. 4 (August 1, 2021): 3451. http://dx.doi.org/10.11591/ijece.v11i4.pp3451-3458.

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<span>Privacy preserving data mining has become the focus of attention of government statistical agencies and database security research community who are concerned with preventing privacy disclosure during data mining. Repositories of large datasets include sensitive rules that need to be concealed from unauthorized access. Hence, association rule hiding emerged as one of the powerful techniques for hiding sensitive knowledge that exists in data before it is published. In this paper, we present a constraint-based optimization approach for hiding a set of sensitive association rules, using a well-structured integer linear program formulation. The proposed approach reduces the database sanitization problem to an instance of the integer linear programming problem. The solution of the integer linear program determines the transactions that need to be sanitized in order to conceal the sensitive rules while minimizing the impact of sanitization on the non-sensitive rules. We also present a heuristic sanitization algorithm that performs hiding by reducing the support or the confidence of the sensitive rules. The results of the experimental evaluation of the proposed approach on real-life datasets indicate the promising performance of the approach in terms of side effects on the original database.</span>

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24

Zhu, Chenyi. "Realistic Dilemma and Improvement of Sensitive Personal Information Processing Rules." Journal of Education, Humanities and Social Sciences 14 (May 30, 2023): 256–62. http://dx.doi.org/10.54097/ehss.v14i.8847.

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The Personal Information Protection Law has a special chapter to stipulate the special pro-cessing rules of sensitive personal information, which reflects the value orientation of strengthening the protection of sensitive personal information. However, due to the mode of permitting the processing of sensitive personal information in principle and restricting pro-cessing with exceptions, the protection of sensitive personal information is greatly weakened in fact. Through the comprehensive analysis of our country's specific specifications of pro-cessing mode of principled prohibition and exception prohibition and combined with compara-tive law experience, the processing of sensitive personal information should adopt the legis-lative mode of principled prohibition and exception permission, and further limit the processing of exceptional allowed circumstances.

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25

Zhu, Chenyi. "Realistic Dilemma and Improvement of Sensitive Personal Information Processing Rules." Journal of Education, Humanities and Social Sciences 14 (May 30, 2023): 127–33. http://dx.doi.org/10.54097/ehss.v14i.8806.

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The Personal Information Protection Law has a special chapter to stipulate the special pro-cessing rules of sensitive personal information, which reflects the value orientation of strengthening the protection of sensitive personal information. However, due to the mode of permitting the processing of sensitive personal information in principle and restricting pro-cessing with exceptions, the protection of sensitive personal information is greatly weakened in fact. Through the comprehensive analysis of our country's specific specifications of pro-cessing mode of principled prohibition and exception prohibition and combined with compara-tive law experience, the processing of sensitive personal information should adopt the legis-lative mode of principled prohibition and exception permission, and further limit the processing of exceptional allowed circumstances.

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26

Ali, Munawar. "Sustainability Index of Benoa Bay Beach Reclamation Against National Resistance." INFLUENCE: INTERNATIONAL JOURNAL OF SCIENCE REVIEW 5, no. 2 (April 5, 2023): 43–62. http://dx.doi.org/10.54783/influencejournal.v5i2.135.

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This study aims to analyze systematically and thoroughly about how the impact of coastal reclamation on National Resilience. The activity starts from a thorough understanding of the system that occurs in the reclamation and variable processes that affect national security. The research method used analysis Multi-Dimensional Scaling Method. The Benoa Bay reclamation activity plan, multi-dimensional analysis is not or less sustainable, with an index of 42.93 %. The most sensitive attribute influences the dimensions of the environment, is the attribute of potential sedimentation is the most sensitive attribute with a value of 0.13. The most sensitive attribute affecting the economic dimension is an increase in regional revenue. In the sensitivity test of the socio-cultural dimension, the most sensitive and influential attribute obtained is the perception of the community shop. The most sensitive attribute influencing the legal dimension is the formal rules, there must be formal rules, indeed administratively the formal rules are legal products that are approved by the institutions governed by the law, but usually what is forgotten is the process of realizing formal rules.

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27

KAPLAN, ABBY. "How much homophony is normal?" Journal of Linguistics 47, no. 3 (April 18, 2011): 631–71. http://dx.doi.org/10.1017/s0022226711000053.

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This paper argues that neutralizing phonological alternations are sensitive to how much homophony they create among distinct lexical items: neutralizing rules create fewer homophones than expected. Building on a case study of Korean by Silverman (2010), I compare the neutralizing rules of Korean to a large number of hypothetical alternatives generated by Monte Carlo simulations. The simulations reveal that the actual rules of Korean frequently create far fewer homophones than similar (but unattested) rules, even when the rules that are compared are controlled for the number of phonemic contrasts they eliminate. These results suggest that phonological patterns are sensitive not only to high-level contrasts among phonemes but also to contrasts among individual lexical items. The effect is most pronounced when homophones are not weighted by frequency, a result that adds to evidence in the literature that the relevant measure of lexical frequency for many lexicon-sensitive phonological patterns is type frequency, not token frequency.

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28

Le, Bac, Lien Kieu, and Dat Tran. "DISTORTION-BASED HEURISTIC METHOD FOR SENSITIVE ASSOCIATION RULE HIDING." Journal of Computer Science and Cybernetics 35, no. 4 (October 31, 2019): 337–54. http://dx.doi.org/10.15625/1813-9663/35/4/14131.

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In the past few years, privacy issues in data mining have received considerable attention in the data mining literature. However, the problem of data security cannot simply be solved by restricting data collection or against unauthorized access, it should be dealt with by providing solutions that not only protect sensitive information, but also not affect to the accuracy of the results in data mining and not violate the sensitive knowledge related with individual privacy or competitive advantage in businesses. Sensitive association rule hiding is an important issue in privacy preserving data mining. The aim of association rule hiding is to minimize the side effects on the sanitized database, which means to reduce the number of missing non-sensitive rules and the number of generated ghost rules. Current methods for hiding sensitive rules cause side effects and data loss. In this paper, we introduce a new distortion-based method to hide sensitive rules. This method proposes the determination of critical transactions based on the number of non-sensitive maximal frequent itemsets that contain at least one item to the consequent of the sensitive rule, they can be directly affected by the modified transactions. Using this set, the number of non-sensitive itemsets that need to be considered is reduced dramatically. We compute the smallest number of transactions for modification in advance to minimize the damage to the database. Comparative experimental results on real datasets showed that the proposed method can achieve better results than other methods with fewer side effects and data loss.

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Mary, A. Geetha, D. P. Acharjya, and N. Ch S. N. Iyengar. "Privacy preservation in fuzzy association rules using rough computing and DSR." Cybernetics and Information Technologies 14, no. 1 (March 1, 2014): 52–71. http://dx.doi.org/10.2478/cait-2014-0005.

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Abstract In the present age of Internet, data is accumulated at a dramatic pace. The accumulated huge data has no relevance, unless it provides certain useful information pertaining to the interest of the organization. But the real challenge lies in hiding sensitive information in order to provide privacy. Therefore, attribute reduction becomes an important aspect for handling such huge database by eliminating superfluous or redundant data to enable a sensitive rule hiding in an efficient manner before it is disclosed to the public. In this paper we propose a privacy preserving model to hide sensitive fuzzy association rules. In our model we use two processes, named a pre-process and post-process to mine fuzzified association rules and to hide sensitive rules. Experimental results demonstrate the viability of the proposed research.

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30

Whittle, Peter. "The risk-sensitive certainty equivalence principle." Journal of Applied Probability 23, A (1986): 383–88. http://dx.doi.org/10.2307/3214366.

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A risk-sensitive certainty equivalence principle is deduced, expressed in Theorem 1, for a model with linear dynamics and observation rules, Gaussian noise and an exponential-quadratic criterion of the form (2). The senses in which one is now to understand certainty equivalence and the separation principle are discussed.

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Whittle, Peter. "The risk-sensitive certainty equivalence principle." Journal of Applied Probability 23, A (1986): 383–88. http://dx.doi.org/10.1017/s0021900200117218.

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A risk-sensitive certainty equivalence principle is deduced, expressed in Theorem 1, for a model with linear dynamics and observation rules, Gaussian noise and an exponential-quadratic criterion of the form (2). The senses in which one is now to understand certainty equivalence and the separation principle are discussed.

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32

Zwicky, Arnold M., Ellen M. Kaisse, Elizabeth A. Cowper, and Keren D. Rice. "Are phonosyntactic rules necessary?" Phonology Yearbook 4, no. 1 (May 1987): 185–94. http://dx.doi.org/10.1017/s0952675700000816.

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Selkirk (1986) proposes that rules of the phrasal phonology apply to a structure called P-structure that is derived from, but not isomorphic to, syntactic structure. While Selkirk claims that most rules of external sandhi fall into the category of P-structure rules, there are three rules that she suggests may still require direct reference to syntactic structure. These are Mende Consonant Mutation (Conteh et al. 1986), Kimatuumbi Vowel Shortening (Odden this volume), and ‘perhaps even rules like English wanna contraction’ (Selkirk 1986: 374). Selkirk says that these rules ‘appear to be sensitive to a richer array of syntactic conditions than would be expressible via the translation of syntax into P-structure’.

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Felando, Cynthia. "Breaking the rules of the game." Short Film Studies 9, no. 2 (April 1, 2019): 157–60. http://dx.doi.org/10.1386/sfs.9.2.157_1.

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El Adiós is a sincere portrait of a dutiful servant as she tends to her deceased employer’s body and home for the last time, while enduring the routine class-based offenses delivered by her employer’s daughter. This article notes how camerawork and mise en scène emphasize the protagonist’s sensitive and ambiguous position.

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Jing Yang, Junwei Zhang, Jianpei Zhang, and Lejun Zhang. "Blocking Inference Channels of Sensitive Rules in Data Stream Mining." INTERNATIONAL JOURNAL ON Advances in Information Sciences and Service Sciences 5, no. 7 (April 15, 2013): 196–203. http://dx.doi.org/10.4156/aiss.vol5.issue7.24.

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Sirole, Tapan, and Jaytrilok Choudhary. "A Survey of Various Methodologies for Hiding Sensitive Association Rules." International Journal of Computer Applications 96, no. 18 (June 18, 2014): 12–15. http://dx.doi.org/10.5120/16893-6942.

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Patel, Deepak, and Vineet Richhariya. "C Privacy Prevention of Discriminating Rules by Perturbing Sensitive Items." Communications on Applied Electronics 2, no. 8 (September 24, 2015): 12–16. http://dx.doi.org/10.5120/cae2015651825.

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37

Rajalakshmi, M., and T. Purusothaman. "Concealing party-centric sensitive rules in a centralized data source." International Journal of Machine Learning and Cybernetics 4, no. 5 (July 5, 2012): 515–25. http://dx.doi.org/10.1007/s13042-012-0111-y.

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38

Zhao, Mingjun. "Optimal simple rules in RE models with risk sensitive preferences." Economics Letters 97, no. 3 (December 2007): 260–66. http://dx.doi.org/10.1016/j.econlet.2007.03.004.

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39

Sharma, Dhiraj, Meenakshi Bansal, and Dinesh Grover. "Storage and Query Over Encrypted Sensitive Association Rules in Database." International Journal of Internet Technology and Secured Transactions 1, no. 1 (2019): 1. http://dx.doi.org/10.1504/ijitst.2019.10012622.

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Bansal, Meenakshi, Dinesh Grover, and Dhiraj Sharma. "Storage and query over encrypted sensitive association rules in database." International Journal of Internet Technology and Secured Transactions 9, no. 3 (2019): 242. http://dx.doi.org/10.1504/ijitst.2019.101818.

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Khalil Jumaa, Alaa, Sufyan T. F. Al-Janabi, and Nazar Abedlqader Ali. "Hiding Sensitive Association Rules over Privacy Preserving Distributed Data Mining." Kirkuk University Journal-Scientific Studies 9, no. 1 (June 28, 2014): 59–72. http://dx.doi.org/10.32894/kujss.2014.89609.

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Ferroni, Marina, Beatriz Diuk, and Milagros Mena. "Acquisition of orthographic knowledge: orthographic representations and context sensitive rules." psicología desde el caribe 33, no. 3 (September 1, 2016): 237–43. http://dx.doi.org/10.14482/psdc.33.3.6942.

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Ferroni, Marina, Beatriz Diuk, and Milagros Mena. "Acquisition of orthographic knowledge: orthographic representations and context sensitive rules." Psicología desde el Caribe 33, no. 3 (November 15, 2016): 237–43. http://dx.doi.org/10.14482/psdc.33.3.9487.

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B., Suma, and Shobha G. "Privacy preserving association rule hiding using border based approach." Indonesian Journal of Electrical Engineering and Computer Science 23, no. 2 (August 1, 2021): 1137. http://dx.doi.org/10.11591/ijeecs.v23.i2.pp1137-1145.

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<div>Association rule mining is a well-known data mining technique used for extracting hidden correlations between data items in large databases. In the majority of the situations, data mining results contain sensitive information about individuals and publishing such data will violate individual secrecy. The challenge of association rule mining is to preserve the confidentiality of sensitive rules when releasing the database to external parties. The association rule hiding technique conceals the knowledge extracted by the sensitive association rules by modifying the database. In this paper, we introduce a border-based algorithm for hiding sensitive association rules. The main purpose of this approach is to conceal the sensitive rule set while maintaining the utility of the database and association rule mining results at the highest level. The performance of the algorithm in terms of the side effects is demonstrated using experiments conducted on two real datasets. The results show that the information loss is minimized without sacrificing the accuracy. </div>

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Quoc Le, Hai, Somjit Arch-int, and Ngamnij Arch-int. "Association Rule Hiding Based on Intersection Lattice." Mathematical Problems in Engineering 2013 (2013): 1–11. http://dx.doi.org/10.1155/2013/210405.

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Association rule hiding has been playing a vital role in sensitive knowledge preservation when sharing data between enterprises. The aim of association rule hiding is to remove sensitive association rules from the released database such that side effects are reduced as low as possible. This research proposes an efficient algorithm for hiding a specified set of sensitive association rules based on intersection lattice of frequent itemsets. In this research, we begin by analyzing the theory of the intersection lattice of frequent itemsets and the applicability of this theory into association rule hiding problem. We then formulate two heuristics in order to (a) specify the victim items based on the characteristics of the intersection lattice of frequent itemsets and (b) identify transactions for data sanitization based on the weight of transactions. Next, we propose a new algorithm for hiding a specific set of sensitive association rules with minimum side effects and low complexity. Finally, experiments were carried out to clarify the efficiency of the proposed approach. Our results showed that the proposed algorithm, AARHIL, achieved minimum side effects and CPU-Time when compared to current similar state of the art approaches in the context of hiding a specified set of sensitive association rules.

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Jiang, Ying, Ming Jing, Jie Zeng, Feng Qi Shen, Du Lan Qi, and Li Hua Wang. "LanguageTool Based Proofreading of Sensitive Chinese Political Information." Applied Mechanics and Materials 687-691 (November 2014): 2644–47. http://dx.doi.org/10.4028/www.scientific.net/amm.687-691.2644.

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Sensitive Chinese political information are partly monitored and controlled by Chinese mainstream media (newspaper, television, the Internet, etc.) and the National Security Agency as well as corresponding political authorities. However, Chinese media authorities still lack in a technology or some methods to detect and identify sensitive Chinese political information quickly and efficiently. Due to complexity of sensitive Chinese political information, it cannot be monitored by a list of keywords or a simple pattern matching. How to satisfy the demands of media institutions is one of the most important problems. The main purpose of this paper is to combine the redacting technology of Chinese grammar rules with sensitive Chinese political information in order to provide the LanguageTool XML rules suitable for monitoring sensitive Chinese political information.

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Yi, Tong, and Minyong Shi. "Privacy Protection Method for Multiple Sensitive Attributes Based on Strong Rule." Mathematical Problems in Engineering 2015 (2015): 1–14. http://dx.doi.org/10.1155/2015/464731.

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At present, most studies on data publishing only considered single sensitive attribute, and the works on multiple sensitive attributes are still few. And almost all the existing studies on multiple sensitive attributes had not taken the inherent relationship between sensitive attributes into account, so that adversary can use the background knowledge about this relationship to attack the privacy of users. This paper presents an attack model with the association rules between the sensitive attributes and, accordingly, presents a data publication for multiple sensitive attributes. Through proof and analysis, the new model can prevent adversary from using the background knowledge about association rules to attack privacy, and it is able to get high-quality released information. At last, this paper verifies the above conclusion with experiments.

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Negus, Oliver J., Andrew Dunn, and William Ridsdill-Smith. "Lower limb acute joint injuries: when to refer for X-ray?" British Journal of Hospital Medicine 81, no. 3 (March 2, 2020): 1–5. http://dx.doi.org/10.12968/hmed.2020.0055.

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This article summarises the clinical decision tools available to help decide when acute lower limb joint injuries should be referred for plain film radiography. The Ottawa foot and ankle rules are a tool for deciding whether to refer a patient for X-ray or not. The rules are highly sensitive, gaining National Institute for Health and Care Excellence recommendation in the UK, although they have limited benefit in some patient groups, such as those with peripheral neuropathy. The Ottawa knee rules are highly sensitive but less specific than the Pittsburgh decision rules. Although the Pittsburgh rules are more specific, they have been less extensively investigated and, unlike the Ottawa rules, are not National Institute for Health and Care Excellence recommended. A major barrier to use of these rules in clinical practice is the concern of litigation, although National Institute for Health and Care Excellence recommendation should reassure clinicians and thus reduce the amount of unnecessary radiation exposure.

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DOMINGO-FERRER, JOSEP, and VICENÇ TORRA. "A CRITIQUE OF THE SENSITIVITY RULES USUALLY EMPLOYED FOR STATISTICAL TABLE PROTECTION." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 10, no. 05 (October 2002): 545–56. http://dx.doi.org/10.1142/s0218488502001636.

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In statistical disclosure control of tabular data, sensitivity rules are commonly used to decide whether a table cell is sensitive and should therefore not be published. The most popular sensitivity rules are the dominance rule, the p%-rule and the pq-rule. The dominance rule has received critiques based on specific numerical examples and is being gradually abandoned by leading statistical agencies. In this paper, we construct general counterexamples which show that none of the above rules does adequately reflect disclosure risk if cell contributors or coalitions of them behave as intruders: in that case, releasing a cell declared non-sensitive can imply higher disclosure risk than releasing a cell declared sensitive. As possible solutions, we propose an alternative sensitivity rule based on the concentration of relative contributions. More generally, we suggest to complement a priori risk assessment based on sensitivity rules with a posteriori risk assessment which takes into account tables after they have been protected.

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Hayes, Daniel, Miguel Moreira, Isabel Boavida, Melanie Haslauer, Günther Unfer, Bernhard Zeiringer, Franz Greimel, Stefan Auer, Teresa Ferreira, and Stefan Schmutz. "Life Stage-Specific Hydropeaking Flow Rules." Sustainability 11, no. 6 (March 14, 2019): 1547. http://dx.doi.org/10.3390/su11061547.

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Peak-operating hydropower plants are usually the energy grid’s backbone by providing flexible energy production. At the same time, hydropeaking operations are considered one of the most adverse impacts on rivers, whereby aquatic organisms and their life-history stages can be affected in many ways. Therefore, we propose specific seasonal regulations to protect ecologically sensitive life cycle stages. By reviewing hydropeaking literature, we establish a framework for hydrological mitigation based on life-history stages of salmonid fish and their relationship with key parameters of the hydrograph. During migration and spawning, flows should be kept relatively stable, and a flow cap should be implemented to prevent the dewatering of spawning grounds during intragravel life stages. While eggs may be comparably tolerant to dewatering, post-hatch stages are very vulnerable, which calls for minimizing or eliminating the duration of drawdown situations and providing adequate minimum flows. Especially emerging fry are extremely sensitive to flow fluctuations. As fish then grow in size, they become less vulnerable. Therefore, an ‘emergence window’, where stringent thresholds on ramping rates are enforced, is proposed. Furthermore, time of day, morphology, and temperature changes must be considered as they may interact with hydropeaking. We conclude that the presented mitigation framework can aid the environmental enhancement of hydropeaking rivers while maintaining flexible energy production.

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