The Experts below are selected from a list of 1101 Experts worldwide ranked by ideXlab platform
Dan Zhang - One of the best experts on this subject based on the ideXlab platform.
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tIdfp mining frequent patterns in different databases with Transaction Id
Data Warehousing and Knowledge Discovery, 2009Co-Authors: C I Ezeife, Dan ZhangAbstract:Since Transaction Identifiers (Ids) are unique and would not usually be frequent, mining frequent patterns with Transaction Ids, showing records they occurred in, provIdes an efficient way to mine frequent patterns in many types of databases including multiple tabled and distributed databases. Existing work have not focused on mining frequent patterns with the Transaction Ids they occurred in. Many applications require finding strong associations between Transaction Id (e.g., certain drug) and the itemsets (e.g., certain adverse effects) to help deduce some pertinent lacking information (like how many people use this product in total) and information (like how many people have the adverse effects). This paper proposes a set of algorithms TIdFPs, for mining frequent patterns with their Transaction Ids in a single Transaction database, in a multiple tabled database, and in a distributed database. The proposed technique scans the database records only once even with level-wise Apriori-based mining techniques, stores frequent 1-items with their Transaction Id bitmap, outperforms traditional approaches and is extendible to other tree-based mining techniques as well as sequential mining.
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DaWaK - TIdFP: Mining Frequent Patterns in Different Databases with Transaction Id
Data Warehousing and Knowledge Discovery, 2009Co-Authors: C I Ezeife, Dan ZhangAbstract:Since Transaction Identifiers (Ids) are unique and would not usually be frequent, mining frequent patterns with Transaction Ids, showing records they occurred in, provIdes an efficient way to mine frequent patterns in many types of databases including multiple tabled and distributed databases. Existing work have not focused on mining frequent patterns with the Transaction Ids they occurred in. Many applications require finding strong associations between Transaction Id (e.g., certain drug) and the itemsets (e.g., certain adverse effects) to help deduce some pertinent lacking information (like how many people use this product in total) and information (like how many people have the adverse effects). This paper proposes a set of algorithms TIdFPs, for mining frequent patterns with their Transaction Ids in a single Transaction database, in a multiple tabled database, and in a distributed database. The proposed technique scans the database records only once even with level-wise Apriori-based mining techniques, stores frequent 1-items with their Transaction Id bitmap, outperforms traditional approaches and is extendible to other tree-based mining techniques as well as sequential mining.
C I Ezeife - One of the best experts on this subject based on the ideXlab platform.
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Mining Integrated Sequential Patterns From Multiple Databases
International Journal of Data Warehousing and Mining, 2020Co-Authors: C I Ezeife, Vignesh Aravindan, Ritu ChaturvediAbstract:Existing work on multiple databases (MDBs) sequential pattern mining cannot mine frequent sequences to answer exact and historical queries from MDBs having different table structures. This article proposes the Transaction Id frequent sequence pattern (TIdFSeq) algorithm to handle the difficult problem of mining frequent sequences from diverse MDBs. The TIdFSeq algorithm transforms candIdate 1-sequences to get Transaction subsequences where candIdate 1-sequences occurred as (1-sequence, itssubsequenceIdlist) tuple or (1-sequence, position Id list). Subsequent frequent i-sequences are computed using the counts of the sequence Ids in each candIdate i-sequence position Id list tuples. An extended version of the general sequential pattern (GSP)-like candIdate generates and a frequency count approach is used for computing supports of itemset (I-step) and separate (S-step) sequences without repeated database scans but with Transaction Ids. Generated patterns answer complex queries from MDBs. The TIdFSeq algorithm has a faster processing time than existing algorithms.
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tIdfp mining frequent patterns in different databases with Transaction Id
Data Warehousing and Knowledge Discovery, 2009Co-Authors: C I Ezeife, Dan ZhangAbstract:Since Transaction Identifiers (Ids) are unique and would not usually be frequent, mining frequent patterns with Transaction Ids, showing records they occurred in, provIdes an efficient way to mine frequent patterns in many types of databases including multiple tabled and distributed databases. Existing work have not focused on mining frequent patterns with the Transaction Ids they occurred in. Many applications require finding strong associations between Transaction Id (e.g., certain drug) and the itemsets (e.g., certain adverse effects) to help deduce some pertinent lacking information (like how many people use this product in total) and information (like how many people have the adverse effects). This paper proposes a set of algorithms TIdFPs, for mining frequent patterns with their Transaction Ids in a single Transaction database, in a multiple tabled database, and in a distributed database. The proposed technique scans the database records only once even with level-wise Apriori-based mining techniques, stores frequent 1-items with their Transaction Id bitmap, outperforms traditional approaches and is extendible to other tree-based mining techniques as well as sequential mining.
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DaWaK - TIdFP: Mining Frequent Patterns in Different Databases with Transaction Id
Data Warehousing and Knowledge Discovery, 2009Co-Authors: C I Ezeife, Dan ZhangAbstract:Since Transaction Identifiers (Ids) are unique and would not usually be frequent, mining frequent patterns with Transaction Ids, showing records they occurred in, provIdes an efficient way to mine frequent patterns in many types of databases including multiple tabled and distributed databases. Existing work have not focused on mining frequent patterns with the Transaction Ids they occurred in. Many applications require finding strong associations between Transaction Id (e.g., certain drug) and the itemsets (e.g., certain adverse effects) to help deduce some pertinent lacking information (like how many people use this product in total) and information (like how many people have the adverse effects). This paper proposes a set of algorithms TIdFPs, for mining frequent patterns with their Transaction Ids in a single Transaction database, in a multiple tabled database, and in a distributed database. The proposed technique scans the database records only once even with level-wise Apriori-based mining techniques, stores frequent 1-items with their Transaction Id bitmap, outperforms traditional approaches and is extendible to other tree-based mining techniques as well as sequential mining.
Sharon Goldberg - One of the best experts on this subject based on the ideXlab platform.
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PAM - The Unintended Consequences of Email Spam Prevention
Passive and Active Measurement, 2018Co-Authors: Sarah Scheffler, Sean Smith, Yossi Gilad, Sharon GoldbergAbstract:To combat Domain Name System (DNS) cache poisoning attacks and exploitation of the DNS as amplifier in denial of service (DoS) attacks, many recursive DNS resolvers are configured as “closed” and refuse to answer queries made by hosts outsIde of their organization. In this work, we present a technique to induce DNS queries within an organization, using the organization’s email service and the Sender Policy Framework (SPF) spam-checking mechanism. We use our technique to study closed resolvers. Our study reveals that most closed DNS resolvers have deployed common DNS poisoning defense techniques such as source port and Transaction Id randomization. However, we also find that SPF is often deployed in a way that allows an external attacker to cause the organization’s resolver to issue numerous DNS queries to a victim IP address by sending a single email to any address within the organization’s domain, thereby provIding a potential DoS vector.
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The Unintended Consequences of Email Spam Prevention
Passive and Active Measurement, 2018Co-Authors: Stefanie Scheffler, Sean Smith, Yossi Gilad, Sharon GoldbergAbstract:To combat Domain Name System (DNS) cache poisoning attacks and exploitation of the DNS as amplifier in denial of service (DoS) attacks, many recursive DNS resolvers are configured as “closed” and refuse to answer queries made by hosts outsIde of their organization. In this work, we present a technique to induce DNS queries within an organization, using the organization’s email service and the Sender Policy Framework (SPF) spam-checking mechanism. We use our technique to study closed resolvers. Our study reveals that most closed DNS resolvers have deployed common DNS poisoning defense techniques such as source port and Transaction Id randomization. However, we also find that SPF is often deployed in a way that allows an external attacker to cause the organization’s resolver to issue numerous DNS queries to a victim IP address by sending a single email to any address within the organization’s domain, thereby provIding a potential DoS vector.
Stefanie Scheffler - One of the best experts on this subject based on the ideXlab platform.
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The Unintended Consequences of Email Spam Prevention
Passive and Active Measurement, 2018Co-Authors: Stefanie Scheffler, Sean Smith, Yossi Gilad, Sharon GoldbergAbstract:To combat Domain Name System (DNS) cache poisoning attacks and exploitation of the DNS as amplifier in denial of service (DoS) attacks, many recursive DNS resolvers are configured as “closed” and refuse to answer queries made by hosts outsIde of their organization. In this work, we present a technique to induce DNS queries within an organization, using the organization’s email service and the Sender Policy Framework (SPF) spam-checking mechanism. We use our technique to study closed resolvers. Our study reveals that most closed DNS resolvers have deployed common DNS poisoning defense techniques such as source port and Transaction Id randomization. However, we also find that SPF is often deployed in a way that allows an external attacker to cause the organization’s resolver to issue numerous DNS queries to a victim IP address by sending a single email to any address within the organization’s domain, thereby provIding a potential DoS vector.
Farid Ahmed - One of the best experts on this subject based on the ideXlab platform.
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A dual Fourier-wavelet domain authentication-Identification watermark.
Optics Express, 2007Co-Authors: Farid AhmedAbstract:A dual Fourier-Wavelet domain watermarking technique for authentication and Identity verification is proposed. Discrete wavelet transform (DWT) domain spread spectrum is used for embedding Identity (such as registration number, Transaction Id etc.) information. While a blind detector detects an Id, it is important to valIdate with other ancillary data. To satisfy that requirement, we embed a robust signature and hIde it in a mId-band wavelet subband using Fourier domain bit-embedding algorithm. Results are furnished to show the compression tolerance of the method.