A Robust Software Product Line Architecture for Data Collection in Android Platform

Waku, Gustavo M.; Bollis, Edson; Rubira, Cecília Mary Fischer; Torres, Ricardo da Silva

doi:10.1109/sbcars.2015.14

Cited by 6 publications

(11 citation statements)

References 13 publications

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“…FR1: Must be able to collect required security-related data in different situations and contexts [21]. FR2: Must be able to store collected data in a storage medium [22]. FR3: Must be able to know where and when to collect security-related data [22].…”

Section: A Requirements 1) Functional Requirements (Fr)mentioning

confidence: 99%

“…FR2: Must be able to store collected data in a storage medium [22]. FR3: Must be able to know where and when to collect security-related data [22]. FR4: Must be able to load information about which data should be collected [22].…”

Section: A Requirements 1) Functional Requirements (Fr)mentioning

confidence: 99%

“…FR3: Must be able to know where and when to collect security-related data [22]. FR4: Must be able to load information about which data should be collected [22]. FR5: Must be able to export data to other systems or create external database [22].…”

Section: A Requirements 1) Functional Requirements (Fr)mentioning

confidence: 99%

“…FR4: Must be able to load information about which data should be collected [22]. FR5: Must be able to export data to other systems or create external database [22]. FR6: Must have the ability to manage and control data [23].…”

Section: A Requirements 1) Functional Requirements (Fr)mentioning

confidence: 99%

“…SR1: Must be able to prevent data loss and ensure data truth in collecting data (data integrity, veracity and availability) [22]. SR2: Must protect user privacy in collecting data [27].…”

Section: ) Security Requirements (Sr)mentioning

confidence: 99%

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A Survey on Network Security-Related Data Collection Technologies

et al. 2018

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Security threats and economic loss caused by network attacks, intrusions, and vulnerabilities have motivated intensive studies on network security. Normally, data collected in a network system can reflect or can be used to detect security threats. We define these data as network security-related data. Studying and analyzing security-related data can help detect network attacks and intrusions, thus making it possible to further measure the security level of the whole network system. Obviously, the first step in detecting network attacks and intrusions is to collect security-related data. However, in the context of big data and 5G, there exist a number of challenges in collecting these security-related data. In this paper, we first briefly introduce network security-related data, including its definition and characteristics, and the applications of network data collection. We then provide the requirements and objectives for security-related data collection and present a taxonomy of data collection technologies. Moreover, we review existing collection nodes, collection tools, and collection mechanisms in terms of network data collection and analyze them based on the proposed requirements and objectives toward high quality security-related data collection. Finally, we discuss open research issues and conclude with suggestions for future research directions.INDEX TERMS Network security, security-related data, data collection technologies, large-scale heterogeneous networks.

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Section: A Requirements 1) Functional Requirements (Fr)mentioning

confidence: 99%

Section: A Requirements 1) Functional Requirements (Fr)mentioning

confidence: 99%

Section: A Requirements 1) Functional Requirements (Fr)mentioning

confidence: 99%

Section: A Requirements 1) Functional Requirements (Fr)mentioning

confidence: 99%

“…SR1: Must be able to prevent data loss and ensure data truth in collecting data (data integrity, veracity and availability) [22]. SR2: Must protect user privacy in collecting data [27].…”

Section: ) Security Requirements (Sr)mentioning

confidence: 99%

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