Monitoring Smartphones for Anomaly Detection

Schmidt, Aubrey-Derrick; Peters, Frank; Lamour, Florian; Albayrak, Şahin

doi:10.4108/icst.mobilware2008.2492

Cited by 33 publications

(32 citation statements)

References 6 publications

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“…An example of a broad alert may be the current national threat level, namely levels green, blue, yellow, orange, red. Within these levels (which may be interpreted as the environment for CV-KM) more specific focus can be applied by using more sensitive parameters in the templates or by instantiating templates associated with the current, more specific levels, and in the evidence combination algorithms discussed in (Goldschmidt 2006). Weaver and Richardson (2006) present an instructive discussion on threshold settings in dynamic environments.…”

Section: Discussion and Lessons Learnedmentioning

confidence: 99%

“…Full details of the ALCOD (Alert Coding) system are available at Goldschmidt (2006), where the ALCOD implementation describes the application of the CV-KM prototype to the Australian Stock Market surveillance operation at the time ALCOD was tested. Since then ASX Surveillance have replaced their PMS, and reviewed and rationalized the number of alert types requiring coding.…”

Section: Problem Structurementioning

confidence: 99%

“…The agents use either task or data sharing to cooperate with other agents." Therefore each team member has a CV-KM IDSS, database, and graphic user interface [GUI] which takes the form of an analyst's workbench or control panel (illustrated in Goldschmidt 2006), plus access to the team memory repository, the blackboard, other databases containing historical information, and relevant external information sources such as real-time market information, news services, or brokers' newsletters.…”

Section: A Framework For Cv-km Using Multi-agent Technology (Mat)-tecmentioning

confidence: 99%

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Managing the false alarms: A framework for assurance and verification of surveillance monitoring

Goldschmidt

2007

Inf Syst Front

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This article discusses methods to support assurance of surveillance monitoring and compliance verification knowledge management (CV-KM). The discussion includes aspects of primary monitoring systems, the different environments in which they operate, the verification problem solving and decision making tasks, the problem structure, and the coordination of the review process to facilitate truth maintenance and regulatory Meta rules. Based on the ALCOD (Alert Coding) prototype developed with the Surveillance Division of the Australian Stock Exchange (ASX), the surveillance operation is considered a primary monitoring function with the analysis of the resulting output the second-tier monitoring function-the assurance component.

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Section: Discussion and Lessons Learnedmentioning

confidence: 99%

Section: Problem Structurementioning

confidence: 99%

Section: A Framework For Cv-km Using Multi-agent Technology (Mat)-tecmentioning

confidence: 99%

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Managing the false alarms: A framework for assurance and verification of surveillance monitoring

Goldschmidt

2007

Inf Syst Front

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“…Thus, we give a brief overview of related academic research. Schmidt A.D., et al [7][8][9][10][11][12][13]is the pioneer in android security research, they provided both dynamic and static analysis methods for malware detection on android platform. Since then, a series of works on malware detection were proposed, while most of them are transplanted from desktop platform [14][15][16][17].…”

Section: E Status Of Academic Researchmentioning

confidence: 99%

Mobile Security Apps: Loyal Gaurds or Hypocritical Thieves?

Sun

Wang

2014

2014 Ninth International Conference on P2P, Parallel, Grid, Cloud and Internet Computing

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Mobile security app plays an important role in managing third-party apps and protecting user's data on smart phone. However, who can guarantee mobile security app's loyalty, or who can determine a given mobile security app is not a hypocritical thief? Thus, it is very necessary to establish a supervision mechanism to restrict mobile security app for user's privacy, but there isn't any technique to supervise the behavior of security apps till now. We summarized the security scenario of android smart phone from five aspects, and proposed a Competitive Supervision Mechanism and three theoretical supportive techniques to supervise mobile security app for user's security concern.

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“…According to the study [4][5][6][7][8][9] of malicious code in the application, the paper gives a classification, it is showed in Figure 1. Enck [10] put forward a research method named dynamic taint analysis and had accomplished the design and implementation of TaintDroid.…”

Section: Current Study and Insufficiencymentioning

confidence: 99%

Implementation of automated testing system for android applications based on dynamic taint propagation

Kelong¹,

Song²,

Fei³

2014

2014 Communications Security Conference (CSC 2014)

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As the increasing downloads of applications via Android Platform, more and more malicious codes were injected in those applications. And some problems are caused by that malicious code such as economic loss and privacy issues. Android has the highest market share of smartphone operating system, the security of Android platform is extremely important. Therefore, the security testing and evaluation of applications is imperative. Dynamic taint propagation is the most common method to do the test, but there are two problems: a) If the custom ROM runs in the smartphone, the running speed of ROM will be limited to the smartphone's battery life and computing power. b) If the program was running in emulator in PC, the efficiency will be very poor because of the manual operation for the triggering action during the running time. The paper presents an automated testing method which was accomplished in emulator. In addition, the system will record the tree structure of Activity and control distribution of each Activity. The test results showed that the system can trigger all the controls and compared with manual test, this method was proven to be more effective and completely.

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Monitoring Smartphones for Anomaly Detection

Cited by 33 publications

References 6 publications

Managing the false alarms: A framework for assurance and verification of surveillance monitoring

Managing the false alarms: A framework for assurance and verification of surveillance monitoring

Mobile Security Apps: Loyal Gaurds or Hypocritical Thieves?

Implementation of automated testing system for android applications based on dynamic taint propagation

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