A Dynamic Trust Model Enforcing Security Policies

Ghazinour, Kambiz; Ghayoumi, Mehdi

doi:10.1145/2816839.2816909

Cited by 2 publications

(5 citation statements)

References 6 publications

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“…In [3], the authors present a dynamic trust model to enforce security policies. Our model is based on their trust model.…”

Section: Iiitrusted Dynamic User Interface (Tdui)mentioning

confidence: 99%

“…It also enables the security officers and designers to have the opportunity for immediate testing to see if the roles are working as they should. In [3] the notion of trust is addressed when an access control systems is desired to behave truly dynamically. That is, when users misuse the access level that they have been granted or try to access the data that they are not supposed to access, the model should raise a flag and limit/reduce the privileges that the users have.…”

Section: Iintroductionmentioning

confidence: 99%

“…That is, when users misuse the access level that they have been granted or try to access the data that they are not supposed to access, the model should raise a flag and limit/reduce the privileges that the users have. In [3] a trust management component is introduced that handles trust levels associated with the users. It can modify the security policies assigned to the users and result in limiting or reducing their data access.…”

Section: Iintroductionmentioning

confidence: 99%

“…It can modify the security policies assigned to the users and result in limiting or reducing their data access. In this paper we take the model introduced in [3] and add a machine learning component that helps the system to adapt itself, learn from the user's behavior and recognize access patterns based on the similar access requests and not only limit the illegitimate access, but also predict and prevent potential malicious and questionable accesses. Machine learning can be considered as science for the design of computational methods using experience to improve their performance [4].…”

Section: Iintroductionmentioning

confidence: 99%

“…This paper is structured as follows: Section 2 describes background and related work. Section 3, briefly describes the trust model [3] based on which we propose our model. Sections 4 and 5 introduce our approach and how machine learning helps enforcing security policies based on user's behavior.…”

Section: Iintroductionmentioning

confidence: 99%

See 4 more Smart Citations

An autonomous model to enforce security policies based on user's behavior

Ghazinour

Ghayoumi

2015

2015 IEEE/ACIS 14th International Conference on Computer and Information Science (ICIS)

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To protect user's information, computer systems utilize access control models. These models are supported by a set of policies defined by security administrators in the environment where the organization is active. In previous studies it has been shown that building a user interface that dynamically changes with the security policies defined for each user is a cumbersome task. This work is a further expansion of an improved dynamic model that adjusts users' security policies based on the level of trust that they hold. We use machine learning beside the trust manager component that helps the system to adapt itself, learn from the user's behavior and recognize access patterns based on the similar access requests and not only limit the illegitimate access, but also predict and prevent potential malicious and questionable accesses.

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“…In [3], the authors present a dynamic trust model to enforce security policies. Our model is based on their trust model.…”

Section: Iiitrusted Dynamic User Interface (Tdui)mentioning

confidence: 99%

Section: Iintroductionmentioning

confidence: 99%

Section: Iintroductionmentioning

confidence: 99%

Section: Iintroductionmentioning

confidence: 99%

Section: Iintroductionmentioning

confidence: 99%

See 3 more Smart Citations

An autonomous model to enforce security policies based on user's behavior

Ghazinour

Ghayoumi

2015

2015 IEEE/ACIS 14th International Conference on Computer and Information Science (ICIS)

Self Cite

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Detecting Advanced Persistent Threats in Oracle Databases

Ray

Felch

2017

Advances in Business Information Systems and Analytics

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Advanced persistent threats (APTs) have become a big problem for computer systems. Databases are vulnerable to these threats and can give attackers access to an organizations sensitive data. Oracle databases are at greater risk due to their heavy use as back-ends to corporate applications such as enterprise resource planning software. This chapter will describe a methodology for finding APTs hiding or operating deep within an Oracle database system. Using an understanding of Oracle normal operations provides a baseline to assist in discovering APT behavior. Incorporating these and other techniques such as database activity monitoring, machine learning, neural networks and honeypots/tokens can create a database intrusion detection system capable of finding these threats.

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A Dynamic Trust Model Enforcing Security Policies

Cited by 2 publications

References 6 publications

An autonomous model to enforce security policies based on user's behavior

An autonomous model to enforce security policies based on user's behavior

Detecting Advanced Persistent Threats in Oracle Databases

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