Creating effective access control policies is a significant challenge to many organizations. Over-privilege increases security risk from compromised credentials, insider threats, and accidental misuse. Under-privilege prevents users from performing their duties. Policies must balance between these competing goals of minimizing under-privilege vs. over-privilege. The Attribute Based Access Control (ABAC) model has been gaining popularity in recent years because of its advantages in granularity, flexibility, and usability. ABAC allows administrators to create policies based on attributes of users, operations, resources, and the environment. However, in practice, it is often very difficult to create effective ABAC policies in terms of minimizing under-privilege and over-privilege especially for large and complex systems because their ABAC privilege spaces are typically gigantic. In this paper, we take a rule mining approach to mine systems' audit logs for automatically generating ABAC policies which minimize both under-privilege and over-privilege. We propose a rule mining algorithm for creating ABAC policies with rules, a policy scoring algorithm for evaluating ABAC policies from the least privilege perspective, and performance optimization methods for dealing with the challenges of large ABAC privilege spaces. Using a large dataset of 4.7 million Amazon Web Service (AWS) audit log events, we demonstrate that our automated approach can effectively generate least privilege ABAC policies, and can generate policies with less over-privilege and under-privilege than a Role Based Access Control (RBAC) approach. Overall, we hope our work can help promote a wider and faster deployment of the ABAC model, and can help unleash the advantages of ABAC to better protect large and complex computing systems.
more »
« less
An Insider Threat Mitigation Framework Using Attribute Based Access Control
Insider Threat is a significant and potentially dangerous security issue in corporate settings. It is difficult to mitigate because, unlike external threats, insiders have knowledge of an organization’s access policies, access hierarchy, access protocols, and access scheduling. In addition, the complexity, time, and skill required to locate the threat source, model, and timestamp make it more difficult for organizations to combat. Several approaches to reducing insider threat have been proposed in the literature. However, the integration of access control and moving target defense (MTD) for deceiving insiders has not been adequately discussed. In this paper, we combine MTD, deception, and attribute-based access control to
make it more difficult and expensive for an insider to gain unauthorized access. We introduce the concept of correlated attributes into ABAC and extend the ABAC model with MTD by generating mutated policy using the correlated attributes for insider threat mitigation. The evaluation results show that the proposed framework can effectively identify correlated attributes and produce adequate mutated policy without affecting the usability of the access control systems.
more »
« less
- Award ID(s):
- 2006329
- PAR ID:
- 10425098
- Date Published:
- Journal Name:
- 7th Workshop on Research for Insider Threats (WRIT) - Annual Computer Security Applications Conference (ACSAC) 2022
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
null (Ed.)In the context of insiders, preventive security measures have a high likelihood of failing because insiders ought to have sufficient privileges to perform their jobs. Instead, in this paper, we propose to treat the insider threat by a detective measure that holds an insider accountable in case of violations. However, to enable accountability, we need to create causal models that support reasoning about the causality of a violation. Current security models (e.g., attack trees) do not allow that. Still, they are a useful source for creating causal models. In this paper, we discuss the value added by causal models in the security context. Then, we capture the interaction between attack trees and causal models by proposing an automated approach to extract the latter from the former. Our approach considers insider-specific attack classes such as collusion attacks and causal-model-specific properties like preemption relations. We present an evaluation of the resulting causal models’ validity and effectiveness, in addition to the efficiency of the extraction process.more » « less
-
Malicious insiders cause significant loss to organizations. Due to an extremely small number of malicious activities from insiders, insider threat is hard to detect. In this article, we present a Dirichlet Marked Hawkes Process (DMHP) to detect malicious activities from insiders in real-time. DMHP combines the Dirichlet process and marked Hawkes processes to model the sequence of user activities. The Dirichlet process is capable of detecting unbounded user modes (patterns) of infinite user activities, while, for each detected user mode, one set of marked Hawkes processes is adopted to model user activities from time and activity type (e.g., WWW visit or send email) information so that different user modes are modeled by different sets of marked Hawkes processes. To achieve real-time malicious insider activity detection, the likelihood of the most recent activity calculated by DMHP is adopted as a score to measure the maliciousness of the activity. Since the majority of user activities are benign, those activities with low likelihoods are labeled as malicious activities. Experimental results on two datasets show the effectiveness of DMHP.more » « less
-
The NGAC (Next Generation Access Control) standard for attribute-based access control (ABAC) allows for run-time changes of the permission and prohibition configurations through administrative obligations triggered by access events. It makes access control more fine-grained and dynamic. However, it raises challenges for assuring the correctness of NGAC policies. As policy testing is an important technique for quality assurance, this paper presents an approach to mutation analysis of NGAC policies. It can evaluate the effectiveness of a testing method and reveal potential faults in an inadequately tested policy. The mutation analysis covers various types of potential faults in the assignments, associations, prohibitions, and obligations of NGAC policies. This paper also proposes an incremental testing approach that first validates the initial configuration of a policy and then the policy as a whole. It helps determine whether faults appear in the configuration or the obligations. To evaluate the work, we have developed four working policies and their test suites based on the current NGAC reference implementation. The empirical studies show that the mutation analysis can shed light on the strengths and weaknesses of the test suites. They also demonstrate the need for developing more cost-effective testing methods.more » « less
-
Smart homes are interconnected homes in which a wide variety of digital devices with limited resources communicate with multiple users and among themselves using multiple protocols. The deployment of resource-limited devices and the use of a wide range of technologies expand the attack surface and position the smart home as a target for many potential security threats. Access control is among the top security challenges in smart home IoT. Several access control models have been developed or adapted for IoT in general, with a few specifically designed for the smart home IoT domain. Most of these models are built on the role-based access control (RBAC) model or the attribute-based access control (ABAC) model. However, recently some researchers demonstrated that the need arises for a hybrid model combining ABAC and RBAC, thereby incorporating the benefits of both models to better meet IoT access control challenges in general and smart homes requirements in particular. In this paper, we used two approaches to develop two different hybrid models for smart home IoT. We followed a role-centric approach and an attribute-centric approach to develop HyBAC RC and HyBAC AC , respectively. We formally define these models and illustrate their features through a use case scenario demonstration. We further provide a proof-of-concept implementation for each model in Amazon Web Services (AWS) IoT platform. Finally, we conduct a theoretical comparison between the two models proposed in this paper in addition to the EGRBAC model (RBAC model for smart home IoT) and HABAC model (ABAC model for smart home IoT), which were previously developed to meet smart homes’ challenges.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Conference Paper:
- The DOI is not currently available.
