Related papers: Attribute Based Administration of Role Based Acces…
To design a discretionary access control policy, a technique is proposed that uses the principle of analogies and is based on both the properties of objects and the properties of subjects. As attributes characterizing these properties, the…
Agentic AI systems increasingly act through tools, sub-agents, and external services, but governance controls are still commonly attached to prompts, dashboards, or post-hoc documentation. This creates a structural mismatch in regulated…
We describe an access control model that has been implemented in the web content management framework "Deme" (which rhymes with "team"). Access control in Deme is an example of what we call "bivalent relation object access control"(BROAC).…
GUI Process Automation (GPA) is a lightweight but general vision-based Robotic Process Automation (RPA), which enables fast and stable process replay with only a single demo. Addressing the fragility of traditional RPA and the…
In the field of access control, delegation is an important aspect that is considered as a part of the administration mechanism. Thus, a complete access control must provide a flexible administration model to manage delegation.…
Being a fully automated technique for resource analysis, automatic amortized resource analysis (AARA) can fail in returning worst-case cost bounds of programs, fundamentally due to the undecidability of resource analysis. For programmers…
Verifying user attributes to provide fine-grained access control to databases is fundamental to an attribute-based authentication system. In such systems, either a single (central) authority verifies all attributes, or multiple independent…
As AI agents attempt to autonomously act on users' behalf, they raise transparency and control issues. We argue that permission-based access control is indispensable in providing meaningful control to the users, but conventional permission…
The autonomy and contextual complexity of LLM-based agents render traditional access control (AC) mechanisms insufficient. Static, rule-based systems designed for predictable environments are fundamentally ill-equipped to manage the dynamic…
Role-Playing Agent (RPA) is an increasingly popular type of LLM Agent that simulates human-like behaviors in a variety of tasks. However, evaluating RPAs is challenging due to diverse task requirements and agent designs. This paper proposes…
Risk-based Authentication (RBA) is an adaptive security measure to strengthen password-based authentication. RBA monitors additional features during login, and when observed feature values differ significantly from previously seen ones,…
Robotic process automation (RPA) has emerged as the leading approach to automate tasks in business processes. Moving away from back-end automation, RPA automated the mouse-click on user interfaces; this outside-in approach reduced the…
Oracle E-Business Suite R12 is a widely used ERP solution that provides integrated view of information across multiple functions and sources. It allows for simplified business process tools for Shared service model e.g. Centralized…
There have been many proposals for access control models and authorization policy languages, which are used to inform the design of access control systems. Most, if not all, of these proposals impose restrictions on the implementation of…
To date, most work regarding the formal analysis of access control schemes has focused on quantifying and comparing the expressive power of a set of schemes. Although expressive power is important, it is a property that exists in an…
Programs with dynamic allocation are able to create and use an unbounded number of fresh resources, such as references, objects, files, etc. We propose History-Register Automata (HRA), a new automata-theoretic formalism for modelling such…
Attribute-based access control makes access control decisions based on the assigned attributes of subjects and the access policies to protect objects by mediating operations from the subjects. Authority, which validates attributes of…
Runtime adaptability is often a crucial requirement for today's complex software systems. Several approaches use an architectural model as a runtime representation of a managed system for monitoring, reasoning and performing adaptation. To…
Preference-based reinforcement learning (PbRL) has shown significant promise for personalization in human-robot interaction (HRI) by explicitly integrating human preferences into the robot learning process. However, existing practices often…
In machine learning, meta-learning methods aim for fast adaptability to unknown tasks using prior knowledge. Model-based meta-reinforcement learning combines reinforcement learning via world models with Meta Reinforcement Learning (MRL) for…