Towards rule-based visual programming of generic visual systems

This paper illustrates how the diagram programming language DiaPlan can be used to program visual systems. DiaPlan is a visual rule-based language that is founded on the computational model of graph transformation. The language supports object-oriented programming since its graphs are hierarchically structured. Typing allows the shape of these graphs to be specified recursively in order to increase program security. Thanks to its genericity, DiaPlan allows to implement systems that represent and manipulate data in arbitrary diagram notations. The environment for the language exploits the diagram editor generator DiaGen for providing genericity, and for implementing its user interface and type checker.Comment: 15 pages, 16 figures contribution to the First International Workshop on Rule-Based Programming (RULE'2000), September 19, 2000, Montreal, Canad

European welfare state under the policy "make work pay" : Analysis with composite indicators

The social security systems in 22 European countries are evaluated with a specially constructed indicator. It is based on a census-simulating model which combines both empirical (statistical) and normative (rule-based) approaches. The individual answers of unemployed on social security benefits are normatively derived from their personal situations with the OECD Tax-Benefit Models. The empirical data about personal situations are available from EuroStat. The goal is estimating the national average of net replacement rates (NRR) for unemployed persons. Such an indicator of social security shows the average degree with which social benefits compensate the loss of previous earnings. Thus, the paper suggests: -(Methodology) a model of census simulation combining statistical data on the population with individual answers computed with a rule-based model, -(Indicator) an integral quantitative evaluation of social security in Europe, which reveals its total decline by 2004 contrary to institutional improvements, -(Analysis) an explanation of the decline by a structural change of European labour markets with rapidly growing `atypical' employment groups (= part-time, temporary, self-employed, etc.) with a lower eligibility to social benefits than normally employed (= permanently full-time), -(Policy implications) a possible resolution of European policy contradictions by the "basic income model" with "flexinsurance". --Composite indicators,social security,European welfare state,European Union,"make work pay" policy

TAPInspector: Safety and Liveness Verification of Concurrent Trigger-Action IoT Systems

Trigger-action programming (TAP) is a popular end-user programming framework that can simplify the Internet of Things (IoT) automation with simple trigger-action rules. However, it also introduces new security and safety threats. A lot of advanced techniques have been proposed to address this problem. Rigorously reasoning about the security of a TAP-based IoT system requires a well-defined model and verification method both against rule semantics and physical-world states, e.g., concurrency, rule latency, and connection-based interactions, which has been missing until now. This paper presents TAPInspector, a novel system to detect vulnerabilities in concurrent TAP-based IoT systems using model checking. It automatically extracts TAP rules from IoT apps, translates them into a hybrid model with model slicing and state compression, and performs model checking with various safety and liveness properties. Our experiments corroborate that TAPInspector is effective: it identifies 533 violations with 9 new types of violations from 1108 real-world market IoT apps and is 60000 times faster than the baseline without optimization at least.Comment: 14 pages, 5 figure

A rule-based machine learning model for financial fraud detection

Financial fraud is a growing problem that poses a significant threat to the banking industry, the government sector, and the public. In response, financial institutions must continuously improve their fraud detection systems. Although preventative and security precautions are implemented to reduce financial fraud, criminals are constantly adapting and devising new ways to evade fraud prevention systems. The classification of transactions as legitimate or fraudulent poses a significant challenge for existing classification models due to highly imbalanced datasets. This research aims to develop rules to detect fraud transactions that do not involve any resampling technique. The effectiveness of the rule-based model (RBM) is assessed using a variety of metrics such as accuracy, specificity, precision, recall, confusion matrix, Matthew’s correlation coefficient (MCC), and receiver operating characteristic (ROC) values. The proposed rule-based model is compared to several existing machine learning models such as random forest (RF), decision tree (DT), multi-layer perceptron (MLP), k-nearest neighbor (KNN), naive Bayes (NB), and logistic regression (LR) using two benchmark datasets. The results of the experiment show that the proposed rule-based model beat the other methods, reaching accuracy and precision of 0.99 and 0.99, respectively

K-bass: A Knowledge–Based Access Security System For Medical Environments

Enforcing security requires the application of an access control model. The access control models used today have limitations that become evident when applied in collaborative environments, such as medical environments. To overcome these problems, a system has been developed in order to introduce dynamic access security. The system at hand combines effectively (C-TMAC) Team-based access control using contexts model and knowledge base technology. The system’s security scheme fine-grains the users’ access rights by integrating the Role Based Access Controls (RBAC) model and the (C-TMAC) model through knowledge-based systems technology. The originality lies on the fact that the users in the system are authenticated by combining their individual access rights (RBAC), their team’s access rights (C-TMAC) and the context information associated with the team they belong to. Furthermore, knowledge-based technology is used for the representation of knowledge and reasoning. The system initiates with some facts and rules and is able to learn, infer knowledge and produce meta-knowledge. Therefore the system can train itself and respond in non-deterministic way to user requests. Any change in context information fires a new rule in the knowledge base. The proposed system is an automated and self-controlled system called (K-BASS) Knowledge-based Access Security System that may be used in medical environments, to dynamically assign permission rights and to add new medical staff and patients

A Dashboard for Security Forces Data Visualization and Storytelling

Neto, M. D. C., Nascimento, M., Sarmento, P., Ribeiro, S., Rodrigues, T., & Painho, M. (2019). A Dashboard for Security Forces Data Visualization and Storytelling. In I. Ramos, R. Quaresma, P. R. D. Silva, & T. Oliveira (Eds.), Information Systems for Industry 4.0: Proceedings of the 18th Conference of the Portuguese Association for Information Systems (pp. 47-62). (Lecture Notes in Information Systems and Organisation; Vol. 31). Springer International Publishing. https://doi.org/10.1007/978-3-030-14850-8_4Being security assumed as a basic right of citizens in the current model of democratic rule of law, optimal resources allocation altogether with budgetary constraints are a key component. In fact optimal resources allocation and budgetary constraints oblige an increasingly careful strategic management, adapted to demographic reality. The SIM4SECURITY project aims to build a technological solution to support decision making regarding security, based on the development of a GIS model and in the implementation of demographic scenarios. This model will allow policy makers, leaders and forces of command units and services in the planning and rational affectation of resources adjusted to local dynamics in crime prevention and crime fighting. To communicate the SIM4SECURITY results and support decision making, a data visualization and storytelling approach was adopted by creating dashboards containing the various dimensions and perspectives of the information were elaborated and are presented. The obtained outcomes show that dashboards are an important visual tool in the decision-making process by providing meaningful insights regarding security and in the location-allocation of security forces.authorsversionpublishe