A Practical Approach for Dynamic Taint Tracking with Control-flow Relationships

Dynamic taint tracking, a technique that traces relationships between values as a program executes, has been used to support a variety of software engineering tasks. Some taint tracking systems only consider data flows and ignore control flows. As a result, relationships between some values are not reflected by the analysis. Many applications of taint tracking either benefit from or rely on these relationships being traced, but past works have found that tracking control flows resulted in over-tainting, dramatically reducing the precision of the taint tracking system. In this article, we introduce Conflux , alternative semantics for propagating taint tags along control flows. Conflux aims to reduce over-tainting by decreasing the scope of control flows and providing a heuristic for reducing loop-related over-tainting. We created a Java implementation of Conflux and performed a case study exploring the effect of Conflux on a concrete application of taint tracking, automated debugging. In addition to this case study, we evaluated Conflux ’s accuracy using a novel benchmark consisting of popular, real-world programs. We compared Conflux against existing taint propagation policies, including a state-of-the-art approach for reducing control-flow-related over-tainting, finding that Conflux had the highest F1 score on 43 out of the 48 total tests.

Raciocínio Baseado em Casos para a Configuração de Modelos de Alocação de Banda

The extensive adoption of computer networks, especially the Internet, using services that require extensive data flows, has generated a growing demand for computational resources, mainly bandwidth. Bandwidth Allocation Models (BAM) have proven to be a viable alternative to network management where the bandwidth resource is shared to meet the high demand for the network. However, managing these networks has become an increasingly complex task, and solutions that allow for nearly autonomous configuration with less intervention of the network manager are highly demanded. The use of Case-Based Reasoning (CBR) techniques for network management has proven satisfactory for decision making and network management. This work presents a proposal for network reconfiguration based on the CBR cycle, intelligence, and cognitive module for MPLS (Multi-Protocol Label Switching) networks. The results show that CBR is a feasible solution for auto-configuration with autonomic characteristics in the MPLS using bandwidth allocation models (BAMs). The proposal improved the general network performance.

Improving Take-Up by Reaching Out to Potential Beneficiaries. Insights from a Large-Scale Field Experiment in Belgium

Non-take-up of means-tested benefits is a widespread phenomenon which undermines the effectiveness and fairness of social policies. The digitalisation of the welfare state creates new opportunities for proactively contacting people who are potentially entitled to benefits, but do not take up their social rights. In this study, we report on how new data flows were used to reach out to potential beneficiaries of the Increased Reimbursement of health care, a programme targeted at low-income households in Belgium. By randomizing the period in which potential beneficiaries were contacted, we were able to identify a three- to four-fold increase in take-up among those contacted as a result of the outreaching activities. Households that did not respond to the intervention, the never takers, have lower pre-intervention healthcare expenditures. This suggests that non-take-up was reduced primarily among those who would expect to benefit most from receiving the Increased Reimbursement. Exploiting the combination of rich administrative data with experimental evidence, we also find that early responders are mostly older and have higher historic health expenditures than late responders. Furthermore, results point to the need for balancing well the inclusiveness of the intervention with an increased number of applications by ineligible people.

A Proposal to Distinguish DDoS Traffic in Flash Crowd Environments

A Flash Crowd (FC) event occurs when network traffic increases suddenly due to a specific reason (e.g. e-commerce sale). Despite its legitimacy, this kind of situation usually decreases the network resource performance. Furthermore, attackers may simulate FC situations to introduce undetected attacks, such as Distributed Denial of Service (DDoS), since it is very difficult to distinguish between legitimate and malicious data flows. To differentiate malicious and legitimate traffic we propose applying zero inflated count data models in conjunction with the Correlation Coefficient Flow (CCF) method – a well-known method used in FC situations. Our results were satisfactory and improve the accuracy of CCF method. Furthermore, since the environment toggles between normal and FC situations, our method has the advantage of working in both situations.

DEVELOPMENT OF A MATHEMATICAL MODEL FOR THE FUNCTIONING OF A MULTI-NODE DECENTRALIZED SYSTEM FOR MANAGING DATA FLOWS OF MOBILE DEVICES

В статье рассматривается модель распределенной автоматизированной системы информационного мониторинга в режиме реального времени в условиях нестационарной нагрузки. Приведена структура, описана математическая модель, представлен алгоритм и некоторые результаты исследований. The article discusses a model of a distributed automated information monitoring system in real time under non-stationary load conditions. The structure is given, a mathematical model is described, an algorithm and some research results are presented.

DEVELOPMENT OF A MATHEMATICAL MODEL FOR THE FUNCTIONING OF A MULTI-NODE DECENTRALIZED SYSTEM FOR MANAGING DATA FLOWS OF MOBILE DEVICES

В статье рассматривается модель распределения ресурсов сети, представленной множеством разнородных мобильных устройств, разнесенных в пространстве, обладающих возможностью динамического выхода из системы и перемещения в ней. Описана математическая модель и приведены результаты ее применения. The model of the distribution of network resources is discusses in the article. The network is represented by a multitude of heterogeneous mobile devices, spaced apart, with the ability to dynamically leaving the system and moving in it. A mathematical model is described and the results of its application are presented.

CONDITIONS VULNERABILITY IDENTIFICATION OF NATURAL AND TECHNICAL OBJECTS BASED ON LINEAR SPLINE INTERPOLATION OF INTERFACE TRAFFIC INTENSITY

The method of application of spline interpolation in solving the problems of identification of abnormal states (A-events) in information data flows and classification of the specified events in the control of natural and technical objects (PTO) is considered. The approach is based on the representation of the intensity of interface traffic by piecewise linear splines and implemented using a modeling stand. At the first stage, descriptions are generated and formed in the form of linear splines representing the states of controlled objects, one of which is subject to external disturbance. At the second stage, the generated descriptions of splines are used to assess discrepancies between the studied distributions and the influence of a number of factors on the reliability of decisions made using probabilistic modeling methods in the Anylogic environment.

Optimization of the Energy Consumption of Connected Objects

The IoT is a growing new approach that has been defined as a global network of devices and machines capable of reliably communicating with each other without human intervention. It is one of the essential technologies in any field, such as medicine and attracts great attention in the future. It is applied in several areas that have achieved success. However, the power and the addition of connected objects to technology is based on the fact that its objects can establish several tasks: communicate, analyze, process and manage data in a parallel manner, which is very difficult in terms of energy consumption. Therefore, the problems related to consumption slow down considerably the evolution and the fast deployment of this high technology.Therefore, it is necessary to create a new lightweight and robust mechanism, which ensures the minimization of the consumption of the objects and makes these objects efficient and less costly while being adapted to the capacities of objects and technologies.That is why our paper aims to address this significant problem and present the role of energy consumption, which is essential in deploying successful IoT products and services and presenting the IoT categories for applications. First, we propose a method that minimizes energy consumption and meets our need through three essential steps: firstly, to study the existing methods to minimize energy consumption. Next, based on these methods, we create a new concept using the data flows. Finally, we implement our solution in an intelligent parking lot to carry out our approach and describe our design steps and conclude with the result of our study and make an interpretation that summarizes our work.

Establishing an ad hoc COVID-19 mortality surveillance during the first epidemic wave in Belgium, 1 March to 21 June 2020

Background COVID-19-related mortality in Belgium has drawn attention for two reasons: its high level, and a good completeness in reporting of deaths. An ad hoc surveillance was established to register COVID-19 death numbers in hospitals, long-term care facilities (LTCF) and the community. Belgium adopted broad inclusion criteria for the COVID-19 death notifications, also including possible cases, resulting in a robust correlation between COVID-19 and all-cause mortality. Aim To document and assess the COVID-19 mortality surveillance in Belgium. Methods We described the content and data flows of the registration and we assessed the situation as of 21 June 2020, 103 days after the first death attributable to COVID-19 in Belgium. We calculated the participation rate, the notification delay, the percentage of error detected, and the results of additional investigations. Results The participation rate was 100% for hospitals and 83% for nursing homes. Of all deaths, 85% were recorded within 2 calendar days: 11% within the same day, 41% after 1 day and 33% after 2 days, with a quicker notification in hospitals than in LTCF. Corrections of detected errors reduced the death toll by 5%. Conclusion Belgium implemented a rather complete surveillance of COVID-19 mortality, on account of a rapid investment of the hospitals and LTCF. LTCF could build on past experience of previous surveys and surveillance activities. The adoption of an extended definition of ‘COVID-19-related deaths’ in a context of limited testing capacity has provided timely information about the severity of the epidemic.