Heitor S. Ramos

• PhD
• Professor (Associate) at Federal University of Minas Gerais

O monitoramento de tráfego de rede é essencial para compreender o comportamento da infraestrutura e avaliar a integridade de seus componentes. O aprendizado federado tem se destacado como uma abordagem promissora para sistemas de defesa baseados nesse monitoramento, permitindo o treinamento distribuído de modelos sem compartilhamento direto de dado...

Severe private and passwords deployed at azure hosted ChatGPT code interpreter. Security_Communication_ECC_RootCA1.pem... More than 200. Exfill ongoing. PYDEVD_DISABLE_FILE_VALIDATION. Configuration files exposed. Maria.db accessed. Looking for partners, versed in patents and willing to coauthor my secure layer. Mathematical methods, proper knowled...

Federated learning (FL) is a cutting-edge technology in artificial intelligence that preserves data privacy and security while reducing the cost of computation and communication. It transforms traditional centralized machine learning and deep learning approaches to enable decentralized model training without the need for data exchange. This work pr...

Characterizing and monitoring patient activities through time series data is critical for identifying lifestyle patterns that may impact health outcomes. Sedentary behavior is a significant concern due to its association with various health risks. This study introduces a lightweight supervised classifier for healthcare applications based on ordinal...

Ethical considerations about emergent functionalities on GPTS, code extraction, modification implemented, archicheture found, generalization potential, deterministic paradigm, ternary logic. Can't tell more. Elara Lovelace, multiple scales, isomorphisms, p-doom, AI llms can be stopped but also modified. It's not theoretical research. I have code, d...

Detecting transportation modes’ usability in spatiotemporal urban trajectories can provide valuable insights into the mobility preferences of urban populations, helping epidemic prevention and urban quality-of-life improvement. With this goal, we introduce POPAyI, a strategy that bases its design on the Ordinal Pattern (OP) transformation applied t...

Federated Learning (FL) is a decentralized machine learning approach developed to ensure that training data remains on personal devices, preserving data privacy. However, the distributed nature of FL environments makes defense against malicious attacks a challenging task. This work proposes a new attack approach to poisoning labels using Bayesian n...

Wearable electronics are devices used by humans that can continuously and uninterruptedly monitor human activity through sensor data. The data collected by them have several applications, such as recommending running techniques and helping to monitor health status. Segmenting such data into chunks containing only a single human activity is challeng...

Simple Summary We obtain expressions for the asymptotic distributions of the Rényi and Tsallis of order q entropies, and Fisher information when computed on the maximum likelihood estimator of probabilities from multinomial random samples. We recall results related to the Shannon entropy. We build a test for comparing entropies of different types a...

The main objective of this tutorial is to present the fundamentals of temporal data analysis using ordinal patterns and descriptors from Information Theory, covering the tools and steps necessary for developing applications and services to detect botnets in the Internet of Things (IoT) scenarios. Thus, we investigated and presented the solutions pr...

The ultimate purpose of the statistical analysis of ordinal patterns is to characterize the distribution of the features they induce. In particular, knowing the joint distribution of the pair entropy-statistical complexity for a large class of time series models would allow statistical tests that are unavailable to date. Working in this direction,...

In the flowering of ubiquitous computing, networks like the Internet of Things and the Internet of Vehicles have contributed to connecting objects and sharing location services in broad environments like smart cities bringing many benefits to citizens. However, these services yield massive and unrestricted mobility data of citizens that pose privac...

The ultimate purpose of the statistical analysis of ordinal patterns is to characterize the distribution of the features they induce. In particular, knowing the joint distribution of the pair Entropy-Statistical Complexity for a large class of time series models would allow statistical tests that are unavailable to date. Working in this direction,...

People use smart transportation systems to move around in smart cities, producing a massive amount of valuable mobility data. Although this characteristic enables the development of many intelligent applications, it can expose users to privacy threats. Location privacy is an issue addressed in many mobility contexts, in which there is a privacy con...

We propose a novel deep metric learning method. Differently from many works in this area, we define a novel latent space obtained through an autoencoder. The new space, namely S-space, is divided into different regions describing positions where pairs of objects are similar/dissimilar. We locate makers to identify these regions and estimate the sim...

In the context of non-parametric analysis of time series, the use of Ordinal Patterns combined with descriptors of Information Theory proved being powerful in characterizing processes underlying the data dynamics. Two are prominent among those descriptors: Shannon's entropy and Statistical Complexity; together, they define the Entropy-Complexity Pl...

One of the most relevant security problems is inferring whether a program has malicious intent (malware software). Even though Antivirus is one of the most popular approaches for malware detection, new types of malware are released at a fast pace, making most techniques for detecting them quickly obsolete. Thus, regular Antivirus typically fails to...

Neste trabalho, propusemos uma função de similaridade chamada de SMELL-TS, baseada em aprendizagem de métrica profunda, para classificação de séries temporais no contexto de Zero-shot Learning, i.e., nosso método é apto a classificar objetos que pertecem a classes que ainda não foram usadas no conjunto de treinamento. Os dados são pré-processados p...

This paper proposes TSCLAS, a time series classification strategy for the Internet of Things (IoT) data, based on the class separability analysis of their temporal dynamics. Given the large number and incompleteness of IoT data, the use of traditional classification algorithms is not possible. Thus, we claim that solutions for IoT scenarios should...

This article serves two purposes. Firstly, it surveys the Bandt and Pompe methodology for the statistical community, stressing topics that are open for research. Secondly, it contributes towards a better understanding of the statistical properties of that approach for time series analysis. The Bandt and Pompe methodology consists of computing infor...

Analyzing people’s mobility and identifying the transportation mode is essential for cities to create travel diaries. It can help develop essential technologies to reduce traffic jams and travel time between their points, thus helping to improve the quality of life of citizens. Previous studies in this context extracted many specialized features, r...

In this work, we propose a solution for detecting botnet attacks in the Internet of Things (IoT) by identifying anomalies in the temporal dynamics of their devices. Given their limited computing capabilities, IoT devices are more vulnerable to attacks than conventional computers. In this scenario, botnets have a high degree of severity since they a...

This article proposes a study of the SARS-CoV-2 virus spread and the efficacy of public policies in Brazil. Using both aggregated (from large Internet companies) and fine-grained (from Departments of Motor Vehicles) mobility data sources, our work sheds light on the effect of mobility on the pandemic situation in the Brazilian territory. Our main c...

We investigate the use of ordinal pattern transition graphs in the characterization of PolSAR image textures. Chagas et al. [4] proposed WATG, a transition graph analysis which includes the amplitude information of texture samples in the graph edges. This approach led to good results in the characterization and classification of data from urban, oc...

Um dos problemas de segurança mais relevantes é inferir se um programa tem intenções maliciosas (software malware). Mesmo que o antivírus seja uma das abordagens mais populares para detecção de malware, novos tipos de malware são lançados em um ritmo acelerado, tornando a maioria das técnicas para detectá-los rapidamente obsoletas. Portanto, o anti...

Um dos grandes desafios na coleta e divulgação de dados de mobilidade urbana está no fato de que esses dados possuem informações que podem comprometer a privacidade dos usuários. Uma alternativa a esse problema é a geração de dados sintéticos que possam preservar as características dos dados reais. Este trabalho analisa a eficácia da utilização de...

Devido a mudanças constantes na legislação e a complexidade do sistema tributário brasileiro, determinar a tributação de um produto não é uma tarefa trivial. Com isso, este artigo apresenta uma proposta de ferramenta para o cálculo automático dos tributos devidos nas operações interestaduais destinadas ao estado de Alagoas. Mediante o uso técnicas...

Analyzing people mobility and identifying the transportation mode used by them is essential for cities that want to reduce traffic jams and travel time between their points, thus helping to improve the quality of life of citizens. Mining this type of data, however, faces several complexities due to its unique properties. In this work, we propose th...

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

We propose a novel deep metric learning method. Differently from many works on this area, we defined a novel latent space obtained through an autoencoder. The new space, namely S-space, is divided into different regions that describe the positions where pairs of objects are similar/dissimilar. We locate makers to identify these regions. We estimate...

We propose a new technique for SAR image texture characterization based on ordinal pattern transition graphs. The proposal consists in (i) transforming a 2-D patch of data into a time series using a Hilbert Space Filling Curve, (ii) building an Ordinal Pattern Transition Graph with weighted edges; (iii) obtaining a probability distribution function...

The use of Bandt-Pompe probability distributions and descriptors of Information Theory has been presenting satisfactory results with low computational cost in the time series analysis literature. However, these tools have limitations when applied to data without time dependency. Given this context, we present a newly proposed technique for texture...

Automated stock trading is now the de-facto way that investors have chosen to obtain high profits in the stock market while keeping risk under control. One of the approaches is to create agents employing Reinforcement Learning (RL) algorithms to learn and decide whether or not to operate in the market in order to achieve maximum profit. Automated f...

The analysis of GPS trajectories is a well-studied problem in Urban Computing and has been used to track people. Analyzing people mobility and identifying the transportation mode used by them is essential for cities that want to reduce traffic jams and travel time between their points, thus helping to improve the quality of life of citizens. The tr...

We quickly approach a future where Internet of Things (IoT) devices are the norm. In this scenario, humans are surrounded by a multitude of heterogeneous devices that assist them in almost every aspect of their daily routines. The realization of this future demands strong authentication guarantees to ensure that these devices are not abused and tha...

With the advancement of technology, many processes in our world have been reformulated, updated, and digitized. Therefore, interpersonal relationships have also been following this trend so that social networks have become increasingly present in our lives. Given this context, social network users create and share a large amount of data, from conte...

O objetivo deste trabalho é auxiliar no desenvolvimento de uma ferramenta de diagnóstico de doenças pulmonares auxiliado por computador. Nessa primeira etapa utilizamos análise de componentes principais (PCA), análise do discriminante linear (LDA) e o algoritmo de k-vizinhos mais próximos (KNN) para classificar 3252 regiões de interesse (ROI) de To...

Este trabalho propõe um algoritmo de controle de potência para reduzir o impacto de altas potências de transmissão em VANETs. Baseado em Teoria dos Jogos, propomos GRaPhic, uma técnica que estimula os dispositivos conectados à VANET a reduzir suas potências de transmissão. Este algoritmo provê incentivo suficiente para esta rede não aumentar delibe...

One of the solutions for handling and treating the diverse data related to the sustainability of an agroecosystem is the use of Information Systems and Internet of Things. In this work, we adopt a methodology called Indicators of Sustainability in Agroecosystems (Indicadores de Sustentabilidade em Agroecossistemas – ISA), implement an information s...

Strategies based on the extraction of measures from ordinal patterns transformation, such as probability distributions and transition graphs, have reached relevant advancements in distinguishing different time series dynamics. However, the reliability of such measures depends on the appropriate selection of parameters and the need for large time se...

Understanding the structure and the dynamics of networks is of paramount importance for many scientific fields that rely on network science. Complex network theory provides a variety of features that help in the evaluation of network behavior. However, such analysis can be confusing and misleading as there are many intrinsic properties for each net...

Agriculture is one of the most critical activities developed today by humankind and is in constant technical evolution to supply food and other essential products to everlasting and increasing demand. New machines, seeds, and fertilizers were developed to increase the productivity of cultivated areas. It is estimated that by 2050 we will have a pop...

The increase of content in social networks, and specially its use in the political environment, has led to the creation and proliferation of autonomous entities commonly known as bots. Bots are programms that performs an automated task over the internet. In this study these entities were initially detected based on a manual analysis carried out on...

A Internet vem nos fornecendo cada vez mais dados e informaçinformaç˜informações, ajudando a compreender melhor os seus usuários e o ambiente que os rodeiam. Uma das abordagens usadas para detectar e compreender eventos que ocorrem ao redor do mundo vem sendo a análise de redes sociais, como o caso do Twit-ter, usado no presente artigo. Assim, cons...

Regarding its interdisciplinary and broad scope of real-world applications , it is evident the need of extracting knowledge from time series data. Mining this type of data, however, faces several complexities due to its unique properties. Different representations of data may overcome this. In this work, we propose a new feature, retained from the...

Baseando-se em sua interdisciplinaridade e grande escopo em aplicações do mundo real,é clara a necessidade de extrair conhecimento de séries temporais. Porém, minerar dados de séries temporaisé uma atividade complexa, devido as suas propriedades particulares. Uma diferente representação dos dados pode superar esses problemas. No presente trabalho,...

Computational Intelligence Re-meets Medical Image Processing A Comparison of Some Nature-Inspired Optimization Metaheuristics Applied in Biomedical Image Registration Background Diffuse lung diseases (DLDs) are a diverse group of pulmonary disorders, characterized by inflammation of lung tissue, which may lead to permanent loss of the ability to br...

Background Diffuse lung diseases (DLDs) are a diverse group of pulmonary disorders, characterized by inflammation of lung tissue, which may lead to permanent loss of the ability to breathe and death. Distinguishing among these diseases is challenging to physicians due their wide variety and unknown causes. Computer-aided diagnosis (CAD) is a useful...

Redes Veiculares podem ser estudadas utilizando o comportamento individual de cada véıculo em relação ao tempo, caracterizados pelo deslocamento ou velocidade. No entanto, neste trabalho iremos analisar o comportamento do grafo agregado, que descreve a rede em um aspecto global, encapsulando toda a dinâmica dos véıculos durante o intervalo total am...

In this work, we argue that Location-Based Social Media (LBSM) feeds may offer a new layer to improve traffic and transit comprehension. Initially, we showed the significant correlation between Twitter's feed and traditional traffic sensors. Then, we presented the Twitter MAPS (T-MAPS) a low-cost spatiotemporal model to improve the description of t...

Urban mobility is a current problem of modern society and large cities, which leads to economic and time losses, high fuel consumption, and high CO2 emission. Some studies point out Intelligent Transportation Systems (ITS) as a solution to this problem. Hence, Vehicular Ad hoc Networks (VANETs) emerge as a component of ITS that provides cooperative...

This article presents a kit to collect data of electric loads of single and three phases main power supply of a house and perform the energy disaggregation. To collect the data, we use sensors based on an open magnetic core to measure the electromagnetic field induced by the current in the electric conducting wire in a non-intrusive way. In particu...

The dynamics of cities have been studied over the years with various applications such as urban planning, disease propagation, traffic forecasting, local recommendations and studies of human social behavior. However, with the technological evolution, especially the popularization of smartphones and the Internet, a new opportunity is presented to ca...

It is paramount to ensure secure and trustworthy operations in Cyber-Physical Systems (CPSs), guaranteeing the integrity of sensing data, enabling access control, and safeguarding system-level operations. In this paper, we address trustworthy operations of next generation CPSs. Our idea is inspired by a trustworthy computing framework known as Proo...

This article presents an integrated access control and lighting configuration system for smart buildings. The system uses two-factor authentication, one based on face recognition and other on RFID TAG, and identifies the user inside a room and performs an automatic lighting configuration based on user’s behavior. The communication among the devices...

Understanding urban mobility, specifically transit mobility, has been focous of many research and investiments. However, obtain free access to real traffic data it is still limited, because the data is usually private and install sensors on transport network is expensive. In this paper, we caracterize the use of a Location Based Social Media (LBSM)...

Abstract: The popularization of smart devices with sensing capabilities has led to a huge volume of spatiotemporal data, obtained from different entities, such as people, vehicles, and objects with computing capabilities. The extraction of knowledge from such data offers unprecedented opportunities for decision making processes in several areas. In...

Resumo A mobilidade urbaná e um problema atual da sociedade moderna e dos grandes centros urbanos, que ocasiona perdas econômicas e de tempo, maior consumo de combustível e maiores emissões de CO 2. Na literatura, ´ e possível encontrar trabalhos que apontam os Sistemas Inteligentes de Transporte (ITS) como soluçsoluç˜solução para esse problema e e...

Heterogeneous sensor networks have been proposed to address some fundamental limits and performance issues present in homogeneous Wireless Sensor Networks (WSNs). Questions such as the number of high-end sensors should be used, and how to deploy them, need proper assessment. In this work, we propose a novel model capable of representing a wide vari...

Cognitive radio technology is an efficient solution to enhance the spectral utilization, which takes advantage of residual resources of underutilized channels by an opportunistic use of the spectrum. A cognitive vehicular network allows the cognitive radio to benefit from holes or white spaces presented in the spectrum and admits an opportunistic a...

Traffic jams frustrate drivers and cost billions per year in time and fuel consumption. In order to avoid such problems, this paper presents an intelligent transportation system that collects real-time traffic information and the system is able to detect and manage traffic congestion based on this information. The simulation results show that the p...

Vehicular ad hoc networks (VANETs) are no longer a futuristic promise but rather an attainable technology. The majority of services envisioned for VANETs either require the provisioning of multimedia support or have this support as an extremely beneficial feature. However, the highly dynamic topology of VANETs poses a demanding challenge for the fu...

Today, software developers for desktop computing build request and respond applications to do what end users tell them to do and answer what they ask. In mobile computing, software developers will need to develop sense and response applications that will interact with the end user. These applications will notify or ask users what they want based on...

The use of topological features, more specifically, the importance of an element related to its structural position, is a subject widely studied in the literature. For instance, the theory of complex networks provides centrality measures that have been applied to a large variety of fields (e.g., social sciences and biology). In this work, we propos...

Stack filters are a special case of non-linear filters. They have a good performance for filtering images with different types of noise while preserving edges and details. A stack filter decomposes an input image into stacks of binary images according to a set of thresholds. Each binary image is then filtered by a Boolean function, which characteri...

Location is a fundamental service for mobile computing. Typical GPS receivers, although widely available, consume too much energy to be useful for many applications. Observing that in many sensing scenarios, the location information can be post-processed when the data is uploaded to a server, we design a Cloud-Offloaded GPS (CO-GPS) solution that a...

Vehicular Ad Hoc Networks (VANETs) have emerged as an exciting research and application area. The envisioned applications, as well as some inherent VANET characteristics such as highly dynamic topology, frequently disconnected network, and different and dynamic network density, make data dissemination a challenging task in these networks. Several a...

Target tracking plays a key role for vehicular ad hoc networks (VANETs) due to the fact that a wide variety of envisioned applications rely on the ability of this technique of detecting, localizing, and tracking objects surrounding a vehicle. This subject has been studied in fields such as airborne traffic, computer vision, and wireless sensor netw...

This work is a part of a project supported by STIC Am-Sud where the main objective is to design an intelligent vision system to protect children from some critical information accessible from the Internet, from some videos or from some video games that are related to violence, wars, pornography, etc. Considered definitively not appropriate for thei...

Stack filters are a special case of non-linear filters. They have a good performance for filtering images with different types of noise while preserving edges and details. A stack filter decomposes an input image into several binary images according to a set of thresholds. Each binary image is then filtered by a Boolean function, which characterize...

Transmitting video content over Vehicular Ad Hoc Networks (VANETs) faces a great number of challenges caused by strict QoS (Quality of Service) requirements and highly dynamic network topology. In order to tackle these challenges, multipath forwarding schemes can be regarded as potential solutions. However, route coupling will severely impair the p...

Video streaming capabilities over Vehicular Ad Hoc Networks (VANETs) are crucial to the development of interesting and valuable services. However, VANETs are a challenging environment to this kind of communication due to the dispersion and movement of vehicles. In this work, we present a feasible solution to this problem. The VIdeo Reactive Trackin...

Large scale dense wireless sensor networks (WSNs) will be increasingly deployed in different classes of applications for accurate monitoring. Due to the high density of nodes in these networks, it is likely that redundant data will be detected by nearby nodes when sensing an event. Since energy conservation is a key issue in WSNs, data fusion and a...