In recent years, along with the extraordinary diffusion of Internet and a growing need for personal verification in many daily applications, automatic signature is being considered renewed interest. This paper presents state art verification. It addresses most valuable results obtained so far highlights profitable directions research to date. includes comprehensive bibliography more than 300 selected references as an aid researchers working field.

This work aims to show how manage heterogeneous information and data coming from real datasets that collect physical, biological, sensory values. As productive companies—public or private, large small—need increasing profitability with costs reduction, discovering appropriate ways exploit are continuously recorded made available can be the right choice achieve these goals. The agricultural field is only apparently refractory digital technology “smart farm” model increasingly widespread by...

As the occurrence of Denial Service and Distributed (DoS/DDoS) attacks increases, demand for effective defense mechanisms increases. Recognition such anomalies in computer network is commonly performed through network-based intrusion detection prevention systems (NIDPSs). Although NIDPSs allow interception all known attacks, they are not robust to continuing variation over time DoS/DDoS anomalies. The machine learning (ML) paradigm provides algorithms that can effectively reduce concept...

Machine learning techniques are tailored to build intelligent systems support clinicians at the point of care. In particular, they can complement standard clinical evaluations for assessment early signs and manifestations Parkinson’s disease (PD). Patients suffering from PD typically exhibit impairments previously learned motor skills, such as handwriting. Therefore, handwriting be considered a powerful marker develop automatized diagnostic tools. this paper, we investigated if which extent...

Automatic traffic flow classification is useful to reveal road congestions and accidents. Nowadays, roads highways are equipped with a huge amount of surveillance cameras, which can be used for real-time vehicle identification, thus providing estimation. This research provides comparative analysis state-of-the-art object detectors, visual features, models implement state estimations. More specifically, three different detectors compared identify vehicles. Four machine learning techniques...

The 0-day attack is a cyber-attack based on vulnerabilities that have not yet been published. detection of anomalous traffic generated by such attacks vital, as it can represent critical problem, both in technical and economic sense, for smart enterprise any system largely dependent technology. To predict this kind attack, one solution be to use unsupervised machine learning approaches, they guarantee the anomalies regardless their prior knowledge. It also essential identify unknown...

A technique for number comparison in the residue system is presented, and its theoretical validity proved. The proposed solution based on using a diagonal function to obtain magnitude order of numbers. In first approach computed suitable extra modulus. final implementation modulus has been inserted set moduli system, avoiding redundancy. compared with other approaches.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Recently, research in handwritten signature verification has been considered with renewed interest. In fact, the age of e-society, still represents an extraordinary means for personal and possibility using automatic a range applications is becoming reality. This paper focuses on some most remarkable aspects field highlights recent directions. A list selected publications also provided interested researchers.

This paper presents a new approach for online signature verification that exploits the potential of local stability information in handwritten signatures. Different from previous models, this classifies using multidomain strategy. A is first split into different segments based on model signer. Then, according to model, each segment, most profitable domain representation purposes detected. In stage, authenticity segment unknown evaluated representation. The then determined by combining...

In recent years, with the widespread of Internet and digitized processing multi-script documents worldwide, script identification techniques have become more important in pattern recognition field. Script concerns methods for identifying different scripts multi-lingual, documents. This paper presents a comprehensive overview on research activities field focuses most valuable results obtained so far. The vital processes are addressed detail: discriminating methods, features extraction (local...

Secure transmission of medical images and data is essential in healthcare systems, both telemedicine AI approaches. The compromise could affect patient privacy the accuracy diagnosis. Digital watermarking embeds into a non-significant image before to ensure visual security. However, it vulnerable white-box attacks because embedded can be extracted by an attacker that knows system’s operation does not authenticity transmission. A visually secure encryption scheme for fingerprint-based...

Recognition of known malicious patterns through signature-based systems is unsuccessful against malware for which no signature exists to identify them. These include not only zero-day but also software able self-replicate rewriting its own code leaving unaffected execution, namely metamorphic malware. YARA a popular analysis tool that uses the so-called YARA-rules, are built match contents within files or network packets analyzed by an Anti-Virus engine. Sometimes such content expressed in...

Process mining applications in healthcare is a field widely investigated the last years. Its diffusion driven by increasing digitalization and availability of large quantities clinical data, enabling hospitals, clinics, other organizations to optimize workflows, reduce operational costs, improve asset management. The importance process lies its potential identify inefficiencies processes, standardize practices, support evidence-based decisions and, general, quality care provided. article...

The widespread use of artificial intelligence deep neural networks in fields such as medicine and engineering necessitates understanding their decision-making processes. Current explainability methods often produce inconsistent results struggle to highlight essential signals influencing model inferences. This paper introduces the Evolutionary Independent Deterministic Explanation (EVIDENCE) theory, a novel approach offering deterministic, model-independent method for extracting significant...