Reducing false positives in anomaly detectors through fuzzy alert aggregation

In this paper we focus on the aggregation of IDS alerts, an important component of the alert fusion process. We exploit fuzzy measures and fuzzy sets to design simple and robust alert aggregation algorithms. Exploiting fuzzy sets, we are able to robustly state whether or not two alerts are “close in time”, dealing with noisy and delayed detections. A performance metric for the evaluation of fusion systems is also proposed. Finally, we evaluate the fusion method with alert streams from anomaly-based IDS.     

FreesoundVR: soundscape composition in virtual reality using online sound repositories

Virtual Reality - The intersection between sound and music computing and Virtual Reality (VR) has grown significantly over the past decades, amounting to an established area of research today....     

Plasmon hybridization engineering in self-organized anisotropic metasurfaces

Nano Research - The engineering of self-organized plasmonic metasurfaces is demonstrated using a maskless technique with defocused ion-beam sputtering and kinetically controlled deposition. The...     

Integratable non-clogging microconcentrator based on counter-flow principle for continuous enrichment of CaSki cells sample

This study addresses the need to reduce the risk of clogging when preparing samples for cell concentration, i.e., the CaSki Cell-lines (epidermoid cervical carcinoma cells). Aiming to develop a non-clogging microconcentrator, we proposed a new counter-flow concentration unit characterized by the directions of penetrating flows being at an obtuse angle to the main flow, due to employment of streamlined turbine blade-like micropillars. Based on the optimization results of the counter-flow unit profile, a fractal arrangement for the counter-flow concentration unit was developed. A counter-flow microconcentrator chip was then designed and fabricated, with both the processing layer and collecting layer arranged in terms of the honeycomb structure. Visualized experiments using CaSki cell samples on the microconcentrator chip demonstrated that no cell-clogging phenomena occurred during the test and that no cells were found in the final filtrate. The test results show an excellent concentration performance for the microconcentrator chip, while a concentrating ratio of >4 with the flow rate being below 1.0 ml/min. As only geometrical structure is employed in the passive device, the counter-flow microconcentrator can be easily integrated into advanced microfluidic systems. Owing to the merit of non-clogging and continuous processing ability, the counter-flow microconcentrator is not only suitable for the sample preparation within biomedical field, but also applicable in water-particle separation.     

Computational study on the interaction of a ring-hydroxylating dioxygenase from Sphingomonas CHY-1 with PAHs

The massive computational resources available in the framework of a grid paradigm approach represent an emerging tool in the bioinformatics field. In this paper, we used the above approach in the rapid determination of the interactions between the ring-hydroxylating dioxygenase, comprised six enzymatic subunits, and polycyclic aromatic hydrocarbons (PAHs) in their optimal positions. The results were obtained by simulating enzyme dynamics at 300 K through molecular dynamics calculations. For the first time, the equilibrated structure of the dioxygenase revealed a network of channels throughout the enzyme that were sufficiently large to allow a flow of small ions or molecules from the inner core of the complex to its exterior surface. The ring-hydroxylating dioxygenase was able to interact with some of the studied PAHs. Additionally, not only the number of aromatic rings but also the PAH shape were critical in predicting the ability of the dioxygenase to interact with these types of molecules. Docking calculations shed light on a new possible binding site that is far from the enzymatic one, which is potentially interesting in considering the stability of the enzyme itself.     

Minutia Cylinder-Code: a new representation and matching technique for fingerprint recognition

In this paper, we introduce the Minutia Cylinder-Code (MCC): a novel representation based on 3D data structures (called cylinders), built from minutiae distances and angles. The cylinders can be created starting from a subset of the mandatory features (minutiae position and direction) defined by standards like ISO/IEC 19794-2 (2005). Thanks to the cylinder invariance, fixed-length, and bit-oriented coding, some simple but very effective metrics can be defined to compute local similarities and to consolidate them into a global score. Extensive experiments over FVC2006 databases prove the superiority of MCC with respect to three well-known techniques and demonstrate the feasibility of obtaining a very effective (and interoperable) fingerprint recognition implementation for light architectures.     

Stochastic algorithms for robustness of control performances

In recent years, there has been a growing interest in developing statistical learning methods to provide approximate solutions to “difficult” control problems. In particular, randomized algorithms have become a very popular tool used for stability and performance analysis as well as for design of control systems. However, as randomized algorithms provide an efficient solution procedure to the “intractable” problems, stochastic methods bring closer to understanding the properties of the real systems. The topic of this paper is the use of stochastic methods in order to solve the problem of control robustness: the case of parametric stochastic uncertainty is considered. Necessary concepts regarding stochastic control theory and stochastic differential equations are introduced. Then a convergence analysis is provided by means of the Chernoff bounds, which guarantees robustness in mean and in probability. As an illustration, the robustness of control performances of example control systems is computed.     

On the collective sort problem for distributed tuple spaces

In systems coordinated with a distributed set of tuple spaces, it is crucial to assist agents in retrieving the tuples they are interested in. This can be achieved by sorting techniques that group similar tuples together in the same tuple space, so that the position of a tuple can be inferred by similarity. Accordingly, we formulate the collective sort problem for distributed tuple spaces, where a set of agents is in charge of moving tuples up to a complete sort has been reached, namely, each of the N tuple spaces aggregate tuples belonging to one of the N kinds available. After pointing out the requirements for effectively tackling this problem, we propose a self-organizing solution resembling brood sorting performed by ants. This is based on simple agents that perform partial observations and accordingly take decisions on tuple movement. Convergence is addressed by a fully adaptive method for simulated annealing, based on noise tuples inserted and removed by agents on a need basis so as to avoid sub-optimal sorting. Emergence of sorting properties and scalability are evaluated through stochastic simulations.