45 research outputs found
Sensors Characterization for a Calibration-Free Connected Smart Insole for Healthy Ageing
The design of technological aids to assist older adults in their ageing process and to ensure proper attendance and care, despite the decreasing percentage of young people in the demographic profiles of many developed countries, requires the proper selection of sensing components, in order to come up with devices that can be easily used and integrated into everyday life. This paper addresses the metrological characterization of pressure sensors to be inserted into smart insoles aimed at monitoring the older adult’s physical activity levels. Two types of sensing elements are evaluated and a recommendation provided, based on the main requirement of designing a calibration-free insole: in this case, the pressure sensor should act as a switch, and the FSR 402 Short sensing element appears to be the proper solution to adopt
DarkVec: automatic analysis of darknet traffic with word embeddings
Darknets are passive probes listening to traffic reaching IP addresses that host no services. Traffic reaching them is unsolicited by nature and often induced by scanners, malicious senders and misconfigured hosts. Its peculiar nature makes it a valuable source of information to learn about malicious activities. However, the massive amount of packets and sources that reach darknets makes it hard to extract meaningful insights. In particular, multiple senders contact the darknet while performing similar and coordinated tasks, which are often commanded by common controllers (botnets, crawlers, etc.). How to automatically identify and group those senders that share similar behaviors remains an open problem.
We here introduce DarkVec, a methodology to identify clusters of senders (i.e., IP addresses) engaged in similar activities on darknets. DarkVec leverages word embedding techniques (e.g., Word2Vec) to capture the co-occurrence patterns of sources hitting the darknets. We extensively test DarkVec and explore its design space in a case study using one month of darknet data. We show that with a proper definition of service, the generated embeddings can be easily used to (i) associate unknown senders' IP addresses to the correct known labels (more than 96% accuracy), and (ii) identify new attack and scan groups of previously unknown senders. We contribute DarkVec source code and datasets to the community also to stimulate the use of word embeddings to automatically learn patterns on generic traffic traces
i-DarkVec: Incremental Embeddings for Darknet Traffic Analysis
Darknets are probes listening to traffic reaching IP addresses that host no services. Traffic reaching a darknet results from the actions of internet scanners, botnets, and possibly misconfigured hosts. Such peculiar nature of the darknet traffic makes darknets a valuable instrument to discover malicious online activities, e.g., identifying coordinated actions performed by bots or scanners. However, the massive amount of packets and sources that darknets observe makes it hard to extract meaningful insights, calling for scalable tools to automatically identify and group sources that share similar behaviour.
We here present i-DarkVec, a methodology to learn meaningful representations of Darknet traffic. i-DarkVec leverages Natural Language Processing techniques (e.g., Word2Vec) to capture the co-occurrence patterns that emerge when scanners or bots launch coordinated actions. As in NLP problems, the embeddings learned with i-DarkVec enable several new machine learning tasks on the darknet traffic, such as identifying clusters of senders engaged in similar activities.
We extensively test i-DarkVec and explore its design space in a case study using real darknets. We show that with a proper definition of services, the learned embeddings can be used to (i) solve the classification problem to associate unknown sources’ IP addresses to the correct classes of coordinated actors and (ii) automatically identify clusters of previously unknown sources performing similar attacks and scans, easing the security analyst’s job. i-DarkVec leverages a novel incremental embedding learning approach that is scalable and robust to traffic changes, making it applicable to dynamic and large-scale scenarios
Cross-network Embeddings Transfer for Traffic Analysis
Artificial Intelligence (AI) approaches have emerged as powerful tools to improve traffic analysis for network monitoring and management. However, the lack of large labeled datasets and the ever-changing networking scenarios make a fundamental difference compared to other domains where AI is thriving. We believe the ability to transfer the specific knowledge acquired in one network (or dataset) to a different network (or dataset) would be fundamental to speed up the adoption of AI-based solutions for traffic analysis and other networking applications (e.g., cybersecurity). We here propose and evaluate different options to transfer the knowledge built from a provider network, owning data and labels, to a customer network that desires to label its traffic but lacks labels. We formulate this problem as a domain adaptation problem that we solve with embedding alignment techniques and canonical transfer learning approaches. We present a thorough experimental analysis to assess the performance considering both supervised (e.g., classification) and unsupervised (e.g., novelty detection) downstream tasks related to darknet and honeypot traffic. Our experiments show the proper transfer techniques to use the models obtained from a network in a different network. We believe our contribution opens new opportunities and business models where network providers can successfully share their knowledge and AI models with customers
Zebrafish caudal fin as a model to investigate the role of probiotics in bone regeneration
: Probiotics are live microorganisms that confer several beneficial effects to the host, including enhancement of bone mineralization. However, probiotic action on bone regeneration is not well studied and therefore we analysed various effects of probiotic treatment on the caudal fin regeneration of zebrafish. Morphological analysis revealed an increased regenerated area with shorter and thicker lepidotrichia segments after probiotic treatment. Fourier transform infrared spectroscopy imaging analysis highlighted the distribution of phosphate groups in the regenerated fins and probiotic group showed higher amounts of well-crystallized hydroxyapatite. At the midpoint (5 days post amputation) of regeneration, probiotics were able to modulate various stages of osteoblast differentiation as confirmed by the upregulation of some key marker genes such as runx2b, sp7, col10a1a, spp1 and bglap, besides suppressing osteoclast activity as evidenced from the downregulation of ctsk. Probiotics also caused an enhanced cell cycle by regulating the expression of genes involved in Retinoic acid (rarga, cyp26b1) and Wnt/β-catenin (ctnnb1, ccnd1, axin2, sost) signaling pathways, and also modulated phosphate homeostasis by increasing the entpd5a levels. These findings provide new outlooks for the use of probiotics as a prophylactic treatment in accelerating bone regeneration and improving skeletal health in both aquaculture and biomedical fields
Aspects of Reproductive Biology of the European Hake (Merluccius merluccius) in the Northern and Central Adriatic Sea (GSA 17-Central Mediterranean Sea)
The study focused on the macroscopic, histological, and biometric analysis of European hake females in GSA 17 (Central-North Adriatic Sea). From 2013 to 2015, 976 females were collected and analyzed monthly. Though females in spawning conditions were found during the whole year, the trend of GSI showed a peak of the reproductive season from April to July in 2014 and 2015. HSI and Kn reached the highest values in September, after the spawning peaks. In 2013, the trend of these indices did not highlight an evident peak, probably due to an adverse event that occurred in the previous winter in the Adriatic shelf. The length at first maturity (L50) was estimated by macroscopic and histological approaches, resulting in 30.81 cm for the macroscopical length and 33.73 cm for the histological length; both values are higher than the current catching legal size. For the first time in this area, batch and relative fecundity were estimated. Relative fecundity was similar to the Mediterranean and the Atlantic stocks, whereas batch fecundity values were lower compared to other fishing grounds. Overall, the analysis of reproductive parameters plays a fundamental role in the sustainable management of this resource in an area as overfished as the Central-North Adriatic Sea
Recurrence of non-hydropic sudden sensorineural hearing loss (SSNHL): a literature review
Sudden Sensorineural Hearing Loss (SSNHL) is typically defined as the acute onset (less than 3 days) of a perceptive hearing loss of more than 30dB over at least three contiguous frequencies on pure tone audiometry. The exact incidence of SSNHL is uncertain, since many patients have a rapid and spontaneous resolution of symptoms and therefore don’t reach medical attention. Estimate of incidence ranges from 5 to 20 per 100.000 individuals, and bilateral involvement is very rare; it increases in the older patients (>65 yo)(77 per 100.000) the in younger population (<18 yo)(11 per 100.000) [3]. The true incidence of paediatric SSNHL is not established in literature; 40% of examined child with SSNHL, showed anatomic abnormaliti
Cerebrospinal Fluid Leak During Stapes Surgery: The Importance of Temporal Bone CT Reconstructions in Oblique Anatomically Oriented Planes.
Stapes gusher is a massive flow of perilymph and cerebrospinal fluid leak that fills the middle ear immediately after surgical opening of the labyrinth, such as during stapedectomy. Stapes gusher usually occurs as the result of a congenital malformation that causes an abnormal communication between the perilymphatic space and the subarachnoid space involving the internal auditory canal or the cochlear duct. To date, the potential risk of stapes gusher cannot be assessed preoperatively, as there are not pathognomonic signs suggestive of this complication. However, high-resolution computed tomography scan (HRCT) of the temporal bone can provide information that may help recognizing patients at risk. Recently, an anatomic evaluation of the inner ear with oblique reformation at HRCT has been described. This reformation offers a new and more detailed topographic vision of temporal bone structures compared to the classic axial and coronal planes and may help identifying anatomical alterations otherwise not visible. In this article, we present a case of stapes gusher and the role of preoperative HRCT with oblique reformation in its prevention
Comparison of different oval window sealing materials in stapes surgery: systematic review and meta-analysis
To compare the efficacy and safety characteristics of different materials used for oval window sealing during stapedotomy