MTDeep: Boosting the Security of Deep Neural Nets Against Adversarial Attacks with Moving Target Defense

Present attack methods can make state-of-the-art classification systems based on deep neural networks misclassify every adversarially modified test example. The design of general defense strategies against a wide range of such attacks still remains a challenging problem. In this paper, we draw inspiration from the fields of cybersecurity and multi-agent systems and propose to leverage the concept of Moving Target Defense (MTD) in designing a meta-defense for 'boosting' the robustness of an ensemble of deep neural networks (DNNs) for visual classification tasks against such adversarial attacks. To classify an input image, a trained network is picked randomly from this set of networks by formulating the interaction between a Defender (who hosts the classification networks) and their (Legitimate and Malicious) users as a Bayesian Stackelberg Game (BSG). We empirically show that this approach, MTDeep, reduces misclassification on perturbed images in various datasets such as MNIST, FashionMNIST, and ImageNet while maintaining high classification accuracy on legitimate test images. We then demonstrate that our framework, being the first meta-defense technique, can be used in conjunction with any existing defense mechanism to provide more resilience against adversarial attacks that can be afforded by these defense mechanisms. Lastly, to quantify the increase in robustness of an ensemble-based classification system when we use MTDeep, we analyze the properties of a set of DNNs and introduce the concept of differential immunity that formalizes the notion of attack transferability.Comment: Accepted to the Conference on Decision and Game Theory for Security (GameSec), 201

Teaching intervention to enhance HIV infection awareness in a biomedical science degree

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Condom use remains the predominant prophylactic intervention to control rates of human immunodeficiency virus (HIV) infection. However, chemoprophylactic strategies, which involve pre-exposure prophyaxis (PrEP) and post-exposure prophyaxis (PEP), have emerged as appropriate prevention tools to minimise and prevent future infections. Different studies have indicated that PrEP can prevent new HIV infections among men who have sex with men when used daily or event-based, and it is also effective with heterosexuals and people who inject drugs. However, appropriate education is needed as recent reports have observed a decline in adherence to PrEP over time, particularly in young adults, which will impact on the effectiveness of PrEP. Thus, we created a brief educational short intervention (3 hours) to increase the awareness of HIV with second year BMedSci Medical Science (Hons) students at De Montfort University (DMU, UK) in 2016/17 (Peña-Fernández et al., 2017). Briefly, BMedSci students tailored a community-centred intervention programme to reduce HIV infection rates following evidence-based public health methodology. 92% indicated an acquisition of knowledge for preventing HIV transmission and tools to fight this disease. However, BMedSci students also showed a lack of knowledge of preventative measures (PrEP and PEP), routes of transmission and appropriate screening. We implemented a similar teaching strategy with BSc Biomedical Science (BMS) students enrolled in the level 4 module of Basic Microbiology in 2017/18, but limited to two hours: one-hour lecture and one hour workshop in which different HIV prevention strategies were discussed and analysed by students. BMS students were also provided with an overview about the Joint United Nations Programme on HIV/AIDS (UNAIDS) 90:90:90 targets in the UK (2016). In a similar way as with the BMedSci cohort, BMS students showed little awareness about PEP/PrEP, specifically knowledge about what are they/how they work, access and usage. This teaching intervention was well-received by students according to the feedback provided in the final module level feedback. BMS participants (n=27 out of 187 students) indicated that they enjoyed the session and suggested a practical session and the introduction of case studies to enhance the teaching intervention. We are developing a virtual clinical case study on HIV following recent successful experiences in the development and introduction of these novel learning strategies and have performed small modifications in the delivery of this workshop for 2018/19 to increase engagement and interaction. In conclusion, we consider that similar short education interventions that specifically target HIV chemoprophylaxis would be needed in any degree to prevent the decline in adherence to PrEP over time observed in young adults and reduce PEP/PrEP stigma and other barriers which could impede their access

CentralNet: a Multilayer Approach for Multimodal Fusion

This paper proposes a novel multimodal fusion approach, aiming to produce best possible decisions by integrating information coming from multiple media. While most of the past multimodal approaches either work by projecting the features of different modalities into the same space, or by coordinating the representations of each modality through the use of constraints, our approach borrows from both visions. More specifically, assuming each modality can be processed by a separated deep convolutional network, allowing to take decisions independently from each modality, we introduce a central network linking the modality specific networks. This central network not only provides a common feature embedding but also regularizes the modality specific networks through the use of multi-task learning. The proposed approach is validated on 4 different computer vision tasks on which it consistently improves the accuracy of existing multimodal fusion approaches

Beyond One-hot Encoding: lower dimensional target embedding

Target encoding plays a central role when learning Convolutional Neural Networks. In this realm, One-hot encoding is the most prevalent strategy due to its simplicity. However, this so widespread encoding schema assumes a flat label space, thus ignoring rich relationships existing among labels that can be exploited during training. In large-scale datasets, data does not span the full label space, but instead lies in a low-dimensional output manifold. Following this observation, we embed the targets into a low-dimensional space, drastically improving convergence speed while preserving accuracy. Our contribution is two fold: (i) We show that random projections of the label space are a valid tool to find such lower dimensional embeddings, boosting dramatically convergence rates at zero computational cost; and (ii) we propose a normalized eigenrepresentation of the class manifold that encodes the targets with minimal information loss, improving the accuracy of random projections encoding while enjoying the same convergence rates. Experiments on CIFAR-100, CUB200-2011, Imagenet, and MIT Places demonstrate that the proposed approach drastically improves convergence speed while reaching very competitive accuracy rates.Comment: Published at Image and Vision Computin

Metabarcoding of insect-associated fungal communities: a comparison of internal transcribed spacer (ITS) and large-subunit (LSU) rRNA markers

Full taxonomic characterisation of fungal communities is necessary for establishing ecological associations and early detection of pathogens and invasive species. Complex communities of fungi are regularly characterised by metabarcoding using the Internal Transcribed Spacer (ITS) and the Large-Subunit (LSU) gene of the rRNA locus, but reliance on a single short sequence fragment limits the confidence of identification. Here we link metabarcoding from the ITS2 and LSU D1-D2 regions to characterise fungal communities associated with bark beetles (Scolytinae), the likely vectors of several tree pathogens. Both markers revealed similar patterns of overall species richness and response to key variables (beetle species, forest type), but identification against the respective reference databases using various taxonomic classifiers revealed poor resolution towards lower taxonomic levels, especially the species level. Thus, Operational Taxonomic Units (OTUs) could not be linked via taxonomic classifiers across ITS and LSU fragments. However, using phylogenetic trees (focused on the epidemiologically important Sordariomycetes) we placed OTUs obtained with either marker relative to reference sequences of the entire rRNA cistron that includes both loci and demonstrated the largely similar phylogenetic distribution of ITS and LSU-derived OTUs. Sensitivity analysis of congruence in both markers suggested the biologically most defensible threshold values for OTU delimitation in Sordariomycetes to be 98% for ITS2 and 99% for LSU D1-D2. Studies of fungal communities using the canonical ITS barcode require corroboration across additional loci. Phylogenetic analysis of OTU sequences aligned to the full rRNA cistron shows higher success rate and greater accuracy of species identification compared to probabilistic taxonomic classifiers

Fibroma desmoplásico, reporte de un caso y revisión de la literatura

ResumenEl fibroma desmoplásico es una lesión neoplásica relativamente rara. Se considera un tumor primario de hueso, que se presenta comúnmente en la región mandibular. Se define como un tumor benigno caracterizado por la formación de abundante matriz y fibras colágenas. En marzo de 2004 se presenta el caso de un paciente de 15 años, varón, con aumento gradual en la región derecha de la mandíbula de 4 meses de evolución. Se manifiesta asintomático, con aumento de volumen, con una apariencia radiográfica y tomográfica bien delimitada radiolúcida. A la exploración se observa un infiltrado a través de la cortical lingual. La lesión es similar a las descritas en la literatura de fibroma desmoplásico.AbstractDesmoplastic fibroma (fibromatosis) is rarely seen a primary tumor of bone. Its occurrence as a central lesion in the jaws is even more uncommon. It is rare tumor of bone, especially in the mandibule. In march 2004, a 15 year-old boy presented, with a 4 month history of gradual enlargement of the right mandibule. Painless intraoral and extraoral swelling, the cortical plate of bone overlying the lesions is expanded with thinning, erosion, and infiltration into the surrounding tissues. The lesion is similar to the one described on the articule