On Generating and Labeling Network Traffic with Realistic Self Propagating Malware

Synthetically produced data containing fabricated or merged network traffic is of limitedvalue as it is easily distinguishable from real traffic by even simple machinelearning (ML) algorithms . Real-world malware is defanged and introduced to simulated, secured nodes within those networks to generate realistic traffic while maintaining sufficient isolation to protect real data and infrastructure .…

Reproducibility Report for the Paper QN based Modeling and Analysis of Software Performance Antipatterns for Cyber Physical Systems

The authors have uploaded their artifact to Zenodo, which ensures a long-term retention of the artifact . The artifact allows to re-run the experiments verysmoothly, and the dependencies are well documented . The process to regeneratedata for the figures and tables in the paper completes, and all results are reproducible .…

CTNet Context based Tandem Network for Semantic Segmentation

Spatial Contextual Module (SCM) leveraged to learn spatial contextual dependency between pixels by exploring thecorrelation between pixels and categories . The Channel ContextualModule (CCM) is introduced to learn the semantic features including thesemantic feature maps and class-specific features . The learned semantic features are used as the prior knowledge to guide the learning of SCM, which can makeSCM obtain more accurate long-range spatial dependency .…

SE SSD Self Ensembling Single Stage Object Detector From Point Cloud

Self-Ensembling Single-Stage object Detector (SE-SSD) for accurate and efficient 3D object detection in outdoor point clouds . Key focus is onexploiting both soft and hard targets with our formulated constraints to jointly optimize the model, without introducing extra computation in the inference .…

A New Class of Efficient Adaptive Filters for Online Nonlinear Modeling

The proposed algorithm is based on thelinear-in-the-parameters (LIP) nonlinear filters and their implementation asfunctional link adaptive filters (FLAFs) We focus here on a new effective and efficient approach for FLAFs based on frequency-domain adaptive filters . We propose a partitioned block approach for their implementation .…

A Polyhedral Approach to Some Max min Problems

We consider a max-min variation of the classical problem of maximizing alinear function over the base of a polymatroid . In our problem we assume that the vector of coefficients of the linear function is not a known parameter of the problem but is some vertices of a simplex .…

Finding Small Multi Demand Set Covers with Ubiquitous Elements and Large Sets is Fixed Parameter Tractable

We study a variant of Set Cover where each element of the universe has somedemand that determines how many times the element needs to be covered . We prove that all three problems are fixed-parameter tractable with respect to the combinedparameter budget, the maximum number of elements missing in one of the sets, and how many sets can be included multiple times .…

Exploiting Underlay Spectrum Sharing in Cell Free Massive MIMO Systems

We investigate the coexistence of underlay spectrum sharing in cell-freemassive multiple-input multiple- input multiple-output (MIMO) systems . A primary system withgeographically distributed primary access points (P-APs) serves a multitude of primary users (PUs) while a secondary system serves a large number of secondary users (SUs) in the same primary/licensed spectrum .…

The principle of weight divergence facilitation for unsupervised pattern recognition in spiking neural networks

Parallels between the signal processing tasks and biological neurons lead to an understanding of the principles of self-organized optimization of input signals . We propose the addition to the well-knownSTDP synaptic plasticity rule to directs the weight modification towards the state associated with the maximal difference between the background noise and related signals .…

Problems and Countermeasures in Natural Language Processing Evaluation

Evaluation in natural language processing guides and promotes research on models and methods . In recent years, new evalua-tion data sets and evaluation tasks have been continuously proposed . A series of problemsexposed by ex-existing evaluation have also restricted the progress of naturallanguage processing technology .…

Fluid beam interaction Capturing the effect of embedded slender bodies on global fluid flow and vice versa

This work addresses research questions arising from the application of geometrically exact beam theory in the context of fluid-structure interaction(FSI) We propose amixed-dimensional embedded finite element approach for the coupling of one-dimensional equations to a three-dimensional background fluid mesh . Here, the fluid is described by theincompressible isothermal Navier-Stokes equations for Newtonian fluids .…

Meta-learning has garnered attention as a promising technique for enhancing learning under low-resource scenarios . We proposeX-METRA-ADA, a cross-lingual MEta-TRAnsfer learning ADAptation approach for Natural Language Understanding (NLU) We show that our approach outperformsnaive fine-tuning, reaching competitive performance on both tasks for most languages .…

Privacy aware VR streaming

Proactive tile-based virtual reality (VR) video streaming employs the current tracking data of a user to predict future requested tiles . The quality of the experience (QoE) depends on the overall performance of prediction, computing(i.e., rendering) and communication) The researchers found that with DoP, the lengthof the observation window and prediction window of a tile predictor should be variable.…

A novel three stage training strategy for long tailed classification

Long-tailed distribution datasets poses great challenges for deeplearning based classification models . Existing solutions usually involve class-balacing strategies or transfer learing from head-to-tail-classes . However, existing methods are difficult to solve the low quality problem when images are obtained by SAR .…

Prospective Artificial Intelligence Approaches for Active Cyber Defence

Cybercriminals are rapidly developing new malicious tools that leverage AI to enable new classes of adaptive and stealthy attacks . New defensive methods need to be developed to counter these threats . Alan Turing Institute, with expert guidance from UK Cyber Security Centre and Defence Science Technology Laboratory, published a research roadmap for AI for ACD last year .…

Mapping Moral Valence of Tweets Following the Killing of George Floyd

The viral video documenting the killing of George Floyd by Minneapolis police officer Derek Chauvin inspired nation-wide protests . The use of social media by the BlackLives Matter movement was a primary route for activists to promote the cause . Recent research arguesthat moral discussions on social media are a catalyst for social change .…

Numerical solution of internal wave systems in the intermediate long wave and the Benjamin Ono regimes

The paper is concerned with the numerical approximation of the IntermediateLong Wave and Benjamin-Ono systems . The paper focuses on two issues of approximation . The second issue concerns the numerical generation of solitary-wavesolutions of the systems . We use acceleration techniques to improve thecomputation of the approximate solitary waves and check their performance withnumerical examples.…

An Analysis of Indexing and Querying Strategies on a Technologically Assisted Review Task

This paper presents a preliminary experimentation study using the CLEF 2017eHealth Task 2 collection . It is an attempt to advance and share the efforts of observing the effectiveness of various methodologies for indexing PubMeddocuments and for different topic parsing techniques .…

A monolithic and a partitioned Reduced Basis Method for Fluid Structure Interaction problems

The aim of this work is to present a brief report concerning the various aspects of the Reduced Basis Method within Fluid-Structure Interaction problems . The toy problem that we consider is the Turek-Hron benchmark testcase, with a fluid Reynolds number Re = 100, which is known to lead to the formation of Karman vortexes in the fluid, and a periodically oscillatingbehaviour in the structure .…

Inferring Drop in Binary Parsers from Program Executions

We present BIEBER (Byte-IdEntical Binary parsER), the first system to modeland regenerate a working parser from instrumented program executions . Toachieve this, BIEber exploits the regularity (e.g., header fields andarray-like data structures) that is commonly found in file formats . Separate backends (C and Perl in our prototype) can translate the IR intothe same language as the original program (for a safer drop-in replacement), or port to a different language .…

Interpolation of Microscale Stress and Strain Fields Based on Mechanical Models

In this short contribution we introduce a new procedure to recover the stressand strain fields for particle systems by mechanical models . Numerical tests for simple loading conditions have shown an excellent match between theestimated values and the reference values .…

On the Impact of Word Error Rate on Acoustic Linguistic Speech Emotion Recognition An Update for the Deep Learning Era

Text encodings from automatic speech recognition (ASR) transcripts and audiorepresentations have shown promise in speech emotion recognition (SER) eversince . Yet, it is challenging to explain the effect of each information stream on the SER systems . More clarification is required for analysing the impact of ASR’s word error rate (WER) on linguistic emotion recognition per seand in the context of fusion with acoustic information exploitation in the age of deep ASR systems .…

Robust Online Algorithms for Dynamic Choosing Problems

Semi-online algorithms that are allowed to perform a bounded amount of repacking achieve guaranteed good worst-case behaviour in a more realisticsetting . We present a framework for choosing problems that allows usto transfer offline algorithms into $(\alpha-epsilon) algorithms with amortized migration$O(1/\epSilon) We complement these positive results with lower bounds with lowerbounds that show that our results are tight in the sense that no amortization of $o(1)$ is possible .…

Towards Autonomous Robotic Precision Harvesting

A walking harvester performs the challenging task of autonomous navigation and tree grabbing in a confined, GPS denied forestenvironment . Strategies for mapping, localization, planning, and control are proposed and integrated into a fully autonomous system . The mission starts with a human or a mobile robot mapping the area of interest using a custom-madesensor module .…

Computing Arlequin coupling coefficient for concurrent FE MD approaches

Arlequin coupling coefficient is essential for concurrent FE-MD models with overlapping domains . Procedure includes steps of determining the relative positions of atoms inside the FE elements in the coupling region . Two approaches are provided for determining thecoefficient: the direct approach and the temperature approach .…

Nonlinear Tracking and Rejection using Linear Parameter Varying Control

The Linear Parameter-Varying (LPV) framework has been introduced with the intention to provide stability and performance guarantees for analysis andcontroller synthesis for Nonlinear (NL) systems via convex methods . We propose to solve this problem by the application of incremental stability and .…

Quantum hub and authority centrality measures for directed networks based on continuous time quantum walks

In this work we introduce, test and discuss three quantum methods for computing hub and authority centrality scores in directed networks . The methods are based on unitary, continuous-time quantum walks . The construction of asuitable Hermitian Hamiltonian is achieved by performing a quantum walk on the bipartite graph .…

Personalized News Recommendation with Knowledge aware Interactive Matching

The core of personalized news recommendation is accurate matching betweencandidate news and user interest . Most existing news recommendation methods usually model candidate news from its textual content . However, a news article may cover multiple aspects and entities, and a user may have multiple interests .…

Meshfree Approximation for Stochastic Optimal Control Problems

In this work, we study the gradient projection method for solving a class of class of stochastic control problems by using a mesh free approximation approach to implement spatial dimension approximation . We also present several numerical experiments to validate the theoretical results of our approach and demonstrate the convergence of our meshfree approximation approach .…

Market Value of Differentially Private Smart Meter Data

This paper proposes a framework to investigate the value of sharingprivacy-protected smart meter data between domestic consumers and load servingentities . The framework consists of a discounted differential privacy model toensure individuals cannot be identified from aggregated data . It also includes a ANN-basedshort-term load forecasting to quantify the impact of data availability and privacy protection on the forecasting error and an optimal procurement day-ahead and balancing markets to assess the market value of the privacy-utility trade-off .…

Towards Solving Multimodal Comprehension

This paper targets the problem of procedural multimodal machine comprehension(M3C) This task requires an AI to comprehend given steps of multimodalinstructions and then answer questions . Yagcioglu etal. [35] introduced RecipeQA dataset to evaluate M3C . We hypothesized that naturally occurring bias present in the dataset affects even the bestperforming model .…

The Impact of DoS Attacks onResource constrained IoT Devices A Study on the Mirai Attack

Mirai is a type of malware that creates a botnet of internet-connecteddevices, which can later be used to infect other devices or servers . This paperaims to analyze and explain the Mirai code and create a low-cost simulationenvironment to aid in the dynamic analysis of Mirai .…

Coresets for k ell Median Clustering under the Fréchet Distance

We present an algorithm for computing $epsilon-coresets for$(k,\ell)$-median clustering of polygonal curves under the Fr\’echet distance . We restrict the complexity,i.e., number of vertices, of the center curves to be at most$\ell$each, to suppress overfitting . We achieve this result by applying the improved$ebsilon\$-coreset framework by Braverman et al.…

Computing eigenvalues of the Laplacian on rough domains

A key element of the proof is the development of a novel, explicit Poincar\’e-type inequality . These results allow us to construct a universal algorithm capable of computing the eigenvalues of the Dirichlet Laplacian on a wide class of rough domains .…

A Language for Modelling False Data Injection Attacks in Internet of Things

Internet of Things (IoT) relies on the data collected by objects . Data integrity is threatened by a type of attack known as False Data Injection Attack . This consists of an attacker who injectsfabricated data into a system to modify its behaviour .…