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Modern botnets leverage TLS encryption to mask C&C server communications. TLS certificates used by botnets could exhibit subtle characteristics that facilitate detection. In this paper we investigate whether text features from TLS certificates can be ...

Prostate cancer is one of the leading causes of cancer death in men in Western societies. Predicting patients’ survival using clinical descriptors is important for stratification in the risk classes and selecting appropriate treatment. Current ...

Many real-world use cases benefit from fast training and prediction times, and much research went into speeding up distance-based outlier detection methods to millions of data points. Contrary to popular belief, our findings suggest that little ...

The development of microwave radar vital sign sensing system brings many benefits to mankind. This system can be used to detect the location of living people buried under debris. Other important applications of microwave radar sensor are smart home, ...

In this research, we hypothesize that some social users are more gullible to fake news than others, and accordingly investigate on the susceptibility of users to fake news--i.e., how to identify susceptible users, what are their characteristics, and if ...

Motion capture technologies digitize human movements by tracking 3D positions of specific skeleton joints in time. Such spatio-temporal multimedia data have an enormous application potential in many fields, ranging from computer animation, through ...

In applications such as virtual and augmented reality, a plausible and coherent audio-visual reproduction can be achieved by deeply understanding the reference scene acoustics. This requires knowledge of the scene geometry and related materials. In this ...

Exploring large medical image sets by means of traditional similarity query criteria (e.g., neighborhood) can be fruitless if retrieved images are too similar among themselves. This demonstration introduces Kundaha, an exploration tool that assists ...

Understanding how to group a set of binary files into the piece of software they belong to is highly desirable for software profiling, malware detection, or enterprise audits, among many other applications. Unfortunately, it is also extremely challenging:...

Many cities have been releasing their traffic data for companies to do the data analytics for business and other purposes. In this paper, we propose different classification models to analyze the places that most of vehicles speed and the places that ...

Intrusion detection systems need to be both accurate and fast. Speed is important especially when operating at the network level. Additionally, many intrusion detection systems rely on signature based detection approaches. However, machine learning can ...

In this article we present a novel method that uses image and speech processing techniques to analyze video from a second language learner and provides speaker's pronunciation training. The pronunciation recommendation provided for the speaker will be ...

Our slogan for the proposed Clairvoyant system is "with several clicks, the future is in your hand, the plan comes into your mind". Clairvoyant is to predict the future of new videos with only few data. The core function in the system is the novel ...

This paper presents a study of clustering algorithms in bug classification for a company from a database that contains a description each bug. It is made a comparison these algorithms using a sample of the database of this company. Considering that the ...

Multi-label classification refers to the problem that predicts each single instance to be one or more labels in a set of associated labels. It is common in many real-world applications such as text categorization, functional genomics and semantic scene ...

Outlier detection is becoming a hot issue in the field of data mining since outliers often contain useful information. In this paper, we propose an improved KNN based outlier detection algorithm which is fulfilled through two stage clustering. ...

In this work we propose a "copy and scale" method based on the 1-NN paradigm to estimate time-localized parameters and apply it to the problem of beat-tracking. The 1-NN algorithm consists in assigning the information of the closest item of a pre-...

Fast query processing of complex objects, e.g. spatial or uncertain objects, depends on efficient spatial pruning of objects' approximations, which are typically minimum bounding rectangles (MBRs). In this paper, we propose a novel effective and ...

Service providers like Google and Amazon are moving into the SaaS (Software as a Service) business. They turn their huge infrastructure into a cloud-computing environment and aggressively recruit businesses to run applications on their platforms. To ...

An outlier is the object which is very different from the rest of the dataset on some measure. Finding such exception has received much attention in the data mining field. In this paper, we propose a KNN based outlier detection algorithm which is ...