The recent proliferation of computing technologies (eg, sensors, computer vision, machine
learning, and hardware acceleration) and the broad deployment of communication …

This survey paper discusses opportunities and threats of using artificial intelligence (AI)
technology in the manufacturing sector with consideration for offensive and defensive uses …

The increase in number and variety of malware samples amplifies the need for improvement
in automatic detection and classification of the malware variants. Machine learning is a …

This textbook explores the different aspects of data mining from the fundamentals to the
complex data types and their applications, capturing the wide diversity of problem domains …

Ransomware is a growing threat that encrypts auser's files and holds the decryption key until
a ransom ispaid by the victim. This type of malware is responsible fortens of millions of …

Outliers are also referred to as abnormalities, discordants, deviants, or anomalies in the data
mining and statistics literature. In most applications, the data is created by one or more …

In the statistics community, outlier detection for time series data has been studied for
decades. Recently, with advances in hardware and software technology, there has been a …

Outlier detection has been a topic in statistics for centuries. Over mainly the last two
decades, there has been also an increasing interest in the database and data mining …

Event labeling is the process of marking events in unlabeled data. Traditionally, this is done
by involving one or more human experts through an expensive and time-consuming task. In …

In the current network-based computing world, where the number of interconnected devices
grows exponentially, their diversity, malfunctions, and cybersecurity threats are increasing at …