Frequent pattern mining has been a focused theme in data mining research for over a
decade. Abundant literature has been dedicated to this research and tremendous progress …

Despite being one of the most basic tasks in software development, debugging is still
performed in a mostly manual way, leading to high cost and low performance. To address …

Advanced Persistent Threats (APTs) are difficult to detect due to their" low-and-slow" attack
patterns and frequent use of zero-day exploits. We present UNICORN, an anomaly-based …

Detecting anomalies in data is a vital task, with numerous high-impact applications in areas
such as security, finance, health care, and law enforcement. While numerous techniques …

This chapter will provide a detailed survey of frequent pattern mining algorithms. A wide
variety of algorithms will be covered starting from Apriori. Many algorithms such as Eclat …

Software fault localization, the act of identifying the locations of faults in a program, is widely
recognized to be one of the most tedious, time consuming, and expensive-yet equally critical …

Given a stream of heterogeneous graphs containing different types of nodes and edges,
how can we spot anomalous ones in real-time while consuming bounded memory? This …

Given a large, weighted graph, how can we find anomalies? Which rules should be violated,
before we label a node as an anomaly? We propose the oddball algorithm, to find such …

Along with the blossom of open source projects comes the convenience for software
plagiarism. A company, if less self-disciplined, may be tempted to plagiarize some open …

Abstract Service-oriented architectures and microservices define two ways of designing
software with the aim of dividing an application into loosely-coupled services that …