Biblio

In recent years, cyber attack techniques are increasingly sophisticated, and blocking the attack is more and more difficult, even if a kind of counter measure or another is taken. In order for a successful handling of this situation, it is crucial to have a prediction of cyber attacks, appropriate precautions, and effective utilization of cyber intelligence that enables these actions. Malicious hackers share various kinds of information through particular communities such as the dark web, indicating that a great deal of intelligence exists in cyberspace. This paper focuses on forums on the dark web and proposes an approach to extract forums which include important information or intelligence from huge amounts of forums and identify traits of each forum using methodologies such as machine learning, natural language processing and so on. This approach will allow us to grasp the emerging threats in cyberspace and take appropriate measures against malicious activities.

A popular form of software reuse is the use of open source software libraries hosted on centralized code repositories, such as Maven or npm. Developers only need to declare dependencies to external libraries, and automated tools make them available to the workspace of the project. Recent incidents, such as the Equifax data breach and the leftpad package removal, demonstrate the difficulty in assessing the severity, impact and spread of bugs in dependency networks. While dependency checkers are being adapted as a counter measure, they only provide indicative information. To remedy this situation, we propose a fine-grained dependency network that goes beyond packages and into call graphs. The result is a versioned ecosystem-level call graph. In this paper, we outline the process to construct the proposed graph and present a preliminary evaluation of a security issue from a core package to an affected client application.