Recent results of machine learning for automatic vulnerability detection have been very
promising indeed: Given only the source code of a function f, models trained by machine …

Automatically discovering software vulnerabilities is a long-standing pursuit for software
developers and security analysts. Since detection tools usually provide limited information …

Cloud computing has become integral to modern organizational operations, offering
efficiency and agility. However, security challenges such as data loss and downtime …

Developers, and administrators, can benefit from inculcating an attacker mindset to
foreshadow potential security flaws is software systems as they are developed and/or …

Cyber risk assessments are an essential process for analyzing and prioritizing security
issues. Unfortunately, many risk assessment methodologies are marred by human …

The security demands on modern system administration are enormous and getting worse.
Chief among these demands, administrators must monitor the continual ongoing disclosure …

Vulnerability scanners are deployed in computer networks and software to timely identify
security flaws and misconfigurations. However, cloud computing has introduced new attack …

It is critical to ask and address the following type of questions, both as a cloud computing
architect who has designed and deployed a public, or private, or hybrid cloud; or a user who …

Current approaches for risk analysis of software vulnerabilities using manual assessment
and numeric scoring do not complete fast enough to keep pace with the maintenance work …

Understanding the landscape of software vulnerabilities is key for developing effective
security solutions. Fortunately, the evaluation of vulnerability databases that use a …