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Download: Identifying Insider Threats Through Machine Learning and Behavioral Analysis White Paper

Using Machine Learning to Identify Insider Threats

When we speak of insider threats various connotations come to mind. Perhaps you think of whistleblowers attempting to damage an organization by leaking proprietary information or maybe employees seeking to profit through persistent industrial espionage. While these examples certainly represent a credible danger, there’s a category of risk that includes a much more significant threat — malicious outsiders who penetrate systems by stealing legitimate credentials and thus appear as insiders.

Given that the most important information resides in databases, organizations are increasingly turning their focus toward databases security technologies. To defend databases from attackers using stolen credentials, the industry is beginning to adopt a new security paradigm based on machine learning and behavior analysis.



Download: Database Discovery White Paper

Non-Intrusive Approach to Database Discovery

Knowing where your most valuable data assets are located is an essential first step in protecting them. Most security practices begin with a discovery phase to identify the organizations most critical data. This will ensure that the security practices will protect these assets. As an information asset residing at the core of every critical business process, databases are the principle location for high-value organizational data.

Keeping track of databases, and the associated data they host, turns out to be a significant challenge. Most organizations lack the necessary tools to track the location of sensitive data repositories and how they’re being used. The issue is far larger than a single or even a periodic initiative to create an inventory of sensitive assets. Given the dynamic nature of organizational data, the way it is being used, stored, and eventually destroyed is constantly in flux and needs to be tracked on a continuous basis.



Download: SQL Injection Defense White Paper

There are no Silver Bullets

A proper defense-in-depth strategy seeks to reduce the SQL injection attack surface at each tier of the architecture. Rather than focusing on a "silver bullet" solution in the Web or application tier, a comprehensive defense-in-depth strategy addresses the entire architecture including the database tier – which is the ultimate goal of the attack.

A SQL injection attack that has penetrated the perimeter, exploited the application, and reached the database tier is “knocking at the door” of the database. If not immediately identified, alarmed, and contained at that point a breach is imminent. Once the SQL injection attack is contained and the specific vulnerability identified, patches can be applied as part of an iterative mitigation process to continually reduce the risk.



Download: Advanced Web Application Pen Testing

Proper Instrumentation is Key to Success

It’s critical your web applications are as secure as possible while also staying on schedule and within budget. Often organizations turn to penetration testing and application code scanning to identify security vulnerabilities. While neither approach is perfect, they both do find lots of areas that your developers need to tighten up (and just as importantly, they keep the compliance folks happy). Still, there’s no question that there are important vulnerabilities that are being missed. The challenge is how to find the most risky ones without blowing the budget or schedule.





Download: Detecting SQL Injection Attacks

Proper Instrumentation is Key to Success

Detecting SQL fragments injected into a Web application has proven extremely challenging. There are several tacks enterprises can take – prevention, remediation, and mitigation. When implementing prevention and remediation efforts, the enterprise strives to develop secure code and/or encrypt confidential data stored in the database. However, these are not always available options.