Cyber threats are becoming extremely sophisticated, as evidenced by the many high-profile breaches over the last few years. Organizations are confronting a new reality where they must accept that they are likely to be impacted, despite their best attempts to keep these threats out altogether. They need quicker and better ways to discover, investigate and remediate these threats. Marrying Big Data with machine learning can help address this challenge by providing security professionals with the Big Data security analytics (BDSA) they need to thwart the bad guys.
Without a doubt, when BDSA is used correctly, it is extremely beneficial to an organization. However, there are many false claims around the capabilities of BDSA. When considering BDSA solutions, analysts need to carefully evaluate these capabilities and determine whether their organizations' needs for detection of attacks on the inside and incident response are being met. In this slideshow, John Dasher, vice president of marketing at Niara, a cybersecurity company focused on Big Data analytics, has identified six common myths to consider when deploying BDSA solutions.
Whaling is a type of spearphishing targeting "big fish" in an organization with access to sensitive, highly-valuable information. ... More >>
Five common failures companies make when preparing for, and responding to, a data breach, as well as guidance for companies on how they can tackle these issues. ... More >>
Incorporating security capabilities such as encryption, better control and management and a data security framework will help alleviate the burden breaches place on the organization and people's lives. ... More >>