Uncovering the Truth about Six Big Data Security Analytics Myths

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Reduces Need for Security Pros

Myth #1: Security analytics reduces the need for security professionals.

The huge volume of IT alerts and the sophistication of attacks require BDSA to use machine learning to automatically surface threats, making security professionals obsolete.

Why it's a myth: BDSA provides the machine assist by identifying markers of advanced attacks, but still requires security professionals to examine the analytics and evidence. Threats are becoming increasingly sophisticated and are constantly evolving, so experienced professionals are needed to ensure that BDSA systems are working correctly.

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.

 

Related Topics : Unisys, Stimulus Package, Security Breaches, Symantec, Electronic Surveillance

 
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