Hacking activism and cyber crimes have increased the threats in cyberspace. Cyber terrorism and warfare intensify these threats even more. Companies encounter advanced threats even if they have the best security solutions. More effective means to detect the threats and remove them is the need of the hour for every company. Every minute, 1820 TB of data is introduced on the World Wide Web.
Any big data project can make use of this data and the challenge is that it poses a serious security problem for IT professionals who are supposed to manage Big Data.
Let us have a look at some of the myths and the truth of security analytics.
Myths and Facts of Big Data Security Analytics
- Big Data can be effectively managed by the enterprise security already in existence without the need of security professionals
It is a myth that big data requires no security professionals. In addition, it can be handled by the enterprise security. The massive data of IT alerts and the complexity of cyber threats need Big Data Security Analytics (BDSA) to adopt machine learning so that threats can be easily recognized.
Reality: Big Data Security Analytics offers identification of sophisticated attacks. However, it is imperative to have security professionals who can successfully assess the analytics. Experienced professionals can never get outdated because they can successfully check the working of BDSA system.
- It is feasible to detect attacks in real-time
Owing to the speedy processors and exorbitant expenditure taken by defense tools, advanced and multi-stage cyber attacks can be recognized in real time. Due to this, they can be promptly removed from the system. These beliefs are not true.
Reality: Real-time detection of cyber threats is not possible. However, BDSA enables the fast mitigation of sophisticated attacks even if they are not recognized by the perimeter defenses. Attacks can be easily detected when the threats are familiar. Rules can be formulated too in that case. It becomes even more challenging when the threats are complex and unknown. This is because the markers linked with such attacks are weak. They fail to rise above the noise. If the security team gets alerts on every weak signal, they would get overwhelmed. Nonetheless, BDSA along with machine learning remove the sophisticated attacks without any need of rules formulation.
- An exhaustive threat visibility is possible through one data source
With the help of risk profiles, a panoramic view of the threat can be obtained. Several solutions are available that guarantee to provide such a view by application of analytics against one data source like log data. This is a myth.
Reality: Analytics on one source like logs offer limited knowledge. If more packets are added, the visibility is enhanced largely. Let us say, for example, – Logs can help you to see the URLs accessed by a browser while packets can help you to assess the information that is being exchanged. This can help you in figuring out threats. Ultimately, an organization’s needs and availability of data sources determines this. It should be taken into consideration that BDSA solution that you choose should offer precise and competitive analytics even if it is one data source or many.
- Newer threats can be detected by conventional security approaches
Conventional security solutions can be customized according to the threats. It is a misconception that the security monitoring system of the organization is enough to fight against the newer threats of cyberspace.
Reality: Security solutions that were used in the olden times cannot handle the enormous information that is being added in companies these days. Unknown and advanced cyber attacks can be combated through such traditional systems. As they are unable to scale and apply self-learning analytics on Big Data, these traditional approaches fail against complex cyber attacks.
- The only thing necessary is user behavior analytics
Another wrong notion regarding security analytics is that user behavior analytics can successfully discover complex attacks by profiling user behavior to recognize malware. This is a false belief that if you have user behavior analytics, you are secure from cyber attacks.
Reality: It is true that behavioral analytics can help in recognizing sophisticated attacks. However, it should be borne in mind that along with users, devices and applications should also be profiled. The correct approach is entity behavior analytics. It is imperative to have behavioral analytics along with discrete analytics and forensics. Discrete analytics helps in having a glimpse of the data in a stateless and entity-less way at a solitary point in time. Forensics, on the other hand, offers proofs for investigation of alerts. The combination of all three can accurately deal with the attacks.
- Analytics are competent enough to fight all threats
The recognition of recent cyber attacks would be effectively done by analytics alone. It is a myth that analytics would suffice for the successful removal of threats.
Reality: Without any ambiguity, analytics are very much precious in order to stay safe from cyber attacks. However, as these attacks are getting advanced with each passing day, it becomes inevitable for the security personnel to have complete evidence regarding the attacks detected by BDSA. For this reason, it is imperative to have forensics intrinsically associated with BDSA so that the analysts have a ready access to data and evidence needed in order to determine the perils of the threats.
Big Data Security Analytics need an innovate approach to consider the security of the company as a whole. The hugeness of the data is sure of concern, but what creates a greater concern is the variability of data and the enormous data sources. The prudent use of BDSA can prove to be immensely useful to a company.
The myths associated with security analytics should be curbed and analysts should focus on the careful evaluation of the potential of these security solutions. Besides, it is necessary to determine what the needs of the organization are as far as security is concerned. Since Big Data is a lot beyond the massive datasets, it is unavoidable to implement advanced business and security rules through BDSA.