Behavioral Analysis Is Known As Privacy-Preserving Technology

admin | July 9th, 2019 | CloudCodes

Behavioral Analysis

Introduction to Behavioral Analysis

On the basis of multiple misconceptions, the location of privacy versus security with behavior analysis is the wrong dichotomy. It is essential to have security as well as privacy in a premises where cloud computing technology is used for growth. Indeed, the idea of behavioral analysis enhances privacy, rather than threatening it. The reason for the same is briefly explained in today’s CloudCodes post.

Security – A Major Problem For Cloud Users

Cyber security itself is shifting to the cloud in an effective manner. But up to what extent are companies analyzing protection level of data in the cloud? What measures are they adopting to protect the information stored online? In an average firm scenario, what’s the success reality of already available endpoint devices security? How are these architecture coping in particular attack scenarios?

Before we directly jump upon answering of these questions, lets first understand ‘what is a behavioral analysis?

A technology consolidated with machine learning programs, artificial intelligence system, big data handling processes, and analytics is known as behavioral analysis. It is used to address malicious, stealth behavior by detecting subtle differences in everyday normal activities to proactively prevent the occurrence of cyberattackers. This type of analysis tries its best in stopping hackers from performing their intended destructive tasks.

Connect Technology, Processes, and People – This mantra is important to adopt in an organization to achieve a successful cloud security environment in their premises. Here, the focus is upon the balance between privacy and big data issues, between the data privacy and data utility. This particular scenario becomes critical when its about information security. Businesses take tension that their data is already collected by security products is intrusive and must be controlled at any cost. Behavioral analysis of that particular collected data, and unstructured type of data like chat history, is a step too far.

Its Time to Get Answers to Actual Questions

First of all, some folks take unusual tension that gathering of personal information doesn’t follow the data protection standards; due to which it is essential to always remember that the data collection for security purpose is a lawful and legitimate activity. Yes, it’s true! Rest, other 50 articles of GDPR are applicable for companies who are processing EU citizens data. Any kind of information collected by protection products must be consistent with the principles of storage limitation, transparency, data minimization, etc.

Another thing is data collected for the purpose of security must comply with local laws of labor. This again limits down the scope and purpose of data collection to protection-based interests. It cannot be applied for other operations like enforcing corporate use standards and performance monitoring unless it discloses the company or the user to the security challenges. Its simple to say but difficult to implement – how could a machine identify whether a web page is prohibited due to ethical causes, or due to the presence of a threat? Also, what if the access to a web site is essentially required for research like for competitive analysis, journalism, etc.? These conditions increase the importance of risk adaptive security and behavioral analysis – policy enforcement flexibility based on the company’s requirement and single risk factor.

The third concern regarding data security and privacy is based on the data security overestimation, which is being gathered. Information security is already collected in petabytes, archived in SIEM, logs, and other places that can result in false outcome. Usually, information is stored in an unencrypted form and insecure manner without any insufficient amount of proper access controls and privileged access monitoring. Log files are often used without any defined set of strict access controls or are kept unlocked. Execution of behavioral analytics forces companies to enhance controls over data security. Also, this demands the assurance of complete data governance.

Details regarding security often collected without the complete transparency of its level and aim and is sent off-site for analysis purpose online. This breaks the data security standard without the organization being known about it. Companies that use behavioral analytics also develop a team for data governance, control, and security, to get a fruitful result. Critically, the team gets to engage in other sorts of business works to benefit it that they forget to supervise the things. It is an important aspect to achieve a complete audit of the activities performed in-office hours, and ensure the real-time monitoring of privileged access via the same technology.

Conclusion

At the end, several organizations underestimate the security challenge from employees causing harm either intentionally or unintentionally. The majority of cybercrimes continue to be caused due to the user activities like malicious insiders, phishing, or compromised confidential details. Organizations that remain oblivious to this, are deliberately ignorant, or remain in denial are disclosed to increasing risk of data breaches.

Companies need to have a better knowledge about cloud computing security challenges along with the role of behavioral analysis technology. Only then, they can organize a complete informed challenge assessment.

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