Analytics

NewEvol’s Powerful Combination of Cyber Security & Data Analytics 

The traditional approach of Cyber Security has become less effective as the nature of cyberattacks has evolved. Cyber attackers use loopholes and target hardware equipment, software, and network systems of an organization, exposing them to more vulnerabilities. With increased dependence on cloud and on-premises data repositories, adoption of 5G, and interconnected devices, organizations have started to adopt advanced data and security analytics platforms. It deploys advanced analytic techniques to structured, semi-structured, raw data and allows analysts to gain new insights from inaccessible data or existing data to drive faster and better decisions. 

Table of contents 

1. Rise of big data analytics in cyber security. 

2. An introduction to NewEvol’s big data analytics. 

3. NewEvol’s data management and analysis capabilities 

4. NewEvol’s in-house cyber security platform 

5. Tools offered by NewEvol security analytics  

6. Example of security analytics use cases  

7. Conclusion 

Rise of Big Data Analytics in Cyber Security 

Millions of devices connected to the same network and cloud create a surface full of entry points. These entry points are loopholes for cyber attackers. As the volume of cyber threats increases, the need for an all-inclusive, data-driven, end-point security solution arises. In today’s world, big data analytics has become an essential approach to drive better and fast decisions. Big Data Analytics detects cyber threats at an early stage and prioritizes the security of an organization as a standard measure. 

An introduction to NewEvol’s Big Data Analytics 

NewEvol’s big data analytics deploys data mining, machine learning, statistical algorithms to analyze data sets and gain useful insights. The security operations team can create and customize current threat models to prevent or mitigate the effects of threats. This solution as a group uncovers customer patterns, explores several situations, predicts future incidents, and provides possible diagnoses related to cyber security problems. 

NewEvol’s Data Management and Analysis capabilities 

NewEvol security analytics is a modern approach to cyber security that uses data collection, data aggregation, analysis tools and applies it to security operations to detect, remediate and monitor threat data. The solution helps investigate malicious events and protects the organization against present or zero-day threats. Data aggregation collects data from different sources and presents a summarised way for statistical analysis.  

NewEvol is a Revolutionary Cybersecurity Platform 

NewEvol has developed a platform that applies machine learning and artificial intelligence technologies to security operations, automating the response to events by proactively being ahead of cyber attackers. NewEvol has developed a group of tools in-house and integrated them into one platform in a cost-effective way. NewEvol’s cyber security and data analytics platform is easily scalable. The data structure of this platform can increase to accommodate large networks and a high number of users. 

Tools offered by NewEvol Security Analytics

NewEvol offers the following solutions: 

• Security information and event management (SIEM): NewEvol SIEM collects and analyses event and log data from various sources to create an alert for malicious events, login failure, etc  

• Hadoop-based Data Lake: NewEvol’s Hadoop-based data lake stores and processes a high volume of structured, semi-structured, and raw data to accommodate larger networks and the high number of users. 

• User and entity behavior analytics (UEBA): UEBA explores users’ behavior or pattern, applications, and mobile devices to find abnormalities that can lead to a cyber attack. 

• Orchestration and Response: NewEvol automates the response to current and new threats with a manual or automatic process created by the playbook.  

• Threat Intelligence: NewEvol threat Intel gathers data about existing and new cyber threats from different sources and prioritizes them. The solution generates threat intel reports and automates the incident response process according to the reports. 

• Security Analytics: NewEvol security analytics deploys AI and ML-based algorithms to security operations to gain insights from previously inaccessible data. These insights are useful for SOC teams to drive faster and better decisions. 

Security analytics use cases

• Cloud Security Monitoring: The cloud is essential for the digitalization of an enterprise. It also creates cyber security challenges as the size and power of IT systems are becoming unscalable. Security analytics offers cloud security monitoring that detects threats and protects cloud-based IT infrastructure. 

• Network Traffic Analysis: The visibility of transactional data and events within IT networks is reducing due to populated network traffic. Security analytics provides analysis of network traffic to detect anomalies within the IT environment. 

• Data Exfiltration Detection: Data Exfiltration refers to unauthorized access to data within the networks. Security analytics offers detection of such unauthorized activities and prevents loss of sensitive data. 

• Insider Threat Detection: Insider threats are as dangerous as external threat actors. Insider threat detection analyses log data, email activity, and unauthorized access requests to provide visibility. 

• Incident Investigation: SIEM creates alerts for cyber security breaches and login failures. Sometimes, it can overwhelm the IT security teams by correlation errors. Incident investigation provides contexts of such alerts and finds legitimate security breaches. 

• Threat Hunting: The proactive approach for detecting threats and security breaches within the IT systems. Security analytics can automate the process according to SOC teams. 

Conclusion:

Big data analytics is an essential approach for the success of an organization. NewEvol Big data analytics enhances cyber security with different security analytics tools, AI, and ML-based techniques to protect IT environments from security breaches and cyber threats. The solution prioritizes cyber threats and automates the process to respond with minimum to no human assistance, eliminating repetitive tasks of IT security teams.