Cyber Security Analytics: The Powerful Combination of Cyber Security and Data Analytics

 

It takes a single vulnerability for the cyber criminal to break into the system and cause massive damage to the business enterprise concerned. With the spiralling complexity of Cyber attacks, it has become indispensable to go beyond the traditional preventive approach towards the PDR (Prevent – Detect – Respond) strategy. This is where Cyber Security Analytics come in. While the presence of data can be an invitation for a Cyber attack; combining Data Analytics and Cyber Security can also help in acquiring insights which can predict, identify and abate Cyber attacks.

In this blog, we will try to answer the question of what is Cyber Security Analytics, consider the different aspects of Data Analytics in Cyber Security, as well as look at the utility of Predictive Analytics in Cyber Security.

What is Cyber Security Analytics?

Cyber Security and Data Analytics: The Mighty Union

Need for Cyber Security Analytics

Data Analytics Cyber Security Strategy

Tools for Conducting Big Data Cyber Security Analytics

Cyber Security Analytics: Use Cases

Benefits of Employing Data Analytics in Cyber Security

Conclusion

What is Cyber Security Analytics?

Cyber Security Analytics is an advanced approach to Cyber Security which makes use of the processes of data gathering, aggregation, attribution and analysis; for deriving valuable insights. These insights in turn help in executing crucial security functions which help in identifying and abating cyber attacks and threats. Big Data Cyber Security Analytics solutions help in aggregating data from multiple sources like business applications, virus scanners, operating systems event logs, behavior data and so on. Organizations try to collate this data into a single data set which can be used by security experts for the application of appropriate searches and algorithms (data analytics) for the prior identification of cyber attack indicators.

Thus, Data Analytics in Cyber Security help security analytics experts to identify potential threats at an early stage and subsequently provide them with the chance to abate them before they manage to creep into the network infrastructure, and result in data loss or breach or data leakage. 

Cyber Security and Data Analytics: The Mighty Union

Cyber Security Analytics, Security Analytics or Big Data Cyber Security Analytics are different names for the single phenomenon of Cyber Analytics which is the child of the marriage between Cyber Security and Data Analytics. Data Analytics deals with data management through its collection and storage, along with the techniques, processes and tools, which help in analyzing it. The main purpose is to derive actionable insights which could help in guiding business decisions, making predictions as well as improving its efficiency. Cyber Security Course deals with providing protection and security to servers, computers, mobiles, programs, systems and networks; with the goal of defending them against malicious digital attacks.

Following the above definition; Cyber Security Analytics can be understood as making use of the power of Data Analytics for attaining a Cyber Security objective. When you use Data Analytics with the aim of comprehending data in a way which can diagnose weakness, elucidate risks, make predictions for possible malicious attacks and recommend protective measures; you are indulging in Big Data Cyber Security Analytics.

Need for Cyber Security Analytics

In this section we will look at some of the factors which have propelled the emergence of Big Data Cyber Security Analytics.

·         According to BARC and KuppingerCole, “Big Data and Information Security” study, “only 6% of companies say they aren’t exposed to any cyber security risks”, and, “62% say digital security threats have increased in the past 12 months” ( http://barc-research.com/research/big-data-and-information-security/ )

·         Cyber Security Analytics provides for data structuring in a way that it helps in a unified view of security breaches and threats which in turn allows for improved planning and timely resolution

·         Advancement in the frequency and sophistication of Cyber attacks has been one the major propellers towards a Data Analytics Cyber Security mechanism. A strategic policy of Cyber Security and Data Analytics taken together help in maintaining a track of threat patterns and thereby issue alerts on the event of any anomaly

 Data Analytics Cyber Security Strategy

Trying to incorporate Data Analytics in Cyber Security framework, entails the need to develop a proactive strategy. This plan of action can take the following path:

·         Data Acquisition

It is important to collect all relevant data throughout the network of an organization into a single dataset. The data can be stored in cloud based repositories and at locations from where they could not be easily accessed by cyber criminals

·         Classifying and Filtering Data

You will be required to normalize data through the application of conventional security taxonomy. Grouping can be carried out for fields with common values which automatically have common names. This helps in streamlining search capabilities

·         Additional Data Gathering

Collection of as much data as possible will help in unlocking new capabilities. It can provide for the application of stringent detection techniques as well as help in the extraction of contextual insights

·         Improve your Security Data

Embellish your security data with data from internal sources like website data, business tools and so on; as well as from external sources like machine data, open source feeds and so on

·         Automating the process of Cyber Security Analytics

The accomplishment of the goals of Cyber Security and Data Analytics is dependent to a large extent on automation. This is because it is important to derive insights in real-time. Automation not only ensures timely extraction of data and insights from the same; but it can also be strategically used to issue a relevant response on the event of a cyber threat

·         Identify and Detect

This stage involves the usage of different techniques and strategies for threat detection, refining queries and carrying out research. At the same time, it is important to identify the right form of detecting strategy. For instance, a statistical approach will be more suited to observe situations wherein there has been an unlikely spurt in network traffic

Tools for Conducting Big Data Cyber Security Analytics

In this section, we will look at some of these Security Analytics solutions.

·         Security Orchestration, Automation and Response (SOAR)

This Cyber Security Analytics solution can be considered as a nodal tool which seeks to establish connections between the processes of data gathering, the process of analysis and threat response applications.

·         Behavioral Analytics

This method seeks to indulge in Predictive Analytics in Cyber Security through examining and analyzing the behavioral patterns of devices and users. These patterns are studied in order to develop generalizations and consequently detect anomalies.

·         Forensics

Forensic Big Data Cyber Security Analytics tools help in digging into attacks which are ongoing or have happened in the past. They also help in determining the ways in which the flaws of the system were exploited by cyber criminals as well as seek to detect potential vulnerabilities which could harm the organization in future.

·         Security Information and Event Management (SIEM) Platform

The SIEM platform helps in collaborating an array of Cyber Security Analytics tools for the purpose of collecting security data across the network infrastructure as well as aid in analysis and provisioning alerts on detection of possible threats.

·         Network Analysis and Visibility (NAV)

This tool is concerned with supervising traffic as it flows across the network. It deals with flow data analysis, network forensics, network discovery and network metadata analysis.

·         Threat Intelligence Software

These Cyber Security Analytics solutions help in providing valuable information about the most recent developments in the field of Cyber Security. These include information about zero-day attacks, new malware, other forms of unusual activity and so on. This helps security analysts to be better prepared for any impending attack or threat.

Cyber Security Analytics: Use Cases

In this section we will look at some of the use cases of Big Data Cyber Security Analytics.

·         Scrutinizing Network Traffic

Data Analytics in Cyber Security help you to acquire a glimpse of your network traffic and thus provide you with the ability to identify any kind of network anomaly.

·         Detection of Insider Threats

Data breach or leakage can also be an intentional act of malicious insiders who possess access to sensitive data in the form of network credentials. Data Analytics Cyber Security tools can be utilized for sensing insider threats through keeping tabs on such activities as abnormal email usage, unsanctioned database requests, unusual login times and so on.

·         Unwarranted Data Access

Unapproved data exfiltration can happen as a result of data theft or data loss. Cyber Security Analytics solutions can help in obstructing unlicensed channels of communication and prevent individuals from giving in their credentials to barred sites.

·         Observe User Behavior in order to Perceive Threats

Data Analytics Cyber Security makes use of user and entity behavior analytics (UEBA) in order to develop algorithms which can help in discerning patterns of mischievous activity in user behavior.

Benefits of Employing Data Analytics in Cyber Security

Combining Cyber Security and Data Analytics into a robust mixture help in strengthening the digital security mechanism through early detection of threats and timely precautionary measures taken for the same.

·         Threat Intelligence Automation

Automating the process of detecting threats is one of the significant benefits of Security Analytics. It not only helps in cutting down the amount of time spent in manual security activities, but also enhances accuracy as well as helps in monitoring large volumes of data.

·         Forensic Investigation

Cyber Security Analytics does not provide for random exposition of cyber threats and attacks. It helps in a detailed exploratory analysis of the origin of the attack, its severity in terms of impact, data affected as well as the way in which it happened.

·         Prioritizing Ability

The combination of Cyber Security and Data Analytics is a potent force which not only helps in early detection and resolution of security issues; but also provides for prioritization of alerts by ranking vulnerabilities. This helps security personnel in directing their attention to areas which are in need of immediate attention.

·         Ensuring Regulatory Compliance

There do exist industry standards and government compliance regulations such as HIPAA, GDPR, PCI-DSS and others. By way of overseeing access, behavior, and a unified view of data; Cyber Security Analytics help compliance managers to detect possible instances of non-compliance.

Conclusion

The robust combination of Cyber Security and Data Analytics has helped to utilize the positive aspects of both domains. Analyzing data not only helps in better preparedness, but also provides for early detection of threats as well as helps security analysts to come up with advanced response and mitigation strategies.

Given the dynamic nature of the domain, a career in Cyber Security is one of the most alluring fields within the tech industry. We, at Syntax Technologies, provide you with an exciting opportunity to acquire skills in consonance with those of a Cyber Security expert.