How can big data analytics help businesses overcome cybersecurity challenges?
Cybercrime has plagued the internet since its inception and over the years, cybercriminals have been becoming craftier, creating more complex cybersecurity threats.
Businesses are one of the main targets of cybercrime. In Australia, cyber attacks cost businesses approximately $29 billion every year and many are left crippled and unable to recover.
Fortunately, modern businesses have bolstered their defences against cyber attacks through cybersecurity infrastructures. Despite this, however, cyber threats are always evolving, becoming more aggressive and complicated, forcing businesses to keep updating their cybersecurity measures frequently.
While big data analytics have helped businesses improve many of their functions like sales, customer service and workload management, it can also help them improve their cybersecurity infrastructure.
Here, we’ll take a look at how big data analytics can help businesses overcome the challenges of cybersecurity.
Analysing historical data
Historical data is a treasure trove of information for businesses. Just like finding patterns in sales and consumer buying patterns, businesses can use big data analytics to discover meaningful connections between past and present cyber attacks and find ways to make their cybersecurity stronger against these cybersecurity threats.
Big data analytics on historical data can also allow businesses to predict future threats. By analysing statistical information, businesses can identify patterns that deviate from the norm, helping them predict an imminent cyber attack.
Businesses can also pair risk assessment with quantitative data analysis to predict its susceptibility to potential cyber attacks, and using the insights they gain from this analysis, they can develop countermeasures against future attacks.
A great way for businesses to leverage their big data analytics is by incorporating machine learning; with machine learning, businesses can develop new responses to cyber attacks using the information collected and analysed from past attacks.
Monitoring work activities
Research has shown that many data breaches in businesses may have actually been carried out by an employee, though in most cases, cybercriminals may gain access into a company’s network by hacking an employee’s account and posing as their victims.
Most of the time, an employee might not even be aware that their account was hacked.
With big data analytics, businesses can monitor workflows to detect any suspicious activity in their company network. For example, the business can analyse data based on employee movements during work hours and the data they accessed or changed during their work tasks to check for any usual behaviour, like opening confidential files without authorisation.
When suspicious logins and unusual activities on the company’s network are detected, the business can take action by identifying the threat and stopping it before it happens.
Improving intrusion detection
Identifying possible weaknesses in a business cybersecurity infrastructure in real-time is very difficult; using big data analytics, businesses can automate this process and analyse logs, workflows and events to identify any usual activities and irregularities in data.
Cybersecurity breaches are becoming more complex and due to this, intrusion detection systems such as NIDS (Network Intrusion Detection Systems) have become more powerful and sophisticated in detecting cyber threats.
Real-time big data analytics can be used to enhance these systems and give them a more comprehensive way to detect possible threats and put a stop to them before they gain access to a business network.
Identifying important incidences
Big data analytics can be used to analyse historical data and use the insights gained to improve a business cybersecurity infrastructure. The problem, however, is finding data on the relevant cybersecurity-related incidences.
Historical data, even that of a small business, can be vast, so finding the most important cybersecurity data from this sea of raw information can be tricky.
With big data analytics, businesses can filter and categorise data so that it’s easier to identify important cybersecurity-related data from the past and their relationships with other relevant historical data.
Keep your business safe from cyber threats with big data analytics
Big data analytics has opened new avenues for businesses all over the world. From marketing to cybersecurity, the number of things businesses can improve with big data analytics is endless.
Keep your business ahead of the competition and safe from cyber threats with help from big data analytics.