With the internet being the nucleus of our world, the risk of cyber attacks has increased exponentially, posing a major threat to the business-critical data and, consequently, the financials of an enterprise.
They increase in sophistication virtually every minute, thereby making it a herculean task to combat them on the go. Sustaining businesses despite such threats is the need of the hour.
Big Data Analytics, however, if smartly deployed, can rise to the occasion and enable stronger cyber-attack resilience.
What are Cyber-Attacks?
Cyber-attacks are deliberate exploitation of computer systems and networks with malicious intent. Their focus is to render networks vulnerable, compromising data and leading to identity theft. Some examples include data breaches, denial-of-service, phishing, worms, viruses, attacks on IoT devices, malware, etc.
Recent cyber-attack instances in India
- A recent cyber-attack that took place in India was deployed on Cosmos Co-operative Bank Ltd. in Pune. By hacking into the ATM and stealing data of debit cardholders, they siphoned off Rs. 94.42 crore.
- In August 2018, two men were involved in activities concerning money transfers from accounts of various individuals by obtaining their SIM card information through illegal means. They were accused of transferring Rs. 4 crore from various accounts.
What does Big Data Analytics mean?
Business information is the most valuable asset of an organization. In today’s world, security and privacy are primary concerns. Businesses need a way to keep sensitive data safe and secure. Big Data Analytics is a complex method of examining data to uncover information such as hidden patterns, unknown correlations, market trends, and customer preferences. Not only that, it also allows businesses to analyze their information and provides hints of any potential threats that might come their way.
Big Data Analytics makes use of machine learning, data mining, artificial learning, natural language processing and statistics to help the organization make informed decisions. The tools used operate in real time and, depending on their severity, alert the user about relevant security concerns. Big Data not only stores large amounts of data but also helps examine, observe and detect irregularities. By predicting intrusions, it helps detect an issue at the earliest.
According to the results of a study conducted by Bowie University, 84% of businesses using Big Data successfully managed to block cyber-attacks with its analytics. In other words, Big Data Analytics is an effective weapon against rising cybersecurity attacks.
Need for cyber-attack resilience:
Every organization needs protection against cyber threats. To defend against the severity of attacks, it is important to have strong systems in place. In simple steps, cyber-attack resilience aims to manage and protect, identify and detect, respond and recover and lastly, assure. It helps in reducing financial losses and protecting the reputation of a brand. Such resilience is needed for confidentiality, integrity and availability.
It is highly important that in the event of an attack or breach, the business remains operational and resumes its services with minimum loss.
How Big Data helps prevent cyber-attacks:
- Analysis of Historical Data:
Since Big Data analyses, collects and processes data based on previous attacks, with the help of machine learning, companies can detect issues with their networks, discover threats in real-time and develop an effective defense. It recognizes the network’s regular patterns and detects deviations in real-time.
- Monitoring Workflows:
By monitoring the work, insider threats can be mitigated. Using specific logins for sensitive data can help prevent cybersecurity breaches. An effective process would help in responding to detected threats efficiently.
- Detection Systems:
Big Data Analytics can help discover irregularities in the working and various suspicious activities. This way, it can prevent a threat before it has occurred. Cybersecurity depends on big data analyzes to quickly detect intrusions and take appropriate steps.
- Intelligent Risk Management:
Cybersecurity mainly relies on actionable intelligence and risk management. Big data analytics tools improve cybersecurity efforts with intelligent risk management insights. Security experts can leverage these insights to interpret data more quickly and easily. As a result, organizations can handle security incidents without any delay.
How to increase cyber attack resilience: To limit the impact of security incidents, the following ways can be adopted:
Allocation of risk and responsibility, identifying critical data and understanding technical measures should be included in any planning process of an organization.
- Identifying risks:
To identify and prioritize organizational threats, an assessment of the organization’s risk is essential. The way you mitigate risks and deal with incidents forms a part of your risk assessments.
- Managing risks:
Prioritizing your data is important. Determination of the probability of occurrence of each risk and its definitive impact is the first step in managing cybersecurity risks.
- Backup solutions:
Having a thorough backup ensures seamless conduct of your business even in case of breach. You could opt for daily backups or weekly backups, depending upon the information your organization deals in.
All businesses, big and small, need to protect their resources. As Big Data identifies risks and vulnerabilities and protects organizational data, detects anomalies, responds and recovers, it proves to be a modern tool in building cyber attack resilience.
(Shomiron Dasgupta is Founder & CEO – DNIF. Views expressed in this article are of the author)