Skip to main content

Security Analytics Market to Gain Traction Across Healthcare Sector

The global market for security analytics solutions and services is set to churn out massive profits in 2021 and beyond. Here’s how:

The 21st century is no doubt one of the profitable eras for large-scale digitization. With massive shifts toward digital platforms being a protocol of the current COVID-19 age, digitization has, perhaps, touched the apex. From brick-and-mortar stores to best infrastructure offices shifting to online platforms, COVID-19 has turned digital platforms from convenient option to a “must have” for these organizations. However, has digital transformation really streamlined the business operations?

Answers to such questions are quite subjective. While some might nod to the claims, others would still be skeptical of the fact; reason being the increasing rate of cybercrimes. Arguably, a stellar growth in digitization is also set to bring in the increased risks of cyberthreats. 

U.S. FBI’s Internet Crime Complaint Center (IC3) had announced receiving more than 2,000 cybercrime complaints every day in 2020, totaling to 791,790 for the year since the outbreak of COVID-19. This represented a 69% spike in the number from the previous year. 

Moreover, about 88% of the organizations worldwide had experienced spear phishing attempts in 2019. 

In this regard, organizations have been calling for a robust solution which would help them undertake proper precautions to restrict the unauthorized access to their IT systems, paving way for the adoption and development of security analytics tools and solutions. 

Why Security Analytics?

The need for security analytics technologies is expanding in the current era. This is mainly due to phenomenal benefits. These include faster detection and remediation of cyber threats, real-time visibility to analyze, detect, and adapt to future threats, robust tracking and reduction of insider frauds, threats, and data leakage, and cost-effective deployment, amongst others.

How Is the Industry Responding to Increasing Demand for Security Analytics?

Cybercrime is one of the pressing challenges of the world today and in midst of this, various cybersecurity companies are going all the way to introduce decent developments in the space to enable organizations to become less vulnerable against cyberattacks.
 
One such company, Exabeam, a prominent security analytics and automation leader, launched its two new robust cloud-delivered security products: Exabeam Fusion XDR and Exabeam Fusion SIEM. These novel additions to the Exabeam portfolio are deemed to be highly efficient in solving threat detection, investigation, response without disturbing the organization’s existing technology stack. 

The Fusion product line displays an open-system approach to extended detection and response (XDR) and security information and event management (SIEM) allowing any organization to procure an advanced TDIR layer on top of the existing security and IT stacks. 

What has been driving the large-scale deployment of these solutions is the convergence of big data analytics. In 2020, Amazon Web Services rolled out Amazon HealthLake, a HIPAA-eligible service that aims to support interoperability standards and further drive the use of big data analytics in healthcare. Similar developments worldwide will expand the focus on security analytics solutions to ensure a smooth and safe data environment.

Big Data Analytics and Machine Learning in Security

Security analytics is a proactive security approach that makes use of big data analytics and machine learning capabilities to categorize, accumulate and analyze data gathered from network devices to detect threats. Importantly, about 97.2% of global organizations are investing in big data and AI to alleviate the chances of cyber frauds. 

Big data analytic solutions use advanced data science and statistical models to detect faults in real time for threat analysis. These solutions generate security alerts while combining them with additional forensic data to respond to cyber threats. These solutions help diverse organizations by aiding in monitoring for insider crimes. 
To expose the suspicious behavior, AI and data analysis can predict attacks and create baselines for normal activity. Machine learning involves training computers against data sets, enabling them to detect patterns.

Security analytics leverages this technology, combined with additional data science-driven statistical modeling capabilities to detect both unknown and known patterns with an advanced degree of accuracy. 

Reportedly, big data analytics is revolutionizing the healthcare industry to offer effective services to the society. Compromise on 9.7 million healthcare records, during 2020 alone, is impelling the need for security analytics in the healthcare sector. COVID-19 has brought in multiple cybercrimes in various healthcare industries. According to HIPAA Journal, 83 anomalies were attributed to hacking incidents and about 9,662,820 records were exposed in those breaches during September last year. 

Luxottica’s cybercrime incidence is considered to be one of the worst e-virus attacks in 2020. In August last year, the attacker had got into the web-based appointment scheduling application managed by Luxottica. It was found that vital information about prescriptions, data and time of appointment of over 892,000 patients were compromised. 

These statistics imply that the healthcare sector is a target for malicious attackers for the type of data that providers and payers hold. It’s a challenge across the industry to deploy adequate data security controls as well as access management controls to make sure that malicious attackers are not able to get in the secure healthcare network. 

Recently, Gravesham NHS Trust and Dartford, a leading cybersecurity and threat intelligence company, turned to Cylera to secure extensive healthcare IoT device ecosystem to secure the patient’s crucial and confidential data. Security analytics can help IT departments in various organizations make sense of the volumes of data flowing in and out of its network and quickly identify the treats posed by outside attacks.