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How Big Data Helps Us Understand Denial of Service (DoS) Attacks

In this special guest feature, Dr. James Stanger, CompTIA Chief Technology Evangelist, highlights how big data is a concept that can provide insight into DDoS attacks and equip companies with the tools they need to effectively combat this threat. James works with information technology (IT) subject matter experts, hiring managers, CIOs, and CISOs worldwide. He has a rich 25-year history in the IT space, working in roles such as security consultant, network engineer, Linux administrator, web and database developer, and certification program designer. He has consulted with organizations including Northrop Grumman, the U.S. Department of Defense, the University of Cambridge and Amazon AWS and is a regular contributor to technical journals, including Admin Magazine, RSA, and Linux Magazine.

Denial of Service (DoS) attacks have been a threat to both large and small businesses around the world as early as the Morris Worm in 1988. Ever since, attackers have refined these types of attacks. In the late 1990s, we saw attackers create the first serious Distributed Denial of Service (DDoS) attacks, and they haven’t looked back. With technology developing at an unprecedented rate, most businesses truly going online and the very nature of the internet itself, DDoS attacks are now more dangerous than ever before. Furthermore, the COVID-19 pandemic forced businesses from all sectors into digitalization, thus expanding the playing field for hackers.

What was once just a nuisance for larger organizations or certain business sectors is now proving to be an existential threat to  organizations worldwide. DDoS attacks can flood servers with huge amounts of fake internet traffic, causing them to be overwhelmed and essentially stop functioning.

Some attacks don’t even require large volumes of packets – just a few malformed packets can crash essential business servers. The problem is many DDoS attacks are relatively simple to create. But, they are as simple as they are effective. Single attackers, or groups of attackers, have been able to take down websites and operational structures, virtually crippling governments, free speech movements, militaries and global businesses. DDoS attacks are difficult to anticipate and hard to mitigate, and modern companies are not doing nearly enough to protect themselves.

However, the implementation of big data practices and multi-layered security systems shows some promise in dealing with this problem. In this article, we will take a closer look at how DDoS attacks have evolved and why modern security solutions do not offer the needed protection from them. We will also explore how big data can be used to combat this ever-growing threat.

DDoS Attacks Are Becoming More Sophisticated

Over the last decade, hackers have managed to evolve their DDoS attack methods to an incredible level. The interconnectivity and increased connection speeds overall have helped tremendously — DDoS attacks have gone from Mbps and Gbps to staggering Tbps in what appears to be mere months. The rise of the internet of things (IoT), ubiquitous connectivity and now, 5G networks are three factors that have greatly contributed to the rapid growth and increased sophistication of DDoS attacks.

It almost seems like hackers have managed to upgrade their methods to include cloud functionality before companies transitioned from scale-up architecture to scale-out architecture. As a result, even specialized security solutions fail to adequately detect, prevent and mitigate today’s DDoS attacks.

Big data is a concept that can provide insight into DDoS attacks and equip companies with the tools they need to effectively combat this threat. Another important tool for mitigating DDoS attacks is the use of multiple, redundant systems and cloud-based data scrubbing platforms that can filter out DDoS traffic. However, hackers have businesses beat when it comes to the early implementation of big data methodologies.

Advantages of Big Data Methods and Analytics

The term big data covers a wide range of concepts, but it essentially means the large volume of structured and unstructured data that businesses encounter on a daily basis. However, it is not just about the amount of data, but how information gleaned from data can be utilized to improve business decision making, security, and the overall productivity of an enterprise. In many ways, the concept of cybersecurity analytics is coming of age to include more data-driven approaches to various security issues, including DDoS attacks.

Big data analytics gives us the ability to acquire large volumes of raw data from a variety of sources and turn it into projections, predictions and trends with incredible accuracy. The recent growth in cloud, mobile and social activity allows us to extract actionable insights using big data methodologies and tools.

Since modern DDoS attacks include a flood of information from thousands of sources, processing all this information is only possible via a big data solution. Aggregating data from a large number of sources in real-time is key to building effective countermeasures and monitoring systems, as well as preparing a system to respond better to future attacks.

How Can Big Data Help Understand and Fight DDoS Attacks?

Introducing big data into the security stack of a business can greatly expand its ability to detect, analyze and even prevent DDoS attacks. Enterprises that are not prepared to handle the big data generated by the IoT botnets that execute massive DDoS hacks can become victims of attacks at unprecedented, terabytes-per-second speeds.

Traditional security methods are limited in their efficiency by storage and memory restrictions. In order to adequately assess DDoS attacks, large volumes of data need to be analyzed and stored. With big data, companies can maintain comprehensive logs of IPs that have been a part of DDoS attacks in the past. Those logs can then be used as a baseline for adaptive evaluation and more efficient monitoring and threat detection. Information from these sources can help organizations of all types apply more appropriate security controls earlier, and faster. This approach can help organizations become more proactive and truly data driven. As a result, organizations can be more nimble in their DDoS mitigation attempts and responses.

Big data applications are exclusively based on cloud technology. The APIs through which they operate allow for adaptive response to DDoS threats, not just execution of static security policies. Additionally, big data offers insights into much more comprehensive information than just the IPs of the attacker. With such a solution, security teams can get access to data regarding network performance, devices and interfaces used and routing information.

A key factor to detection and prevention of DDoS attacks are comprehensive raw data logs that can be used for analysis. As the name implies, big data structures are capable of handling gigantic amounts of information, making evaluation and benchmark-setting possible.

Reporting is another important aspect in which big data can be of help. While traditional security solutions include minimal logging and just a few summary reports, big data analytics generate in-depth analysis that can provide insights into a variety of important information. Overall, big data implementation provides a sharp increase in an enterprise’s capabilities to combat DDoS threats.

Even Out the Playing Field with Cloud-Based Big Data Solutions

As DDoS attacks are evolving and becoming more sophisticated, companies must catch up when it comes to security measures. Nowadays, no company is safe from this threat and even a small attack has the potential to disrupt operations and hurt the bottom line of a business.

Adapting cloud-based big data solutions will help enterprises bridge the gap between them and the hackers, evening out the play field. Big data allows us to take a closer look at how DDoS attacks are executed and use this information to detect, prevent and mitigate subsequent attempts.

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