In a world where digital transformation is accelerating, the stakes for safeguarding critical infrastructure, government systems, and financial services have never been higher. These sectors are increasingly targeted by sophisticated payment fraud schemes and AI-powered cyberattacks, leaving them under immense pressure to shield their customers from threats. With the global cost of cybercrime projected by Cybersecurity Ventures to hit $10.5 trillion USD annually by 2025, organizations must be more vigilant than ever.
Recent data paints a clear picture of this escalating threat. The 2023 Cybersecurity Almanac by Cybersecurity Ventures revealed a major surge in high-volume, large-scale attacks such as distributed denial-of-service (DDoS) incidents. In a DDoS attack, there is a malicious attempt to disrupt the normal traffic of a targeted server, service, or network by overwhelming it with a flood of transaction traffic. This is achieved by utilizing multiple compromised applications, IoT devices, or computer systems as attack vectors, which are part of a larger hijacked network called a botnet.
DDoS attacks result in the disruption of online services, including banking portals, payment systems, and mobile apps. This affects customers’ ability to conduct transactions, check account balances, or perform any financial activities, leading to customer frustration, loss of trust, and, ultimately, a decline in revenue. Additionally, DDoS attacks can serve as diversionary tactics to conceal more malicious activities, such as data breaches or fraud. While the institution is focused on mitigating the DDoS attack, cybercriminals may exploit security gaps to infiltrate networks, steal sensitive information, or commit financial fraud.
Cyberattacks are on the rise and becoming harder to defend against
AI-powered DDoS attacks have been on the rise since 2020. Generative AI is being used to create increasingly complex and harder-to-detect attack patterns that automatically identify vulnerabilities in systems and launch without human intervention. These clever attacks avoid triggering typical security alarms by closely mimicking normal traffic flows and emulating human behaviour, making attacks harder to detect and mitigate.
Generative AI is also being used to optimize botnets, meaning the number of requests that can flood a targeted server have grown exponentially. One standout example is the Google attack in August 2023, which hit a record 398 million requests per second – a staggering 7.5 times larger than the attack they encountered in 2022, which peaked at 46 million requests per second.
These AI advancements make it more challenging to identify the true source of a DDoS attack using traditional tools such as Content Delivery Networks, load balancing and rate-limiting – before major damage is done.
Sense and respond: A new approach for new threats
Traditional approaches to mitigating DDoS attacks are still important. However, to ensure business continuity and protect against increasingly sophisticated cyber threats, organizations must be equipped with a new generation of solutions designed to detect, prevent, and shield themselves from the risks of DDoS attacks in real-time. These solutions leverage comprehensive network-level intelligence in combination with the application file system and log data derived from HPE NonStop servers to provide complete, end-to-end visibility into the transaction journey. This whole new level of visibility provides a formidable defense against cyber threats, empowering organizations to adopt a proactive “sense and respond” approach to monitor and block DDoS attacks within an HPE NonStop ecosystem.
Data precision for cyber-crime detection and prevention
Effective cyber-crime detection and prevention hinge on quality data. The integration of cutting-edge tools with this data, including real-time alerting, unsupervised machine learning models, automated fraud case management and individual transaction blocking provides the ultimate defense against emerging fraud and cyber-attacks across your entire HPE NonStop ecosystem.
Here are some ways that measuring, monitoring, and mining your HPE NonStop data in real-time, combined with an extended sense of network, helps you stay ahead of new cyber-crime threats, secure customer trust, and maintain seamless operations in a financial or government services environment:
Continuous transaction monitoring
The ability to gather and correlate both HPE NonStop and network-level data in real-time – across all the network links and hops of every transaction journey – gives you a powerful data advantage over fraudsters. This means you can monitor transactions and immediately unlock data insights to reveal heightened risk indicators and compromised systems or switches anywhere along the transaction journey. The more data you have, the easier it is to independently audit transactions, reduce false positives, and deliver a safer, more reliable customer experience.
Detection and prevention extend to many payment fraud, internal fraud, advanced persistent threats, and cybercrime use cases, including:
- Payment fraud – Card present, card not present, account takeover, stolen cards, direct debit and payment card fraud, skimming
- Internal fraud – Fund transfers, transaction message adulteration, remote malware distribution and control
- Advanced persistent threats – Man-in-the-middle attacks, cash-out attacks
- Cybercrime – BIN attacks, rogue terminal attacks, credential stuffing attacks, and DDoS
Advanced AI and machine learning models
Access to transaction details, including granular HPE NonStop application and network-level data fields, is a goldmine when it comes to AI. For example, this data can be used to feed individual, self-training machine-learning models that generate unique profiles for every user, card, terminal, and device. The detailed data fed into these models can trigger automatic updates to the models to achieve greater precision in behavioral analysis, risk scoring, and fraud detection. This data can also be used to automate fraud case management or block/pause individual transactions based on field-level data details – without disrupting the entire network or causing a negative impact on legitimate transactions. This can be done without the need for expensive data scientists to retrain models.
Enhanced analytics and real-time insights
Identifying new cyber-fraud patterns and addressing emerging risks demands a higher level of transaction visibility. By leveraging deep analytics from both HPE NonStop application data and network-level data, you gain the flexibility to implement precise cybersecurity and fraud rules for new threats and minimize financial losses while ensuring maximum availability and approval of legitimate transactions. Once you identify emerging attack types and patterns, you can generate visual dashboards and reports to update risk analysts, communicate new controls, and launch targeted awareness campaigns effectively.
Real-time cyber-attack detection and prevention without performance impact
HPE NonStop users have access to partner solutions such as INETCO BullzAI that are specifically designed for high transaction volume environments, providing advanced sense and response capabilities for intelligent network defense. Real-time, out-of-band monitoring ensures that the data collection, decoding, and correlation of application-level, network-level, and payload intelligence occurs outside the main transaction path, preserving the speed and availability of your HPE NonStop system.
By combining HPE NonStop data with network and transaction payload intelligence, organizations can take more immediate action against cyber threats. Advanced machine learning models can utilize this data to identify even the most sophisticated DDoS attacks and fraudulent transactions in real-time. Not only can you swiftly pinpoint DDoS attack sources, but you can also automatically block individual transactions associated with other fraud scenarios such as insider attacks – all while letting legitimate transactions proceed seamlessly.
Ready to outsmart cyber threats without slowing down your systems?
In today’s world, where digital security is crucial, staying ahead of fraudsters and safeguarding essential services is more than just a necessity—it’s a strategic must for maintaining trust and operational resilience. You must be ready to detect and prevent cyber threats instantly without compromising the performance or integrity of your critical systems. A sense and respond approach fueled by independent, out-of-band data collection, measurement, and monitoring, especially in an HPE NonStop environment, offers significant benefits, such as minimal impact on system performance, enhanced cybersecurity, and improved fraud prevention capabilities.
By integrating real-time measurement, monitoring, and mining of HPE NonStop application, network, and transaction payload data, you can build an intelligence foundation that is essential for protecting your mission-critical operations against AI-driven threats like crippling DDoS attacks and insider fraud risks. Embracing advanced tools that provide holistic visibility into every step of the transaction journey will help you eliminate cyber-fraud, stay compliant, and keep the vital services your customers depend on running smoothly.
Be the first to comment