It’s common for organizations to have a false sense of cybersecurity. However, attackers can easily evade previously effective security controls – especially in the era of hybrid working. And, as more and more IoT devices are being connected to networks, a lack of security on these devices can turn them into potential attack vectors too.The highest number of newly discovered security vulnerabilities on record was recorded in 2021 – and this trend isn’t likely to change.So, the threat landscape for organizations is rapidly evolving as they become more reliant on remote access and distributed computing resources to conduct business, all while their traditional network security fails to detect these new vulnerabilities.Next-generation security leads the way Modern attack tactics include reusing stolen credentials, exploiting zero-day vulnerabilities, employing ransomware, and exploiting trusted insiders. In response to these threats, a new generation of cybersecurity solutions uses real-time predictive methods such as machine learning, AI and behavioral analytics to prevent breaches quickly and efficiently.The term “next-generation security” also extends to automated threat detection and response capabilities. These tools can uncover emerging attacks and detect advanced persistent threats while flagging new indicators of compromise (IoCs) and applying knowledge of attackers’ tactics, techniques and procedures (TTPs) in real time.Examples of IoCs are malware signatures and malicious internet protocol addresses or domains. TTPs contain knowledge about adversary behavior gained from the analysis of individual cybersecurity incidents.Interconnectivity is therefore an important aspect of security intelligence, as it allows IoC and TTP repositories to be continually updated from threat intelligence feeds. Interconnected, predictive and automated The traditional notion of threat intelligence has evolved into a new tier of interconnected, automated and predictive security intelligence. So, how do these next-generation measures get the job done?They use a range of tools to eliminate false positives and help organizations classify and prioritize threat information. The tools include endpoint detection and response, sandboxing, visibility, next-generation firewalls or anti-virus software, patch management, data-loss prevention, device control, honeypots and cloud antivirus.These security offerings also facilitate innovative strategies to protect business endpoints and prevent unauthorized activities – again, by making use of machine learning and AI.They control which applications can gain access through an organization’s firewall to minimize the avenues of attack, and they bring together cloud-based threat intelligence, predictive analysis, and human and technical defenses to systematically prevent sophisticated multilevel attacks.They help organizations determine potential vulnerabilities to help counter threats immediately. Machine intelligence applies deep learning models to large data sets and learns the characteristics of malicious patterns such as malware signatures and bad URLs.They are also essential in analyzing breaches to help organizations identify and remediate the root cause of any cyberattack.Organizations can reduce alert fatigue and time to remediate by automating menial, repetitive and time-consuming actions that were typically performed by security operation teams and creating playbooks to help orchestrate security automation.These tools can provide end-to-end visualizations of an organization’s network topology and cloud assets, enabling a holistic approach to cloud security.Through AI and deep learning, they can produce predictive cyber-risk scores for detected threats so that organizations can prioritize their resources and address the highest risks first.Examples of next-generation security technologiesThe shift to hybrid work and increase in cloud adoption have established identity as the new enterprise network perimeter, shifting it far beyond the organization’s usual boundaries.New security frameworks include zero trust, which verifies upon each and every connection request that there really is a valid and authorized user behind that request.Security solutions using user and entity behavior analytics (UEBA) can flag deviations from normal behavior in real time to be evaluated by machine-learning algorithms. These algorithms compare current and standard user or entity behavior to detect anomalies and enable organizations to prioritize security alerts.Identity threat detection and response (ITDR) software adds layers of defense by efficiently detecting and responding to identity-based attacks.Then, the intelligence provided by extended detection and response (XDR) solutions can help defenders identify and respond to suspicious activity before adversaries can infiltrate a network to a significant degree.Deception technology blankets a network with deceptive credentials, shares, bait and other decoys that are aimed at drawing an attacker’s attention early in the attack lifecycle.For superb security, don’t go it aloneMultiple security products can also be combined into one platform that presents a range of incident detection and response options. But even running just one or two of the latest security technologies efficiently in-house can be complicated for most organizations. They often need help to find the most cost-effective and fastest ways of deploying next-generation security technology. Managed service providers like NTT can quickly provide these capabilities and the tools and practices needed to safeguard new digital ways of doing business. Read more about NTT’s Managed Cloud Security Services.