Artificial Intelligence Combined With MXDR Can Protect All Your Digital Assets

Organizations must bridge the gap between attack detection and response speed to manage modern cyber threats successfully. Combining MXDR services with artificial intelligence capabilities can enable companies to realize a cyber defense strategy capable of keeping up with the accelerating speed of today’s cyber-attacks.

Undoubtedly, traditional threat monitoring solutions are slow in detecting attacks and have an even slower response. They are designed to use pre-defined rules or signature databases to detect security threats and are more focused on compliance requirements. Such an approach is incapable of protecting all the digital assets deployed in your organization.

The Evolving Threat Environment for Digital Assets

Modern threats are evolving at an unprecedented pace since attackers are leveraging advanced technologies like machine learning to create new, never before seen, stealth attacks and malware. The emerging cyber threat landscape for digital assets is no match for conventional cybersecurity practices operating in organizations today. Increased reliance on the Internet of Things (IoT) and smart devices in the workplace has weakened network perimeters as they provide hackers with multiple points of entry. The number of attacks is also on the rise as attack patterns have changed drastically since cyber adversaries use AI-based attacks to evade detection. Moreover, in 2020 “Criminals perpetrating cyberattacks keep shifting their strategies to expose new vulnerabilities.” In addition to that, present-day hackers are approaching their activities with a business-like mindset, streamlining the process of deploying malicious code and targeting their victims.

The application of newer technologies has further enabled malicious cyber actors to customize an attack to fit a specific organization’s context. At the same time, cybercriminals can automate the customized attacks to scale their execution in different companies. For example, phishing bots created using AI can learn an email conversation and continue on the same subject. Users on the other end may end up revealing sensitive information without realizing they are talking to a bot. CISOMAG published an article noting that hackers can use AI technologies to create malware capable of mimicking trusted system components, enabling them to execute undetectable attacks that blend with an organization’s security environment. Such attacks can target specific employees or departments, leading to financial or data loss. With other types of attacks leveraging machine learning and deep learning capabilities, traditional cybersecurity tools are incapable of protecting your digital assets.

Combining Artificial Intelligence with Managed eXtended Detection & Response (MXDR) – Empowering Organizations to Know the Unknown

A strong MXDR platform can monitor and detect threats in real time within a company’s IT asset portfolio and respond appropriately. MXDR services address challenges faced with traditional cybersecurity tools by enabling quick detection and resolution to threats. Some of the more sophisticated MXDR platforms employ AI capabilities to protect organizations from advanced threats and highly complex attack techniques. The Securus360 MXDR platform, for instance, combines artificial intelligence, human intelligence, machine learning, and security automation to ensure swift threat detection and rapid response to interrupt an offensive campaign before it can impact critical digital assets.

Combining MXDR with artificial intelligence provides proactive threat hunting capabilities to detect hidden and unknown threats in a digital environment, rather than waiting for a threat alert to show up indicating a potential attack. AI-based MXDR models utilize machine learning algorithms and data science models to identify and stop anomalous or suspicious events. The following reasons elaborate on the benefit of using an AI-enabled MXDR platform to monitor and protect your digital assets.

1. Enhancing Cyberdefense Effectiveness

Companies today collect massive amounts of data from numerous areas to run business operations effectively. With a vast array of data points, cloud computing, and a massive number of endpoints to track, 56 percent of organizations say their cybersecurity analysts are overwhelmed with 23 percent lacking the capabilities to investigate all identified incidents successfully. Attackers can exploit the opportunity by directing malicious data to an organization and using it to breach a protected network. AI-powered MXDR solutions utilize omnichannel analytics to filter and process organizational data and data collected from other sources, including network endpoints, user behavior & access, security devices, applications and cloud instances. MXDR leverages artificial intelligence to detect potential breaches, vulnerabilities, and threats. A recent Cap Gemini survey revealed that 69 percent of senior executives see AI as essential for battling cyberattacks.

The application of machine learning algorithms reveals unusual data patterns from internal or external sources. Qualified cybersecurity teams composed of various specialists act on the data analysis insights to identify threats to organizational cybersecurity posture and deliver an enhanced, holistic cyber defense. For example, an AI MXDR platform like that offered by Securus360 can analyze possible threats and existing vulnerabilities relevant to specific digital assets and anticipate known or unknown threats before an attack. Hunting down threats and evaluating security logs or events using real-time AI rules can identify instances of compliance violations and attacks. Detecting and addressing threats in real-time enables companies to enhance the effectiveness of their cyber defenses.

2. Analyzing Data Patterns to Detect Unknown Attacks

Combining MXDR with AI empowers organizations to identify unknown threats before an actual attack impacts data and essential IT infrastructure. AI provides machine learning algorithms that analyze past data of recorded attacks and use the knowledge to learn attack patterns continuously. Continuous learning builds on the knowledge and uses it to detect an intrusion, whether known or unknown. Supervised machine learning algorithms use colossal training data sets of past intrusions to build knowledge to detect advanced malware attacks. Due to challenges in obtaining the training data, unsupervised algorithms are employed to identify outliers in data obtained from various clustering algorithms. Unusual datasets are subjected to further analysis to establish if they are attacks.

3. Detection of Abnormal User Activity Using AI

Insider threats are the most dangerous since there is no telling when a malicious insider will strike. Fortunately, an AI-enabled MXDR can learn the standard user patterns when accessing crucial digital assets. The MXDR profiles user access to various IT assets and data and use the knowledge to detect abnormal user behavior if there are deviations at any time. The MXDR platform flags unusual user access or activities, allowing security analysts to conduct further investigations to determine if the alert is a bona fide problem that needs to be addressed. Moreover, anomaly detection algorithms enable an AI based MXDR to detect outliers in endpoint and user activity, data connections, and data transfers, which complements threat hunting and detection capabilities.

Key Takeaways

Organizations will continue facing advanced cyber threats, some of which will be more sophisticated than their current defensive capabilities to detect them. Combining artificial intelligence with MXDR can prevent such attacks from occurring. The MXDR solution applies machine learning algorithms to detect abnormal user access and activities, analyze complex data sets to reveal unknown threats and enhance cyber defenses’ effectiveness. The Securus360 MXDR platform integrates advanced AI rules and machine learning algorithms to provide your digital assets with round-the-clock protection from emerging cyber-attacks and malware in real time.

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