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Safeguarding Against Cyberwarfare: Sentient-Cyber’s AI Platform

News, Innovative Solutions
Artificial Intelligence, cyberwarfare, cyberattack, Markov Decision Making Process, Bayesian Network, maritime cybersecurity, U.S. Navy

State-sponsored cyberwarfare is quickly becoming the modern battleground of choice where the combatants are nation-wide actors, well-resourced groups with a wide variety of political and economic motivations. These combatants engage in both overt and covert operations to disrupt, manipulate, or destroy important computer network and system infrastructure. Their tactics involve a wide range of cyberattacks, including hacking, malware deployment, denial-of-service attacks, and information warfare.

As our technology evolves, so do the capabilities and strategies of our cyber adversaries. The advancing cyberattack capability poses significant challenges to the security of our nation’s warfighters, having almost been exclusively confined to non-military targets – but that constraint may be coming to an end. Sentient Digital is developing Sentient-Cyber, a software platform that utilizes Markov Decision Making Processes and Bayesian Networks to enhance maritime cybersecurity research.

In this article, our Senior Artificial Intelligence Research Scientist, Gene Locklear, will discuss how Sentient-Cyber’s multilayered platform can provide the foundation for assisting naval command in providing a formidable defense against potential cyber threats that target both U.S. Navy ships and commercial shipping vessels.

Cyberwarfare and the U.S. Navy

Cyberwarfare presents a potential threat to naval platforms by exploiting weaknesses in their interconnected systems. Cyber adversaries have the potential to launch sophisticated attacks to disrupt communication networks, manipulate navigation systems, or compromise onboard sensors and weapon systems. Such disruptions could jeopardize mission-critical operations, impair situational awareness, and endanger personnel. Cyberattacks that target U.S. naval and commercial maritime platforms could inflict widespread damage and undermine national security interests.

As the reliance on interconnected computer systems grow within maritime operations, defending against cyber threats becomes hugely important to ensure the effectiveness and survivability of naval assets.

Geopolitical Tension: Modern Conflict

In today’s context of cyberwarfare, the adversarial relationship between the United States and North Korea serves as an excellent example of geopolitical tension and military brinkmanship that are common in modern conflicts. From the U.S. perspective, North Korea’s cyber capabilities post a significant threat since attacks have targeted critical infrastructure and financial institutions. These capabilities are often attributed to state-sponsored hacker organizations like the Lazarus Group, believed to be responsible for the 2014 Sony Pictures cyber-attack. Conversely, North Korea views cyber operations as a means of asymmetric warfare, a kind of conflict between opposing forces that differ greatly in military power and can involve the usage of unconventional weapons or tactics such as guerilla warfare. Such tactics can include ransomware attacks and misinformation on social media designed to assert influence and retaliate against the United States as its perceived primary adversary.

Cyberwarfare Scenarios

Comic strip-style graphic showing three different cyberwarfare scenarios. GPS spoofing, ransomware, and hack attack.
Scenario 1. An enemy submarine launches a GPS spoofing attack, leading to friendly ship entering a restricted zone. Tensions escalate after the enemy submarine launches a simulated missile attack. Scenario 2. An enemy ship hacks into the systems of a large container ship, demanding a ransom to avoid disabling the systems entirely. Scenario 3. Hacking group target the maritime supply chain and introduce delays to US military installations. As a result, critical military operations are severely disrupted.

The Sentient-Cyber Platform

Sentient Digital is developing Sentient-Cyber, an innovative software platform designed to enhance maritime cybersecurity by utilizing a cognitive AI system to model the intricate relationships among cyberattack indicators, enabling predictive analysis of potential threats. Sentient-Cyber’s AI system is built around the core techniques of the Markov Decision Making Process (MDMP) and Bayesian networks to prevent and/or degrade nation-state cyberattacks targeting U.S. Naval platforms. Using a suite of probabilistic algorithms and machine learning techniques, it continuously monitors the evolving cyber threat environment to identify anomalies and suspicious activities while being fully integrated with the Naval commander’s Common Operational Picture (COP).

The AI system of Sentient-Cyber uses MDMP along with human-in-the-loop injection to allow the platform to semi-autonomously or autonomously respond to detected threats in real-time. By evaluating the current threat and the potential courses of action, it develops a script of defense strategies that can be carried out against the cyber threats before the adversary can mount a successful attack. This proactive approach strengthens the resilience of U.S. Naval platforms by lessening the risk of operational disruptions and failure of critical defensive platforms responding to kinetic attack.

Ultimately, Sentient-Cyber provides the naval commander with the tools and insights necessary to safeguard critical assets against sophisticated cyber adversaries and fortifies the US Navy’s cyber resilience in an increasingly contested maritime environment.

Cyberattack Detection

The Sentient-Cyber AI system, known as CyAI, is a compartmentalized structure of overlapping layers of MDMP representing the core of it cyberattack detection and defense. Cognition-based learning algorithms, underlaid with deep learning models, are the major components in analyzing the large amounts of data, identifying patterns, and making autonomous decisions. CyAI’s layers of MDMP, a hierarchical mathematical framework that models decision-making in stochastic environments, enables it to analyze complex scenarios, evaluate potential actions, and select optimal strategies based on probabilistic outcomes.

Markov Decision Making Process (MDMP)

CyAI analyzes diverse data sources, including network traffic and system logs, to identify anomalies and indicators of malicious access that may signal cyberattack activity. Through continuous monitoring and analysis, CyAI learns to recognize patterns associated with various cyber threats, such as malware infections and unauthorized access attempts. By leveraging MDMP, CyAI’s systems can assess the potential impact of detected threats and determine the most effective course of action to mitigate risks and defend critical assets.

Moreover, CyAI’s cyberattack detection is defined by its ability to adapt and evolve over time. As the threat environment evolves its tactics, techniques, and procedures, CyAI can learn from past experiences, update its model, and refine its decision-making processes to stay ahead of the emerging threat.

CyAI also integrates threat intelligence sources, vulnerability assessments, and real-time monitoring capabilities to anticipate potential threats, assess their severity, and orchestrate proactive defense measures to prevent or mitigate their impact. In the event of an ongoing cyberattack, CyAI’s defense mechanisms can autonomously initiate response actions, such as isolating compromised systems, blocking malicious traffic, or deploying countermeasures to neutralize threats.

Bayesian Networks

Bayesian Networks, a probabilistic graphical model, enable CyAI to represent and reason about uncertain and complex relationships among features of a threat attack’s signature, making them well-suited for modeling cybersecurity threats. Fundamentally, CyAI uses Bayesian Networks to model the likelihood of different cyber threats based on observed evidence, by assigning probabilities to the individual features of a cyberattack’s signature. This technique also allows for the integration of contextual information and expert knowledge into the cyber threat analysis.

Integration of MDMP and Bayesian Networks for Cyberattack Detection

Sentient-Cyber’s integration of MDMP and Bayesian Networks offers a comprehensive and adaptive defense strategy. MDMP enables the analysis of complex cyber scenarios and evaluates potential actions based on probabilistic outcomes. By leveraging MDMP, Sentient-Cyber’s AI system can assess the dynamic nature of cyber threats, anticipate their potential impact, and determine the most effective course of action to mitigate risks and protect critical assets. The integrating of Bayesian Networks into the AI allows for the modelling of the likelihood of different cyber threats based on observed evidence, thus aiding the MDMP layers. Further, the integration of MDMP and Bayesian Networks enables Sentient-Cyber to build and implement proactive defense measures, such as threat intelligence gathering, vulnerability assessments, and real-time monitoring capabilities.

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Innovation in Maritime Cybersecurity

Sentient-Cyber’s innovative integration of a cognitive AI system, composed of a compartmentalized layering of the Markov Decision Making Processes and Bayesian Networks, is a significant movement forward in maritime cybersecurity research.

Offering additional enhancement, Sentient-Cyber’s ability to provide integrated, continuous monitoring, analysis, and adaptive decision-making, into the naval COP enables proactive threat detection safeguarding critical maritime assets and operations. Its ability to autonomously assess the dynamic threat environment and select optimal defense strategies enhances the resilience of naval and commercial fleets against the emerging cyber threat.

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