cyberattacks

This article reviews the legal framework governing the protection of critical infrastructure in Africa with an emphasis on threats like cyberwar and cyberterrorism. As African governments and businesses increasingly depend on the internet and information systems, there is a need to enact appropriate laws to protect critical infrastructure from cyberattacks that could jeopardize the economic and national security postures of African countries. The article outlines the need for appropriate legal instruments to protect critical infrastructure as African businesses increasingly rely on the internet and information systems. The lack of adequate laws regulating critical infrastructure does not translate to the absence of critical infrastructure in African countries. Ghana, for instance, has a legal framework governing critical infrastructure. These infrastructures are common in most African countries but lack the required legal framework to protect them. It is important to note that despite the Budapest Convention and African Convention on Cybersecurity and Personal Data Protection, there is no international legal framework regulating cyberwar and cyberterrorism. Considering these factors, this article reviews Ghana's Cybersecurity Act and the Directive on Critical Information Infrastructure and uses the United States framework for comparative analysis. In addition to reviewing the types of attacks critical infrastructure could face, the article looks at the legal framework for managing incidents that could arise from cyberattacks targeting critical infrastructure.

Software-Defined Network (SDN) introduces centralized network control via the OpenFlow protocol, enhancing network management, traffic routing, and security policy enforcement. However, SDN's centralized nature also introduces vulnerabilities, particularly to cyberattacks targeting the controller and communication channels. This study presents a resilience assessment methodology for SDN under cyberattack conditions, leveraging Markov process theory to model system states and transitions. Three SDN architectures were evaluated under various attack scenarios, revealing that traditional configurations lack sufficient resilience against synchronous attacks and controller breaches. To address these vulnerabilities, we propose an enhanced SDN protection framework integrating controller redundancy, automatic reconfiguration mechanisms, and anomaly detection using Long Short-Term Memory (LSTM) networks. The methodology was validated through simulations in the EVE-NG environment, demonstrating improved SDN stability under cyber threats. These findings provide a foundation for designing more resilient SDN infrastructures, ensuring network continuity and security against evolving cyber threats.

Background: With the continued advance in cyber threats, traditional network security systems offer little returns to organizations. AI has turned out to be a useful technology in improving network security because it proactively identifies and responds to threats in a short time. Objective: This article seeks to discuss the role played by AI self-defending mechanisms in autonomous network security given their effectiveness in threat detection, response time, and the overall harm that can be caused to networks by cyber criminals. Methods: Three separate studies were made, including conventional security systems, and analytically compared them with the AI-driven system across 100 different network environments. Machine learning (ML), deep learning (DL), and other forms of AI were applied to identify and counteract distinct threats like viruses, phishing, and even DDoS attacks. Detecting accuracy, response time and ability to mitigate attacks where among some of the other factors that were examined. Results: Automated threat intelligence systems have a 92% accuracy while legacy systems only have 78%. Mean response time was also decreasing by 65% from 45 seconds to 15 seconds. A significant increase to attack mitigation rates was noted with fifty percent effectiveness of the AI programs averting 85 percent of the threats in the first 30 seconds of identification. Conclusion: Autonomous threat response systems substantiate AI, which function as a radically superior replacement to conventional network security structures, minimizing threat response time and boosting the overall threat neutralization outcome. Incorporation of these types of secure mechanisms into contemporary security landscapes is important as a means of counteraction against new forms of cyber threats.