Machine Learning White-Hat Worm Launcher for Tactical Response by Zoning in Botnet Defense System

Pan, Xiangnan; Yamaguchi, Shingo

doi:10.3390/s22134666

Cited by 8 publications

(3 citation statements)

References 30 publications

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“…The idea of lifespan was proposed. Pan et al [ 27 ] proposed a zoning method to mitigate malware attacks, and lifespan is used to release a zone from a botnet once the lifespan has been reached. The method is effective when forming a temporary zone when needed and releasing the zone once it has been recovered.…”

Section: Discussionmentioning

confidence: 99%

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Diffusion of White-Hat Botnet Using Lifespan with Controllable Ripple Effect for Malware Removal in IoT Networks

Ahmadon

Yamaguchi

2023

Sensors

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Self-propagating malware has been infecting thousands of IoT devices and causing security breaches worldwide. Mitigating and cleaning self-propagating malware is important but challenging because they propagate unpredictably. White-hat botnets have been used to combat self-propagating malware with the concept of fight fire-with-fire. However, white-hat botnets can also overpopulate and consume the resource of IoT devices. Later, lifespan was introduced as a self-destruct measure to restrain white-hat botnets’ overpopulation, but unable to change based on real-time situations. This paper proposes a method for diffusing white-hat botnets by controlling lifespan. The main contribution of this paper is that the method uses a dynamic lifespan that increases and decreases based on the congregation’s situation of the self-propagating malware and white-hat botnets. The method tackles the problem of overpopulation of white-hat botnets since they can self-propagate by controlling the ripple effect that widens the white-hat botnet’s diffusion area but suppresses the number of white-hat botnets to achieve a ’zero-botnet’ situation. The effectiveness in reducing the overpopulation rate was confirmed. The experiment result showed that the ripple effect could reduce the number of white-hat botnets in the network by around 80%, depending on different control parameters.

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Section: Discussionmentioning

confidence: 99%

“…Then Pan et al. [ 27 ] proposed zoning tactics to exterminate malware using clustering. The white-hat botnet is diffused into the network using a launcher and placed in a specific position to form a zone for clean-up or mitigate the attack.…”

Section: Related Workmentioning

confidence: 99%

Diffusion of White-Hat Botnet Using Lifespan with Controllable Ripple Effect for Malware Removal in IoT Networks

Ahmadon

Yamaguchi

2023

Sensors

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“…It also proposed a basic launcher and strategies to build the white-hat botnet. Reference [ 26 ] proposed an improved launcher adopting machine learning. The launcher learns how to build white-hat botnets appropriate to the infection status of the malicious botnet and can disinfect given botnets effectively.…”

Section: Simulation Evaluationmentioning

confidence: 99%

Botnet Defense System: Observability, Controllability, and Basic Command and Control Strategy

Yamaguchi

2022

Sensors

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This paper deals with the observability, controllability, and command and control strategy in the Botnet Defense System (BDS) that disinfects malicious botnets with white-hat botnets. The BDS defends an IoT system built over the Internet. The Internet is characterized by openness, but not all nodes are observable and controllable. We incorporated the concept of observability and controllability into the BDS design and theoretically clarified that the BDS can enhance its observability and controllability by utilizing its white-hat botnets. In addition, we proposed a Withdrawal strategy as a basic strategy to command and control white-hat botnets. Then, we modeled the BDS, adopted the Withdrawal strategy with agent-oriented Petri net PN2 and confirmed the effect through the simulation of the model. The result shows that even if considering observability and controllability, the BDS wiped out the malicious bots and reduced the white-hat bots to less than 1% as long as the white-hat worms were sufficiently infectious.

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Artificial intelligence (AI) cybersecurity dimensions: a comprehensive framework for understanding adversarial and offensive AI

Malatji,

Tolah

2024

AI Ethics

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As Artificial Intelligence (AI) rapidly advances and integrates into various domains, cybersecurity emerges as a critical field grappling with both the benefits and pitfalls of AI technologies. This paper explores the multifaceted dimensions of AI-driven cyberattacks, offering insights into their implications, mitigation strategies, underlying motivations, and profound societal impacts. The research centres on developing and presenting the AI Cybersecurity Dimensions (AICD) Framework, a comprehensive, multidimensional schema designed to guide academics, policymakers, and industry professionals in understanding and combating the evolving challenges posed by AI-driven cyber threats. The research unveils the complex dynamics of offensive AI, stressing the need for adaptive defences and ethical considerations. Concurrently, the study highlights adversarial AI threats, calling for proactive measures to address their potential ramifications. Through rigorous textual analyses and extensive literature reviews, the paper underscores the urgency for interdisciplinary approaches to bridge the technology-humanity chasm traditionally observed in cybersecurity discussions. By synthesising these diverse elements, the AICD Framework emerges as an instrumental tool for holistic understanding and practical interventions in the AI-infused cybersecurity landscape. The paper concludes with an urgent call for collaborative efforts in research and practice to navigate the intricate challenges and capitalise on the opportunities borne from the convergence of AI and cybersecurity.

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Machine Learning White-Hat Worm Launcher for Tactical Response by Zoning in Botnet Defense System

Cited by 8 publications

References 30 publications

Diffusion of White-Hat Botnet Using Lifespan with Controllable Ripple Effect for Malware Removal in IoT Networks

Diffusion of White-Hat Botnet Using Lifespan with Controllable Ripple Effect for Malware Removal in IoT Networks

Botnet Defense System: Observability, Controllability, and Basic Command and Control Strategy

Artificial intelligence (AI) cybersecurity dimensions: a comprehensive framework for understanding adversarial and offensive AI

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