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| Submission declined on 1 November 2023 by Timtrent (talk). I'm struggling with this draft. a huge lead section - something that is meant to summarise the article contents, but is most of the content - needs a précis or subdividing. That alone does not prevent acceptance.
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Nature-inspired cybersecurity (NICS) is a distinct sector in computer security that derives defensive strategies from observations in nature, such as animal swarms and chaotic systems. It addresses a wide range of threats including data disclosure, repudiation, privilege escalation, compromise, service disruption, and redirection. NICS fundamentally extrapolates models from natural systems
Definition
editNature-inspired cybersecurity (NICS) is a paradigm that integrates principles from natural systems into security solutions, employing algorithms and techniques inspired by biological, ecological, and evolutionary processes. This approach enhances resilience and adaptability in cyber defence mechanisms. NICS is formally defined as deriving insights from natural systems to formulate resilient security solutions for diverse cybersecurity challenges. By emulating behaviours observed in nature, NICS offers novel strategies for cybersecurity. It utilizes computer techniques strategically, leveraging defensive behaviours found in various species and natural occurrences.[1].
NICS is recognized for its effectiveness against emerging cyber threats, utilising methodologies like multi-objective optimization, deceptive information deployment and data integration. When combined with AI, ML, and computational data science, NICS provides robust defence against sophisticated cyberattacks, enhancing adaptability, self-organization, resilience, and overall robustness within security solutions[2].
History
editBefore computers became ubiquitous, the terminology surrounding them varied. The birth of computing, closely tied to mathematics, saw early programmable devices named the Difference Engine and Analytical Engine by Charles Babbage[3]. During the World Wars, the sudden advancement in computing, from analogue to digital, primarily focused on calculations for tasks like ballistic trajectories and cipher decryption.
In the mid-1960s, a shift occurred as efforts concentrated on connecting devices to exchange information, leading to the creation of networks like ARPANET. J.C.R. Licklider [4] introduced the concept of computer networks in his Intergalactic Computer Network idea. This notion of communication among entities mirrors biological systems.
The emergence of computer malware highlighted similarities to biological entities. Self-replicating programs initially referred to as organisms in the 1960s[5], later became known as `computer viruses' in 1983 by Frederic Cohen and Len Adleman[6]. Worms, similar to viruses, mimic their biological counterparts, spreading through connected networks to infect hosts.
Biologically linked malware prompted the development of defences inspired by living immune systems[7]. This approach, seen in modern Intrusion Detection/Prevention Systems (ID/PSs), employs artificial intelligence algorithms to automatically react to emerging threats, rather than relying on manual signature databases[8].
Foundations of Nature-inspired Cyber Security
editNature-inspired algorithms offer elegant solutions to a wide range of design challenges, including those within cyber systems. These algorithms, adapted or inspired by observations of natural biological systems, are attractive for both aesthetic and practical reasons. They are proven techniques, that minimise the risk of catastrophic failure when applied in similar contexts to their natural counterparts. However, achieving locally maximized or globally optimal performance with these algorithms outside their native environment is challenging. Natural systems often operate as black boxes, bypassing design efforts through demonstrable success. Yet, understanding and adapting these algorithms for human-designed settings require robust analogies between the natural and artificial environments, considering constraints and desired outcomes.
Constructing such analogies is time-consuming, and the impact of deviating from natural algorithms on performance outcomes may be unclear initially. However, fruitful interrogation into the workings of black box solutions can lead to insights that enable purposeful design.NICS draws from principles inherent in natural systems, including resilience, adaptability, and efficiency from biological organisms, ecosystems, and evolutionary processes. By mimicking decentralized, self-organizing, and collaborative traits of nature, NICS aims to enhance cybersecurity mechanisms[9].
The study of natural phenomena shapes NICS principles, involving analysis of living organisms' characteristics like growth patterns and energy requirements. Hierarchical and adaptive structures observed in nature serve as models for cybersecurity frameworks.Various biological traits can effectively simulate aspects of cybersecurity, particularly in network traffic regulation and governance. However, effective application requires a deep understanding of these models. Depending on the context, full integration of biological attributes may be necessary, while metaphorical parallels may prove insufficient in some cases, necessitating alternative strategies.
Key Concepts and Techniques
editKey methodologies in NICS include genetic algorithms, evolutionary computation, swarm intelligence, artificial immune systems, ant colony optimization, chaotic systems, and bio-inspired cryptography. These methods enable the development of adaptive and self-learning security mechanisms capable of autonomously identifying and mitigating emerging threats in dynamic environments[10][11].
Creating nature-inspired algorithms in cybersecurity involves establishing meaningful parallels between threats and biological systems, and adapting algorithms to meet computational requirements. Balancing automated parameterization with solution functionality is essential. NICS is recognized as a crucial component of natural computation, integrating concepts from connectionism, social behaviour, emergence, and metaheuristic approaches to address cybersecurity challenges. NICS adapts methodologies to the evolving cybersecurity landscape by assimilating design principles from bio-inspired computation.
Biomimicry and Cyber Security
editIn response to cyber threats, engineers and cybersecurity experts are turning to biomimicry, emulating nature's patterns and strategies for innovative solutions. Drawing on nature's adaptability and resilience, industries like wind energy and medical devices have already benefited. For cybersecurity, biomimicry offers potential in combatting cybercrime, with sacrificial systems, digital ants, and disruptive camouflage techniques being explored. These approaches aim to provide insights into attacker behaviour, preemptively identify threats, and confound cyber adversaries[12].
Physical Phenomenon and Cyber Security
editChaos theory in cybersecurity is evident in cascading failures within distributed systems. In large-scale networks like cloud platforms or banking systems, interconnected components create a complex web of dependencies. Minor events, like software glitches or surges in network traffic, can trigger chain reactions leading to widespread disruption or system collapse. These cascades result from non-linear interactions and feedback loops, amplifying the impact of small disturbances.
For example, the 2016 DDoS attack on Dyn[13][14], a DNS provider, caused internet outages affecting Twitter, Netflix, and PayPal. Exploiting IoT device vulnerabilities, the attack overwhelmed Dyn's servers with traffic, leading to cascading failures that disrupted critical online resources. This incident illustrates the chaotic nature of cybersecurity threats.
Nature-inspired Cryptology (NIC)
editNature-inspired cryptology (NIC) refers to cryptographic techniques and algorithms that draw inspiration from natural phenomena or processes found in biological systems, physics, chemistry, or other natural domains[15]. These techniques often emulate the behaviour of natural systems to design cryptographic primitives, protocols, or systems.
Future Directions
editDespite promising solutions, Nature-Inspired Computing (NICS) faces challenges such as scalability, computational overhead, ethical and legal concerns regarding autonomous security mechanisms, and integration with existing cybersecurity frameworks. Future research aims to explore NICS applications in emerging technologies like IoT security, blockchain, and quantum computing.
The rapid evolution of cyberspace technologies necessitates increased reliance on emerging applications like fog and cloud computing, smart cities, IoT, collaborative computing, and virtual/mixed reality environments. Securing these applications against cyber threats drives innovation in cybersecurity and resilience solutions.
Algorithms inspired by natural processes, phenomena, and organisms have been developed, including artificial neural networks, swarm intelligence, chaotic behaviour algorithms, deep learning systems, and biomimicry. These algorithms offer unique characteristics that enable novel methodologies to effectively address cybersecurity challenges[16]
References
edit- ^ Rzeszutko, Elżbieta; Mazurczyk, Wojciech (April 2015). "Insights from Nature for Cybersecurity". Health Security. 13 (2): 82–87. arXiv:1410.8317. doi:10.1089/hs.2014.0087. ISSN 2326-5094. PMID 25813971.
- ^ Shandilya, Shishir Kumar; Choi, Bong Jun; Kumar, Ajit; Upadhyay, Saket (March 2023). "Modified Firefly Optimization Algorithm-Based IDS for Nature-Inspired Cybersecurity". Processes. 11 (3): 715. doi:10.3390/pr11030715. ISSN 2227-9717.
- ^ Bromley, Allan G. (1982). "Charles Babbage's Analytical Engine, 1838". IEEE Annals of the History of Computing. 4 (3): 196–217. doi:10.1109/MAHC.1982.10028.
- ^ Denning, Peter J. (1989). "The Science of Computing: The ARPANET after Twenty Years". American Scientist. 77 (6): 530–534. ISSN 0003-0996. JSTOR 27856002.
- ^ Levy, Scott; Crandall, Jedidiah R. (2020-07-30), The Program with a Personality: Analysis of Elk Cloner, the First Personal Computer Virus, arXiv:2007.15759
- ^ Zetter, Kim. "Nov. 10, 1983: Computer 'Virus' Is Born". Wired. ISSN 1059-1028. Retrieved 2024-06-11.
- ^ Anderson, William; Moore, Kaneesha; Ables, Jesse; Mittal, Sudip; Rahimi, Shahram; Banicescu, Ioana; Seale, Maria (2022-08-16), Designing an Artificial Immune System inspired Intrusion Detection System, arXiv:2208.07801
- ^ Anderson, William; Moore, Kaneesha; Ables, Jesse; Mittal, Sudip; Rahimi, Shahram; Banicescu, Ioana; Seale, Maria (2022-08-16), Designing an Artificial Immune System inspired Intrusion Detection System, arXiv:2208.07801
- ^ Mazurczyk, Wojciech; Drobniak, Szymon; Moore, Sean (2016), Akhgar, Babak; Brewster, Ben (eds.), "Towards a Systematic View on Cybersecurity Ecology", Combatting Cybercrime and Cyberterrorism: Challenges, Trends and Priorities, Cham: Springer International Publishing, pp. 17–37, doi:10.1007/978-3-319-38930-1_2, ISBN 978-3-319-38930-1, retrieved 2024-07-29
- ^ Bitam, Salim; Zeadally, Sherali; Mellouk, Abdelhamid (June 2016). "Bio-inspired cybersecurity for wireless sensor networks". IEEE Communications Magazine. 54 (6): 68–74. doi:10.1109/MCOM.2016.7497769. ISSN 0163-6804.
- ^ Fefferman, Nina H. (2019-04-01), "When to turn to nature-inspired solutions for cyber systems", Nature-Inspired Cyber Security and Resiliency: Fundamentals, Techniques and Applications, IET Digital Library, pp. 29–50, doi:10.1049/pbse010e_ch2, ISBN 978-1-78561-638-9, retrieved 2024-07-29
- ^ Rzeszutko, Elzbieta; Mazurczyk, Wojciech (2019-04-01), "Nature-inspired analogies and metaphors for cyber security", Nature-Inspired Cyber Security and Resiliency: Fundamentals, Techniques and Applications, IET Digital Library, pp. 1–27, doi:10.1049/pbse010e_ch1, ISBN 978-1-78561-638-9, retrieved 2024-07-29
- ^ Woolf, Nicky (2016-10-26). "DDoS attack that disrupted internet was largest of its kind in history, experts say". The Guardian. ISSN 0261-3077. Retrieved 2024-06-11.
- ^ Hekmati, Arvin; Krishnamachari, Bhaskar (2024-03-14), Graph-Based DDoS Attack Detection in IoT Systems with Lossy Network, arXiv:2403.09118
- ^ Shandilya, Shishir K. (2023). A Nature-Inspired Approach to Cryptology. Studies in Computational Intelligence. Vol. 1122 (1st ed.). Singapore: Springer Nature (published 14 December 2023). doi:10.1007/978-981-99-7081-0. ISBN 978-981-99-7081-0.
- ^ Song, Bosheng; Li, Kenli; Orellana-Martín, David; Pérez-Jiménez, Mario J.; PéRez-Hurtado, Ignacio (2021-02-11). "A Survey of Nature-Inspired Computing: Membrane Computing". ACM Comput. Surv. 54 (1): 22:1–22:31. doi:10.1145/3431234. hdl:11441/107916. ISSN 0360-0300.