X-Swarm: The Upcoming Swarm Worm

  • Thanh Cong Truong
  • Quoc Bao Diep
  • Ivan Zelinka
  • Than Trong Dao
Keywords: Swarm intelligence, malware, Tor, cybersecurity, self-healing network

Abstract

With the rapid growth of technology in the digital landscape, cybercriminals attempt to utilize new and sophisticated techniques to autonomous and increase the speed and scale of their attacks. Meanwhile, the Dark Web infrastructures such as Tor, plays a crucial role in the criminal underground, especially for malware developers' communities. It is logical to expect that the malicious actors would utilize the combination of these techniques in shortcoming time. To better understand the upcoming threat, in this manuscript, we investigate the design and mitigation of such malware. Accordingly, we introduce X-sWarm, which will be the next generation of resilient, stealthy malware that leverages the intelligent technique and the darknet infrastructures. Furthermore, we show that with the self-healing network mechanism, X-sWarm can achieve a low diameter and a low degree and be robust to partitioning under node removal. More importantly, we suggest the mitigation technique that neutralizes the nodes of the proposed worm.

References

Amer, E., and Zelinka, I. A dynamic windows malware detection and prediction method based on contextual understanding of api call sequence. Computers & Security 92(2020), 101760.

Barabasi, A.-L., and Albert, R. Emergence of scaling in random networks. Science 286, 5439(1999), 509–512.

Dingledine, R., Mathewson, N., and Syverson, P. Tor: The second-generation onion router. Tech. rep., Naval Research Lab Washington DC, 2004.

Douceur, J. R. The sybil attack. In International workshop on peer-to-peer systems (2002), Springer, pp. 251–260.

Erdos, P., and Renyi, A. On the evolution of random graphs. Publ. Math. Inst. Hung. Acad. Sci 5, 1 (1960), 17–60.

Goldschlag, D., Reed, M., and Syverson, P. Onion routing. Communications of the ACM 42, 2 (1999), 39–41.

Manku, G. S., Naor, M., and Wieder, U. Know thy neighbor’s neighbor: The power of looks head in randomized p2p networks. In Proceedings of the Thirty-Sixth Annual ACM Symposium on Theory of Computing (New York, NY, USA, 2004), STOC ’04, Association for Computing Machinery, pp. 54–63.

Sikora, L., and Zelinka, I. Swarm Virus, Evolution, Behavior and Networking. Springer Berlin Heidelberg, Berlin, Heidelberg, 2018, pp. 213–239.

Szor, P.The Art of Computer Virus Research and Defense. Pearson Education, 2005.

Thanh Cong, T., and Zelinka, I. A survey on artificial intelligence in malware as next-generation threats. MENDEL 25, 2 (Dec. 2019), 27–34.

Truong, T. C., Diep, Q. B., and Zelinka, I. Artificial intelligence in the cyber domain: Offense and defense. Symmetry 12, 3 (2020).

Truong, T. C., Huynh, T.-P., and Zelinka, I. Applications of swarm intelligence algorithms countering the cyber threats. In Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion (New York, NY, USA, 2020), GECCO ’20, Association for Computing Machinery, p. 1476–1485.

Truong, T. C., Zelinka, I., Plucar, J.,Candık, M., and Sulc, V. Artificial intelligence and cybersecurity: Past, presence, and future. In Artificial Intelligence and Evolutionary Computations in Engineering Systems (Singapore, 2020), S. S. Dash, C. Lakshmi, S. Das, and B. K. Panigrahi, Eds., Springer Singapore, pp. 351–363.

Truong, T. C., Zelinka, I., and Senkerik, R. Neural swarm virus. In Swarm, Evolutionary, and Memetic Computing and Fuzzy and Neu-ral Computing (Cham, 2020), A. Zamuda, S. Das, P. N. Suganthan, and B. K. Paanigrahi, Eds., Springer International Publishing, pp. 122–134.

Wang, P., Sparks, S., and Zou, C. C. An advanced hybrid peer-to-peer botnet. IEEE Transactions on Dependable and Secure Computing 7, 2(2010), 113–127.

Zelinka, I., and Amer, E. An ensemble-based malware detection model using minimum feature set. MENDEL 25, 2 (Dec. 2019), 1–10.

Zelinka, I., Das, S., Sikora, L., and Senkerık, R. Swarm virus-next-generation virusand antivirus paradigm?Swarm and EvolutionaryComputation 43(2018), 207–224.

Published
2020-08-24
How to Cite
[1]
Truong, T., Diep, Q., Zelinka, I. and Dao, T. 2020. X-Swarm: The Upcoming Swarm Worm. MENDEL. 26, 1 (Aug. 2020), 7-14. DOI:https://doi.org/10.13164/mendel.2020.1.007.
Section
Research articles