Cybersecurity in IoT networks

Abstract: One way to view the Internet of Things (IoT) is as a microcosm of the wider Internet; while humans interact directly over the Internet, IoT devices (e.g., Amazon Alexa) communicate and process data autonomously, ensuring their efficiency [1]. Unfortunately, although IoT networks are user-friendly, they lack the stringent security protocols present in traditional computer networks. As such, they are susceptible to cyberattacks [2] and threats such as phishing and IP spoofing [3]. Thankfully, research has been undertaken to assess and bolster the resilience of IoT networks [5]. Some have used deep learning models [4], while others work as hackers, simulating various attack scenarios and detecting backdoors and other weaknesses in sample IoT networks. Our group will not only assume the role of these hackers, but we will also deploy strategies to enhance cybersecurity in these networks, ensuring devices and users alike are protected in the age of the World Wide Web.

References:
[1] A. S. Rao and S. Mole, "Exploring the Potential of IoT: An In-Depth Examination of Applications and Prospects," The Journal of Contemporary Issues in Business and Government, vol. 29, no. 4, pp. 49–67, 2023, doi: https://cibgp.com/au/index.php/1323-6903/article/view/2632
[2] R. Andrade, I. Ortiz-Garces, X. Tintin, and G. Llumiquinga, "Factors of Risk Analysis for IoT Systems," Risks, vol. 10, no. 8, p. 162, Aug. 2022, doi: https://doi.org/10.3390/risks10080162
[3] T. Sasi, A. H. Lashkari, R. Lu, P. Xiong, and S. Iqbal, "A Comprehensive Survey on IoT Attacks: Taxonomy, Detection Mechanisms and Challenges," Journal of Information and Intelligence, vol. 2, no. 6, Dec. 2023, doi: https://doi.org/10.1016/j.jiixd.2023.12.001
[4] M. Roopak, G. Yun Tian, and J. Chambers, "Deep Learning Models for Cyber Security in IoT Networks," 2019 IEEE 9th Annual Computing and Communication Workshop and Conference (CCWC), Jan. 2019, doi: https://doi.org/10.1109/ccwc.2019.8666588
[5] Y. Lu and L. Da Xu, "Internet of Things (IoT) Cybersecurity Research: A Review of Current Research Topics," IEEE Internet of Things Journal, vol. 6, no. 2, pp. 1–1, 2018, doi: https://doi.org/10.1109/jiot.2018.2869847

Analyzing the Security of Email Transmission in NS3 Through DDoS Attacks

Abstract:
Distributed Denial-of-Service (DDoS) attacks pose a significant threat to secure communication, potentially disrupting access to critical online services. Email transmission, which relies on TCP encryption protocols for security, can be heavily impacted by such attacks. This project aims to analyze the effects of DDoS attacks on secure email transmission using NS3 simulations. The study will model an email communication system employing TLS or SSL encryption and simulate different DDoS attack scenarios by varying attack intensity and traffic patterns. Performance metrics such as throughput, latency, and packet loss will be evaluated using NS3’s FlowMonitor module. The goal of this research is to assess the resilience of secure email systems under DDoS conditions and identify strategies to optimize network performance and mitigate attack impacts.

References:
[1] C. Douligeris and A. Mitrokotsa, "DDoS attacks and defense mechanisms: a classification," IEEE, 2003.
[2] G. Chen and R. Wanner, "Secure Email Transmission Protocols -- A New Architecture Design," arXiv, 2022.
[3] R. Holz et al., "TLS in the wild: an Internet-wide analysis of TLS-based protocols for electronic communication," arXiv, 2016.
[4] G. Carneiro et al., "FlowMonitor: a network monitoring framework for NS-3," VALUE-TOOLS, 2009.
[5] H. Wang and Y. Li, "Overview of DDoS Attack Detection in Software-Defined Networks," IEEE Access, 2024.
[6] R. Housley, "Evolution of Email Security Standards," IEEE Communications Magazine, 2022.
[7] R. Abubakar et al., "An Effective Mechanism to Mitigate Real-Time DDoS Attack," IEEE Access, 2020.

Multiplayer Game Server Simulation using ns-3 and ENet

Abstract: With the widespread popularity of online multiplayer video games, each user wants a fast and reliable connection to the server for an enjoyable experience. This report explores the simulation and analysis of online multiplayer game servers using ns-3 and ENet Networking Library to see the performance of game networks. Specifically, looking at the latency, packet loss, queue management, and retransmissions and errors. Our study aims to gain insight into how real-time gaming networks function as strain on the network increases. We plan to use ns-3 to build a model emulating a multiplayer gaming network. We will also be using ENet, which is a C++ library, to simulate real-time conditions of data being sent in the network.

References:
[1] T. Alstad et al., "Game network traffic simulation by a custom bot", 2015 Annual IEEE Systems Conference (SysCon) Proceedings, Vancouver, BC, Canada, 2015, pp. 675-680, doi: 10.1109/SYSCON.2015.7116828 https://ieeexplore.ieee.org/document/7116828
[2] C. E. Palazzi and A. Bujari, “Evaluating outdoor games with the NS-2 and NS-3 simulation frameworks”, Published in 2014 IEEE 11th Consumer Communications and Networking Conference (CCNC): Networking Issues in Multimedia Entertainment (NIME'14), Las Vegas, NV, USA, Jan. 2014, pp. 498–501. doi: 10.1109/CCNC.2014.7056355. https://ieeexplore.ieee.org/document/7056326
[3] 0xFA11, "GameNetworkingResources", github.com, Date Accessed: 2/7/25, [Online] Available: https://github.com/0xFA11/GameNetworkingResources
[4] Pierre, "Beginner’s Guide to Game Networking", pvigier.github.io, Date Accessed: 2/7/25, [Online], Available: https://pvigier.github.io/2019/09/08/beginner-guide-game-networking.html
[5] M. Diehl, "Network Programming with ENet", linuxjournal.com, Date Accessed: 2/7/25, [Online], Available: https://www.linuxjournal.com/content/network-programming-enet
[6] A. Abdelkhalek, A. Bilas and A. Moshovos, "Behavior and performance of interactive multi-player game servers", 2001 IEEE International Symposium on Performance Analysis of Systems and Software. ISPASS., Tucson, AZ, USA, 2001, pp. 137-146, doi: 10.1109/ISPASS.2001.990690. https://ieeexplore.ieee.org/document/990690

Evaluating Power and Performance Consumption in a P2P Network While Mitigating a DDOS Attack Within ns-3

Abstract:
The project examines how peer-to-peer networks operate when compromised with simulated DDOS attacks and how the network can combat excessive power consumption and performance loss through prevention techniques. Through ns-3 we can apply attack mitigation systems to boost the performance metrics and mitigate the effect of a simulated DDOS attack on the peer-to-peer system. Key components such as network congestion, node processing load, and power efficiency can be modelled and analyzed upon applying the simulation. From these sets of data, we can gain insights into how a balance of both security and effective energy usage can be derived from a peer-to-peer network while undergoing a simulated DDOS attack.

References:
[1] N. Singh and S. De, "Survey on recent DDoS mitigation techniques and comparative analysis," Proc. Int. Conf. Adv. Comput. Commun. Autom. (ICACCA), 2016, pp. 1–5. doi: 10.1109/ICACCA.2016.7546581.
[2] A. K. Verma and D. Mukhopadhyay, "DDoS testbed based on peer-to-peer grid," Proc. Int. Conf. Inf. Process. (ICIP), 2017, pp. 1–6. doi: 10.1109/INFOP.2017.7955627.
[3] N. Fan, D. L. Goeckel, D. Towsley, and P. Basu, "Simulation of DDoS attacks on P2P networks," Proc. IEEE Mil. Commun. Conf. (MILCOM), 2011, pp. 1883–1888. doi: 10.1109/MILCOM.2011.6063048.
[4] S. T. Vuong and Y. H. Wang, "Distinguishing the master to defend DDoS attack in peer-to-peer networks," Proc. IEEE Int. Conf. Comput. Intell. Security (CIS), 2010, pp. 212–217. doi: 10.1109/CIS.2010.5578493.
[5] R. Al-Sayyed and A. Ouda, "A survey of P2P overlays in various networks," Proc. Int. Conf. Inf. Sci. Appl. (ICISA), 2011, pp. 1–7. doi: 10.1109/ICISA.2011.6024559.

Simulation and Impact of a DDoS Attack in a 5G Network

Abstract:
5G networks are being evermore utilized as time goes on, with the high speed and low latency they bring allowing users to connect with each other faster than they’ve ever been able to before. Though this increasing popularity brings more threats to 5G networks, such as DDoS attacks which can impede a user’s ability to properly utilize the network. The aim of this project is to simulate a 5G network and a DDoS attack on that network while varying the number of attackers to observe how it affects network performance.

References:
[1] H. Djuitcheu, T. Shah, M. Tammen and H. D. Schotten, "DDoS impact assessment on 5G system performance," 2023 IEEE Future Networks World Forum (FNWF), Baltimore, MD, USA, 2023, pp. 1-6, doi: 10.1109/FNWF58287.2023.10520536
[2] A. Pagadala and G. Ahmed, "Analysis of DDoS Attacks in 5G Networks," 2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT), Delhi, India, 2023, pp. 1-6, doi: 10.1109/ICCCNT56998.2023.10307311
[3] H. Huang, J. Chu and X. Cheng, "Trend Analysis and Countermeasure Research of DDoS Attack Under 5G Network," 2021 IEEE 5th International Conference on Cryptography, Security and Privacy (CSP), Zhuhai, China, 2021, pp. 153-160, doi: 10.1109/CSP51677.2021.9357499
[4] M. S. Khan, B. Farzaneh, N. Shahriar, N. Saha and R. Boutaba, "SliceSecure: Impact and Detection of DoS/DDoS Attacks on 5G Network Slices," 2022 IEEE Future Networks World Forum (FNWF), Montreal, QC, Canada, 2022, pp. 639-642, doi: 10.1109/FNWF55208.2022.00117
[5] S. M. Vidhani and A. V. Vidhate, "Security Challenges in 5G Network: A technical features survey and analysis," 2022 5th International Conference on Advances in Science and Technology (ICAST), Mumbai, India, 2022, pp. 592-597, doi: 10.1109/ICAST55766.2022.10039654

Performance analysis of 802.11ax 5GHz (WiFi 6)

Abstract:
Following the release of IEEE 802.11ac (WiFi 5) in 2013, IEEE 802.11ax (WiFi 6) was released in 2019 [1]. A performance analysis of the 802.11ax 5GHz (WiFi 6) protocol lists multiple benefits with a major highlight being the inclusion of an improved MU-MIMO (Multi-User Multiple-Input Multiple-Output) which allows for both downlink and uplink, increasing the number of simultaneous streams to increase from four to eight [2] alongside an increase in maximum speeds. This project will outline the main characteristics of the WiFi 6 protocol, indicating if there are any significant changes compared to previous iterations, and discuss the implications of the protocol’s implementation with respect to its performance.

References:
[1] N. Lawrence, "What is WiFi 6?," Reviews.org. Accessed: Feb. 06, 2025. [Online]. Available: https://www.reviews.org/au/internet/what-is-wifi-6/
[2] E. Mozaffariahrar, F. Theoleyre, and M. Menth, "A Survey of Wi-Fi 6: Technologies, Advances, and Challenges," Future Internet, vol. 14, no. 10, Art. no. 10, Oct. 2022, doi: 10.3390/fi14100293.
[3] R. Liu and N. Choi, "A First Look at Wi-Fi 6 in Action: Throughput, Latency, Energy Efficiency, and Security," Proc. ACM Meas. Anal. Comput. Syst., vol. 7, no. 1, p. 25:1-25:25, Mar. 2023, doi: 10.1145/3579451.
[4] E. Tokhirov and R. Aliev, "Analysis of the differences between Wi-Fi 6 and Wi-Fi 5," E3S Web of Conf., vol. 402, p. 03020, 2023, doi: 10.1051/e3sconf/202340203020.
[5] Eliud Momanyi Manyinsa, "Implementation of IEEE802.11 (Wi-Fi) in NS-3," JCC, vol. 13, no. 6, Jun. 2016, doi: 10.17265/1548-7709/2016.06.003.
[6] Deronne et al., "ns-3 Wi-Fi 11ax Project: Release final," May 2019. Available: https://wp.ece.uw.edu/wp-content/uploads/sites/36/2018/11/11ax-final-report.pdf

Simulation of Priorities in Peer-to-Peer Networks Using BitTorrent Protocol

Abstract:
In modern networking, peer-to-peer (P2P) file sharing remains one of the primary protocols of file distribution thanks to its decentralized nature and self-scaling. However, prioritization mechanisms in these networks significantly impact performance and fairness among peers. This project evaluates priority-based sharing in the BitTorrent protocol using ns-3 simulations which will provide insights into optimizing P2P file-sharing strategies, balancing fairness amongst users, and efficiency in real-world networks.

References:
[1] M. E. Rivero-Angeles and G. Rubino, "Priority-Based Scheme for File Distribution in Peer-to-Peer Networks," 2010 IEEE International Conference on Communications, pp. 1–6, May 2010, doi: https://doi.org/10.1109/icc.2010.5501852.
[2] D. Qiu and R. Srikant, "Modeling and performance analysis of BitTorrent-like peer-to-peer networks," ACM SIGCOMM Computer Communication Review, vol. 34, no. 4, p. 367, Oct. 2004, doi: https://doi.org/10.1145/1030194.1015508.
[3] L. Guo, S. Chen, Z. Xiao, E. Tan, X. Ding, and X. Zhang, "A performance study of BitTorrent-like peer-to-peer systems," IEEE Journal on Selected Areas in Communications, vol. 25, no. 1, pp. 155-169, Jan. 2007, doi: https://doi.org/10.1109/jsac.2007.070116.
[4] D. Schoder, K. Fischbach, and C. Schmitt, "Core Concepts in Peer-to-Peer Networking." Available: https://citeseerx.ist.psu.edu/document?repid=rep1&type=pdf&doi=cb43290129a3f85455c229285799925d2a794043
[5] M. E. Rivero-Angeles and Izlian Yolanda Orea-Flores, "System Modeling for Priority Schemes in Managed Peer-to-Peer Networks," Computación y Sistemas, vol. 22, no. 2, Jul. 2018, doi: https://doi.org/10.13053/cys-22-2-2747.
[6] "Steps for implementing peer-to-peer topology," Ns3 Projects, 2024. https://ns3simulation.com/how-to-implement-peer-to-peer-topology-in-ns3/.