Investigation into Wireless Device Botnets

Abstract:
A botnet is a network of compromised computers controlled by a central entity for malicious purposes. A botnet can be used to engage in malicious activities such as sending spam, launching DDoS attacks, and stealing information. The growing number of Internet of Things (IoT) devices, such as smart home appliances, security cameras, and medical devices, has provided attackers with a large pool of vulnerable devices to exploit. These devices often have weak security measures or outdated firmware, making them an easy target for attackers to compromise and use as part of botnets to launch DDoS attacks. The goal of this project is to implement a botnet in NS-3 comprised of various devices connected to wireless networks and observe its effectiveness at executing DDoS attacks.

References:
[1] Vishwakarma, R., Jain, A.K. A survey of DDoS attacking techniques and defence mechanisms in the IoT network. Telecommun Syst 73, 3–25 (2020). https://doi.org/10.1007/s11235-019-00599-z
[2] V. Buriachok and V. Sokolov, "Using 2.4 GHz Wireless Botnets to Implement Denial-of-Service Attacks," in IEEE Transactions on Networking, vol. 28, no. 3, pp. 1447-1458, June 2020, doi: 10.1109/TNET.2020.2974776.
[3] Lyu, M., Sherratt, D., Sivanathan, A., Gharakheili, H. H., Radford, A., & Sivaraman, V. (2017, July). Quantifying the reflective DDoS attack capability of household IoT devices. In Proceedings of the 10th ACM Conference on Security and Privacy in Wireless and Mobile Networks (pp. 46-51). Association for Computing Machinery. https://doi.org/10.1145/3098243.3098264
[4] J. He, Y. Yang, X. Wang, and Z. Tan, "Adaptive traffic sampling for P2P botnet detection," International Journal of Network Management, vol. 27, no. 5. Wiley, p. e1992, Aug. 04, 2017. doi: 10.1002/nem.1992.
[5] R. Chen, W. Niu, X. Zhang, Z. Zhuo, and F. Lv, "An Effective Conversation-Based Botnet Detection Method," Mathematical Problems in Engineering, vol. 2017. Hindawi Limited, pp. 1-9, 2017. doi: 10.1155/2017/4934082
[6] S. García, A. Zunino, and M. Campo, "Survey on network-based botnet detection methods," Security and Communication Networks, vol. 7, no. 5. Wiley, pp. 878-903, Jun. 21, 2013. doi: 10.1002/sec.800.
[7] L. Wenke, Botnet detection : countering the largest security threat. Springer, 2008.
[8] D. Zhao et al., "Botnet detection based on traffic behavior analysis and flow intervals," Computers & Security, vol. 39. Elsevier BV, pp. 2-16, Nov. 2013. doi: 10.1016/j.cose.2013.04.007.

Analysis of LoRa and LoRaWAN Operation Supported by ns-3 Simulation

Abstract:
LoRa has become a popular radio communication technology in recent years due to its ability to be extremely long-range while using relatively low power and at a low cost [1]. In this project we explore Wide Area Networks (WAN) uses with LoRa, which when combined are referred to as LoRaWAN. In this project we first aim to introduce the operation of LoRa modules, and the LoRaWAN network and protocols involved. The simulation of LoRaWAN networks that has been previously explored [2] [3] [4] are then reviewed and discussed, followed by our own simulation using ns-3 simulation packages made available on GitHub [5], and described in a ns-3 style wiki [6]. In our own simulation we aim to demonstrate the operation of a small network of connected end-devices and gateways. Overall this project aids in providing a better understanding of the network operation and performance specific to LoRa end-devices.

References:
[1] J. P. Tomás, “What is Lorawan and what are the main benefits of this technology?,” RCR Wireless News, 12-Jun-2017. [Online]. Available: https://www.rcrwireless.com/20170612/internet-of-things/what-lowrawan-main-benefits-technology-tag23. [Accessed: 28-Jan-2023].
[2] T. -H. To and A. Duda, "Simulation of LoRa in NS-3: Improving LoRa Performance with CSMA," 2018 IEEE International Conference on Communications (ICC), Kansas City, MO, USA, 2018, pp. 1-7, doi: 10.1109/ICC.2018.8422800.
[3] F. H. Khan and M. Portmann, “Experimental evaluation of Lorawan in NS-3,” 2018 28th International Telecommunication Networks and Applications Conference (ITNAC), 2018.
[4] J. Silva, D. Flor, V. Junior, N. Bezerra, and A. Medeiros, “A survey of LORAWAN simulation tools in NS-3,” Journal of Communication and Information Systems, vol. 36, no. 1, pp. 17–30, 2021.
[5] D. Magrin, “Lorawansimulations using NS-3 - nsnam.org.” [Online]. Available: https://www.nsnam.org/tutorials/tutorials/consortium19/wns3-lorawan.pdf. [Accessed: 28-Jan-2023].
[6] “Lorawan module,” LoRaWAN Module - Model Library. [Online]. Available: https://signetlabdei.github.io/lorawan-docs/models/build/html/lorawan.html#. [Accessed: 17-Feb-2023].

Analysis of Cloud Security using TLS/HTTP/TCTP

Abstract:
Cloud security solutions commonly use HTTP intermediaries which include reverse proxies, load balancers, and intrusion prevention systems. Which acts as the TLS server connection ends and access HTTP/TLS plaintext to perform their functions. This method chooses its configuration randomly without considering the vulnerability to attacks and outside threats. Further, it has various other shortcomings such as inefficient presentation languages, message flow vulnerabilities and the circumvention of HHTP streaming. Fueled by cloud adoption by large enterprises increasing exponentially, the need for improvement and cunning edge security arises. One of the potential solutions that addresses these issues is the Trusted Cloud Transfer Protocol, which applies entity body encryption that can overcome these vulnerabilities. The key concept of TCTP is HTTP application layer encryption channels which integrate TLS functionality into the HTTP application layer. In this project, we will delve deeper into TCTP and other potential methods in relation to cloud security.

References:
[1] M. Slawik, "The Trusted Cloud Transfer Protocol," 2013 IEEE 5th International Conference on Cloud Computing Technology and Science, Bristol, UK, 2013, pp. 203-208, doi: 10.1109/CloudCom.2013.126. [Accessed: 26-Feb-2023]
[2] S. Müller, D. Bermbach, S. Tai and F. Pallas, "Benchmarking the Performance Impact of Transport Layer Security in Cloud Database Systems," 2014 IEEE International Conference on Cloud Engineering, Boston, MA, USA, 2014, pp. 27-36, doi: 10.1109/IC2E.2014.48. [Accessed: 26-Feb-2023]
[3] M. Msahli, M. T. Hammi and A. Serhrouchni, "Safe box cloud authentication using TLS extesion," 2015 International Conference on Cyber Security of Smart Cities, Industrial Control System and Communications (SSIC), Shanghai, China, 2015, pp. 1-6, doi: 10.1109/SSIC.2015.7245679. [Accessed: 26- Feb-2023]
[4] Jabir, Raja & Khanji, Salam & Ahmad, Liza & Alfandi, Omar & Said, Huwida. (2016). Analysis of cloud computing attacks and countermeasures. 1-1. 10.1109/ICACT.2016.7423295. [Accessed: 26-Feb-2023]
[5] Singh, I. D. (2013, December). Data Security in cloud oriented application using SSL/TLS protocol - IJAIEM. Data Security in Cloud Oriented Application Using SSL/TLS Protocol. Retrieved February 27, 2023, from https://ijaiem.org/volume2issue12/IJAIEM-2013-12-10-022.pdf [Accessed: 26-Feb-2023]

ns-3 Simulation of Propagation Loss for Various LoRa Chirp Variations of RYLR896 Module

Abstract:
LoRaWAN (Long Range Wireless Area Network) is a wireless communication protocol that makes use of the unlicensed spectrum. It is optimized for low-power and long-range applications as its name suggests, implementing 2 different tyes of nodes, gateways and end devices which are capable of communicating using a signal that sweeps multiple frequencies as it travels in time, also known as chirp. A chirp is capable of encoding information while providing resiliency to interference and therefore a long range. This study leverages ns-3 to implement a mechanism to simulate scenarios where the chirp characteristics are not fixed, just like in real-life deployed gateways and end devices, where the chirp characteristics change on a regular basis. To achieve this, a LoRaWAN module (RYLR896: SX1276 chip with antenna) was selected to be modelled in the ns-3 simulation. As a result, the behavior of LoRa products that make use of that specific LoRa module can be more accurately simulated on ns-3.

References:
[1] U. Raza, P. Kulkarni and M. Sooriyabandara, "Low power wide area networks: An overview", IEEE Commun. Surveys Tuts., vol. 19, no. 2, pp. 855-873, 2017.
[2] D. Magrin, M. Centenaro and L. Vangelista, "Performance evaluation of LoRa networks in a smart city scenario," 2017 IEEE International Conference on Communications (ICC), Paris, France, 2017, pp. 1-7, doi: 10.1109/ICC.2017.7996384.
[3] F. Van den Abeele, J. Haxhibeqiri, I. Moerman and J. Hoebeke, "Scalability Analysis of Large-Scale LoRaWAN Networks in ns-3," IEEE Internet of Things Journal, vol. 4, no. 6, pp. 2186-2198, Dec. 2017, doi: 10.1109/JIOT.2017.2768498.
[4] Semtech, “SX1726 Product Details”. [Online]. Available: https://www.semtech.com/products/wireless-rf/lora-connect/sx1276
[5] Reyax Technology, “RYLR896 Specification”. [Online]. Available: https://reyax.com/products/rylr896/
[6] A. Gutiérrez-Gómez et al., “A Propagation Study of LoRa P2P Links for IoT Applications: The Case of Near-Surface Measurements over Semitropical Rivers,” Sensors, vol. 21, no. 20, p. 6872, Oct. 2021, doi: 10.3390/s21206872. [Online]. Available: http://dx.doi.org/10.3390/s21206872
[7] G. Codeluppi, A. Cilfone, L. Davoli, and G. Ferrari, “LoRaFarM: A LoRaWAN-Based Smart Farming Modular IoT Architecture,” Sensors, vol. 20, no. 7, p. 2028, Apr. 2020, doi: 10.3390/s20072028. [Online]. Available: http://dx.doi.org/10.3390/s20072028
[8] V. Talla, M. Hessar,B. Kellogg, A. Najafi, J. Smith, S. Gollakota. “LoRa Backscatter: Enabling The Vision of Ubiquitous Connectivity”. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies. May 2017, doi: 10.1145/3130970. [Online]. Available: https://doi.org/10.1145/3130970

Performance of UDP and TCP over 5G network

Abstract:
5G or the fifth-generation cellular network is the successor to 4G networks that use mmWave technology to achieve high throughputs (around 10 Gbps). In this paper, we will simulate a 5G network over an ns-3 simulator and study the performance of the User Datagram Protocol and Transmission Control Protocol. The ns-3 simulator is highly customizable as it offers a cross-layer design which helps in testing new 5G protocols [4]. Although many performance metrics exist today, we will use delay, jitter, throughput, and packet loss to compare the performance of these two protocols. Some advantages of TCP vs UDP are already known, such as reliable transmission in TCP and low delay in UDP over 4G and wired networks [5]. These characteristics will be analyzed in depth in 5G in addition to whether 5G simulated networks are suitable for data transmission [5].

References:
[1] J. P. Postel, “Transmission control protocol,„ RFC Editor, September-1981. [Online]. Available: https://www.rfc-editor.org/rfc/rfc793. [Accessed: 21-Feb-2023].
[2] J. P. Postel, “User Datagraml protocol,„ RFC Editor, 28-Aug-1980. [Online]. Available: https://www.rfc-editor.org/rfc/rfc768. [Accessed: 21-Feb-2023].
[3] S. A. Nor, R. Alubady, and W. A. Kamil, “Simulated performance of TCP, SCTP, DCCP and UDP protocols over 4G network,„ Procedia Computer Science, 23-Aug-2017. [Online]. Available: https://www.sciencedirect.com/science/article/pii/S1877050917311754. [Accessed: 21-Feb-2023].
[4] M. Mezzavilla et al., "End-to-End Simulation of 5G mmWave Networks," in IEEE Communications Surveys & Tutorials, vol. 20, no. 3, pp. 2237-2263, thirdquarter 2018, doi: 10.1109/COMST.2018.2828880.
[5] D. Madhuri and P. C. Reddy, "Performance comparison of TCP, UDP, and SCTP in a wired network," 2016 International Conference on Communication and Electronics Systems (ICCES), Coimbatore, India, 2016, pp. 1-6, doi: 10.1109/CESYS.2016.7889934.

A Study of How VPN Connections to Different Geographic Locations Affect CDN Streaming Latency

Abstract:
Virtual Private Networks, also known as VPNs, are a cost-effective method for the common person to maintain internet security. Mainly, it protects confidential user data from packet sniffing on public networks and allows remote staff and offices to access company servers securely. VPNs can also bypass internet restrictions in certain countries, and can even prevent bandwidth throttling from Internet Service Providers. However, using a VPN can have its downsides. In regards to using a VPN for streaming content, increased distances between a user and VPN server location can affect latency. Similarly, VPN servers can be another bottleneck where congestion can further affect user experience. This report will explore how the use of a VPN server for streaming in other countries can decrease latency and possible ways this issue can be minimized. 

References:
[1] Z. Zhipeng, S. Chandel, S. Jingyao, Y. Shilin, Y. Yunnan and Z. Jingji, "VPN: a Boon or Trap? : A Comparative Study of MPLS, IPSec, and SSL Virtual Private Networks," 2018 Second International Conference on Computing Methodologies and Communication (ICCMC), Erode, India, 2018, pp. 510-515, doi: 10.1109/ICCMC.2018.8487653.
[2] Eglė Juodytė, “Does a VPN decrease internet speed? Let’s test it”, NordVPN, 2022. [Online]. Available: https://nordvpn.com/blog/does-vpn-slow-down-internet/. [Accessed: 20- Feb- 2023].
[3] X. Wei, L. Guo, Y. Wang, X. Liu and J. Deng, "Research and design of high performance VPN Security System Based on VPP," 2021 7th International Conference on Computer and Communications (ICCC), Chengdu, China, 2021, pp. 2038-2041, doi: 10.1109/ICCC54389.2021.9674530.
[4] Cantrell, C., Henmi, A., Lucas, M., & Singh, A. (2006). Firewall policies and VPN configurations Anne Henmi, technical editor ; Mark Lucas, Abhishek Singh, Chris Cantrell. (1st edition.). Syngress. Paul, I. (2022). Best VPN services: Top picks for speed, price, privacy, and more. PCWorld, 40(1), 57–66. ​
[5] Gentile, A. F., Fazio, P., & Miceli, G. (2021). A survey on the implementation and management of Secure Virtual Private Networks (vpns) and virtual lans (vlans) in static and mobile scenarios. Telecom, 2(4), 430–445. https://doi.org/10.3390/telecom2040025
[6] Pena, C. J. C., & Evans, J. (2000). Performance evaluation of software virtual private networks (VPN). Proceedings 25th Annual IEEE Conference on Local Computer Networks. LCN 2000, 552. https://doi.org/10.1109/lcn.2000.891094 Veidenbaum, A., Joe, K., Amano, H., & Aiso, H. (2003). High performance computing: 5th International Symposium, Ishpc 2003: Proceedings. Springer.
[7] Da-yuan, Z., Yi-xin, J., Chuang, L., & Yan-xi, L. (2005). Implementation and performance evaluation of IPSec VPN based on Netfilter. Wuhan University Journal of Natural Sciences, 10(1), 98–102. https://doi.org/10.1007/bf02828626

Evaluating Congestion of a Wi-Fi Positioning System in a Shopping Mall Simulation for Indoor Navigation

Abstract:
GPS has long been recognized as a prevalent positioning system, yet Wi-Fi Positioning Systems (WPS) are gaining increased attention as a viable alternative for scenarios in which GPS availability is limited [1, 2]. Numerous empirical studies have demonstrated the feasibility of utilizing Wi-Fi networks for location determination, utilizing a diverse array of complexities and techniques. However, these investigations have primarily focused on the accuracy of a single user, rather than examining the practical implications of multi-user scenarios. This research project proposes to investigate the Time of Flight positioning methodology through simulation utilizing the ns-3 platform. The simulation will be designed to replicate a shopping mall environment, incorporating multiple users in a large room and evaluating the accuracy of position determination through Round Trip Time (RTT) analysis. Furthermore, the impact of network congestion during periods of high traffic, as well as the cost implications of maintaining such a system will also be analyzed.

References:
[1] F. Zafari, A. Gkelias, and K. K. Leung, “A Survey of Indoor Localization Systems and Technologies,” IEEE Communications Surveys & Tutorials, vol. 21, no. 3, pp. 2568-2599, Apr. 2019.
[2] L. Schauer, F. Dorfmeister, and M. Maier, “Potentials and limitations of WIFI-positioning using time-of-flight,” International Conference on Indoor Positioning and Indoor Navigation, 2013.
[3] Y. Zeng, P. H. Pathak, and P. Mohapatra, “Analyzing shopper's behavior through WIFI signals,” Proceedings of the 2nd workshop on Workshop on Physical Analytics, pp. 13-18, May 2015.
[4] J. Etter-Olguín, C. Duran-Faundez, J. Rohten, R. Seguel-Cárdenas, and I. Santana, “Simulación de algoritmos de posicionamiento basados en RSSI pararedes inalámbricas utilizando ns-3”, XVIII Simposio de Ingeniería Eléctrica SIE-2019, 2019.
[5] Y. Liu, D. Cheng, T. Pei, H. Shu, X. Ge, T. Ma, Y. Du, Y. Ou, M. Wang, and L. Xu, “Inferring gender and age of customers in shopping malls via indoor positioning data,” Environment and Planning B: Urban Analytics and City Science, vol. 47, no. 9, pp. 1672-1689, Apr. 2019.
[6] M. Cypriani and F. Lassabe, "Open Wireless positioning System" in , France:Computer Science Laboratory of the University of Franche-Comte, 2009.
[7] J. Shen, J. Cao, X. Liu, and S. Tang, “Snow: Detecting shopping groups using WIFI,” IEEE Internet of Things Journal, vol. 5, no. 5, pp. 3908-3917, May 2018.

Performance Analysis of Video Streaming on 5G Networks

Abstract:
5G is the mobile network of the future that has only recently entered the market in 2019 with hopes of covering 65% of the world's population by 2025. The traffic for videos delivered over the Internet will reach 82% of the total Internet traffic by 2021 with a million minutes of video content crossing the network [3]. This paper will analyze the performance of video streaming under various scenarios relating to network load using the ns-3 simulator and trace data.

References:
[1] Dapeng Wu, Y. T. Hou, Wenwu Zhu, Ya-Qin Zhang and J. M. Peha, "Streaming video over the Internet: approaches and directions," in IEEE Transactions on Circuits and Systems for Video Technology, vol. 11, no. 3, pp. 282-300, March 2001, doi: 10.1109/76.911156. (visited on 02/25/2023)
[2] M. Uitto and A. Heikkinen, "Evaluation of Live Video Streaming Performance for Low Latency Use Cases in 5G," 2021 Joint European Conference on Networks and Communications & 6G Summit (EuCNC/6G Summit), Porto, Portugal, 2021, pp. 431-436, doi: 10.1109/EuCNC/6GSummit51104.2021.9482605. (visited on 02/25/2023)
[3] G. Minopoulos, K. E. Psannis, G. Kokkonis and Y. Ishibashi, "QoE Assessment of Video Codecs for Video Streaming over 5G Networks," 2020 3rd World Symposium on Communication Engineering (WSCE), Thessaloniki, Greece, 2020, pp. 34-38, doi: 10.1109/WSCE51339.2020.9275576. Available: https://ieeexplore.ieee.org/document/9275576 (visited on 02/25/2023)
[4] A. Martin et al., "Network Resource Allocation System for QoE-Aware Delivery of Media Services in 5G Networks," in IEEE Transactions on Broadcasting, vol. 64, no. 2, pp. 561-574, June 2018, doi: 10.1109/TBC.2018.2828608. Available: https://ieeexplore.ieee.org/document/8354944 (visited on 02/25/2023)
[5] M. Uitto and A. Heikkinen, "Evaluating 5G uplink performance in low latency video streaming," 2022 Joint European Conference on Networks and Communications & 6G Summit (EuCNC/6G Summit), Grenoble, France, 2022, pp. 393-398, doi: 10.1109/EuCNC/6GSummit54941.2022.9815703.