Wireless networks and performance evaluation

To create and implement wireless routing method such as IEEE 802.11 to transfer data efficiently and make a comparison of the two Network simulators NS3 and NS2. The project has been divided into 3 tasks.

Task 1

Q1.

Explore and analyze the following network simulator and write a short comparative study report.

NS3 and NS2

Answer ?

Introduction of Network Simulators

NS2 and NS3 are both widely used network simulators based on “discrete event simulation [1].” They are primarily employed in research and educational contexts. This report provides a comparison of these two simulators, focusing on their key features, as well as their relative strengths and weaknesses.

Overview of NS2

“NS2 started as a revision of ns-1. From 1997 to 2000. Its development was funded by DARPA through the VINT project at LBL,” Xerox PARC, UC Berkeley, and USC/ISI. In 2000.

As shown in Fig. 4.1, the network architecture is derived from “[2]

Key features of NS2:

It is compatible with a wide variety of network protocols.
Large numbers of users and a substantial amount of documentation.
A sizeable number of models that have been provided are currently available. It is compatible with a wide variety of network protocols.
Large numbers of users and a substantial amount of documentation.
A sizeable number of models that have been provided are currently available.

“NS2 provides numerous benefits, notably its established presence and extensive application in academic research.[3]” It has an extensive repository of protocols and network models, rendering it an indispensable resource for academics and instructors. Nonetheless, significant drawbacks exist, including the dual language framework (C++ and OTCL), which may pose difficulties for novices to comprehend. Furthermore, NS2 exhibits constrained scalability for extensive networks and is impeded by antiquated graphics and visualization features.

Overview of NS3

NS3 is the sequel to NS2, and it addresses some of the shortcomings that were present in NS2. C++ is the only language used to write NS3, and Python bindings are available as an option.

Shape2

NS3 Simulation 1

Key features:

Enhanced Performance and more scalable in nature.
Enhanced software architecture.
Flexible in making more complex network scenes.

The utilization of a singular language, C++, in this scenario offers the benefit of simplicity in learning and application, while it poses a more challenging learning curve for individuals previously acquainted with NS2. Moreover, although there are less models accessible in comparison to NS2, this disparity is progressively diminishing. An important advantage is enhanced support for parallel and distributed simulation.

Comparison between NS2 AND NS3

S/N	Properties	NS2 Simulator
1	Core Language	C++ core with OTcl scripting interface
2	Ease of Use	More complex due to dual-language structure
3	Model Availability	Larger collection of contributed models
4	Performance & Scalability	Sufficient for most cases but less efficient for large-scale simulations
5	Development Activity	Limited active development in recent years
6	Community & Documentation	Well-documented with an established user base
7	Network Modeling Accuracy	Adequate for most simulations

S/N	Properties	NS3 Simulator
1	Core Language	Entirely in C++ with optional Python bindings
2	Ease of Use	Steeper learning curve initially but easier to manage after learning
3	Model Availability	Fewer models, but growing rapidly with active development
4	Performance & Scalability	Better performance and scalability, especially for large networks
5	Development Activity	Ongoing active development with frequent updates and new features
6	Community & Documentation	Improving documentation and a growing community
7	Network Modeling Accuracy	More accurate and realistic network modeling

Q2.

What is the latest version of NS3 simulator? What new features are added in the latest version of the NS3 simulator? Write a short report on the Changes from NS-3.38 to latest version of NS3 simulator. Describe the new API and model change history of NS3.

LATEST VERSION OF NS3 Simulator

NS-3.42, the current version of this tool for network protocols and systems simulation, was released on 29th May 2024.

New features are added in the latest version of the NS3 simulator

The release of this attests to the development work that has been invested in NS-3 and further contributes to its good production output. Relating this to the topic at hand, it is not surprising that NS-3 has become a valuable tool for research and education in networking.

It includes multiple enhancements and new features that further allow more accurate and efficient network simulation.

Further flexibility is availed in NS3, the facility for real-world networks and devices to be integrated with it, thus providing hybrid simulations-a mix of virtual and physical. It provides several visualization tools that may be used in analyzing and interpreting simulation results.

NS-3 is an open-source network simulation tool that features a bundle of powerful features and is designed to be modular to let users extend new protocols and functionalities. It is free, giving the right to read, modify, and extend the codebase for flexibility in user custom solutions. Its one important feature is that it supports different networking protocols at different layers, like WiFi/LTE and TCP/IP.

“NS3 has very extensive network modeling capability, hence providing realism in network simulation [4]”. It can be scaled up to large-size networks with thousands of nodes and is hence ideal for testing and research pertaining to a wide range of networking scenarios.

NS3 runs on Linux, macOS, and Windows OS; it is continuously updated, and extensive documentation with user support is available.

NS-3 is a reproducibility principle, which by default means that simulations could be easily replicated. So, given all advantages listed above, NS-3 is really a very good tool in which scientific research and debugging may be performed.

Write a short report on the Changes from NS-3.38 to latest version of NS3 simulator

From the version NS 3.38 and onwards, a lot of performance, usability, and core improvements have been made to the “NS-3 network simulator [4]”. The new release introduces improved memory management and faster execution times by using modern C++ standards support, ensuring, all things considered, better handling of simulations, big networks. Refactoring also occurred for Python bindings and resulted in a much smoother experience for users who were used to scripting in Python. These changes constitute the development environment more accessible and productive for developers working with NS-3.

In terms of features, there have been the addition of several new protocol models to it, essentially positioning NS-3 to keep pace with current networking technologies like 5G, IoT, and SDN. Updates of existing in-tree models in Wi-Fi and LTE/5G further improve the capability of this simulator to realistically emulate modern wireless and cellular network environments. Wi-Fi models now support emerging standards, including Wi-Fi 6, while LTE/5G models further support handovers and mobility management to achieve higher fidelity and realism in simulations.

Also, the new version of NS-3 has several bug fixes and stability enhancements. Fixed bugs and crashes that appeared in the NS-3.38 version, including memory leaks. Optimizations have also been made to distributed simulations, enhancing performance on multiple machines. Documentation has been extended to be more intuitive, both for newcomers and for advanced users. Tutorials have been updated to reflect the current capabilities. Growing community support combined with maintaining backward compatibility policy will continue to give users an opportunity to conduct practically any kind of network simulation task using NS-3 without big disruptions.

Describe the new API and model change history of NS3.

NS3 has had quite a few updates and changes over the course of the timeline. All the same, one may include:

Changes in APIs

NS3 has moved to a modular architecture where it is easy to integrate modules. The migration to C++11/14/17 standards have improved readability and performance. Smart pointers have increased to handle memory management. The callback system has enhanced event handling. The attribute system has been refined to have flexible methods of setting simulation parameters. Even the logging system has improved to facilitate the debugging and analysis process.

Changes in the Model

“WiFi models are enhanced [4]”, while LTE and 5G NR models are extended, including mmWave models. An updated TCP congestion control algorithm model, IPv6 support and QUIC protocol models add to the update. Also included in the update are new application layers, improved energy models, and more sophisticated channel models in different environments.

If we talk about enhancements then it also includes enhanced simulation speed and scalability, enhanced support for parallel and distributed simulations, and improved integration with visualization tools like “NetAnim” for performance analysis.

Task 2

Q2. Write a Multihop Adhoc wireless networks program for simulating in the NS3 simulator. Name the program as your group number.

The NS-3 simulation tool will be used to simulate an ad-hoc multihop wireless network, involving node preparation, wireless device setup, and packet recording files. A C++ program will be used to simulate this scenario.

Step 1 ? Obtain the NS3 Simulator from the supplied link. https://www.nsnam.org/

Step 2 ? Transfer the supplied code to the "Scratch" directory and rename it according to the specified format "'GroupNumber.cc

Step 3 ? Initiate the Ubuntu operating system interface from your Windows environment or virtual machine.

Step 4 ? Enter 'cd' command to change the directory and 'ls' to list the directory contents.

Step 5 ? Access the ns-allinone-3.38 and ns-3.38 directories and list their contents.

Step 6 ? Take the command "./build.py" and execute it.

Step 7 ? Change directory

Step 8 ? Execute the command: ./ns3 run scratch/ML_JS_G3.cc

Step 9 ? Execute the NetAnim command to launch the netAnim interface.

Step 10 ? Choose the XML file from the interface provided by the netAdmin.

Step 11 ? Navigate to the Scratch folder and click on your ML_JS_G3.xml” file

Step 12 ?Generation of Code for 5 packet node creation

Step 13 ? Study the activity on the network as well as the packets coming from the five different nodes.

Task 3

Q3.

Many wireless devices use wireless technology, yet they lack the necessary security protections. In an Australian Information Security Association (AISA) members gathering in Melbourne a security researcher, who has himself a diabetic, demonstrated a wireless attack on an insulin pump that could change the delivery of the patient. In this gathering another AISA member who is a security vendor found that they can scan a public space from up to 91 meters (300 feet) away, find vulnerable pumps made by a specific medical device manufacturer, and then force these devices to dispense fatal insulin doses. Based on the above scenario write a short report and answer the following questions:

Conduct research the current state of the attacks on wireless medical devices and proposed defenses to mitigate the attack.

Current State of Attacks against Wireless Medical Devices

Wireless medical devices like insulin pumps and pacemakers are improving patient care through real-time monitoring and data transmission. However, they also present new security vulnerabilities due to increasing cyberattacks, including manipulation of device performance, data loss, and patient life jeopardy. Common types of attacks against wireless medical devices include:

A Man-in-the-Middle (MitM) attack occurs when a cyber adversary intercepts and potentially alters the communication between a medical device and its control system, healthcare provider, or patient monitoring system. In this type of attack, the adversary positions themselves between the communicating entities, gaining unauthorized access to sensitive data being transmitted. By manipulating this data, they can alter the functioning of the device in harmful ways. For example, an attacker could intercept and modify information transmitted between an insulin pump and its controller, changing the dosage information sent to the device. This manipulation could result in the patient receiving too much or too little insulin, leading to serious health consequences, such as hypoglycemia or hyperglycemia. Such attacks compromise the integrity and reliability of medical devices, placing patients' lives in jeopardy.

Denial of Service (DoS) Attacks:

A Denial of Service (DoS) attack is another common type of cyberattack on wireless medical devices, targeting the availability and functionality of these critical systems. In a DoS attack, the attacker floods either the device itself or the network it relies on with an excessive volume of requests, rendering the device unresponsive or unable to communicate properly. For medical devices that rely on timely updates or commands, this could lead to a significant breakdown in functionality. For instance, a medical device may be prevented from receiving important instructions from a healthcare provider or a critical software update due to the overwhelming network traffic. This disruption could cause delays or complete failure in the device’s ability to monitor or treat a patient, putting the patient's health at severe risk. In extreme cases, it could result in the device being unable to deliver life-saving interventions in emergencies.

Replay Attacks: In this attack, the intruder captures and re-transmits valid traffic between a given medical device and its associated network. It might make the gadget respond to some stale or malicious commands, such as the dosage of some medicine not supposed to be given under those circumstances.

Malware and Ransomware: Malware risks can affect device functionality and data integrity. Recent ransomware software encrypts data and holds it ransom until a buyback deal is agreed upon.

Data Breaches: Patient health data transferred through wireless devices is sensitive and vulnerable to identity theft, insurance fraud, and black-market sales. Unencrypted or insufficiently protected data transmissions can significantly compromise patient privacy.

Defenses Proposed to Mitigate the Attacks

The cybersecurity concerns of wireless medical devices need multi-faceted technological, regulatory, and procedural defenses. Some of the proposed strategies to mitigate such types of attacks may be based on:

Improved encryption protocols: More efficient encryption mechanisms must be used in the communication links between wireless medical devices and external systems. The confidentiality and integrity of critical health information can be assured by an end-to-end encryption method from unauthorized access or modification during transmission. Device Authentication and Access Control: Medical devices should provide multi-factor

Should the vendors who make this wireless medical device be forced to add security to their devices? What should be penalty if they do not?

Yes, manufacturers of wireless medical devices should be compelled to include sound security while developing their products. These devices are life-critical in nature and compromising their security would put lives in jeopardy; thus, safety and integrity for these devices need to be paramount. Without proper security, vulnerabilities in medical devices can lead to dangerous situations, including attacks disabling or manipulating the device with the aim of harming the patient or disclosing personal health data.

Security should not be an afterthought; it needs to be part and parcel of the design, considering the sensitive nature of data being transmitted and the true consequences that device malfunction may lead to. These devices are also of special interest to governments, regulatory bodies, and healthcare institutions, which would want to make sure they were safe, secure, and reliable. Even with existing regulations, like those from the FDA or the MDR, that place great emphasis on cybersecurity in medical devices, even more strict guidelines must be clearly provided and followed through to full compliance.

Non-compliance Penalty

For instance, another stringent punitive effectiveness should be included in the policy to ensure that the vendors do not take security for granted. These include but are not limited to:

Fines and Legal Penalties: If a vendor does not use the proper security, then there is a need for heavy fines in keeping with the proportionate level of risk or harm posed by the vulnerability. Fines need to be severe enough not to take shortcuts when deployed around security host devices. Legal liabilities will have to be laid if any damage takes place because of a security breach that could have been prevented.

Recalls or Bans: Regulatory authorities may implement recalls or market bans of devices that are proven to not meet the required security standards. This would eventually give the patients protection over such unsafe devices while compelling the manufacturers themselves to do more on their security practices, lest costly recalls with attributed reputation damage be incurred.

"Certification" status can hold up the sale or use of the medical devices in actual clinical use. Many times, these medical devices require to get certification from regulating agencies, prior to their marketing. If a vendor does not come up to the security requirements, then these certifications should be withheld by the agencies.

Damages Liability: The liability of some Vendors for damages incurred due to an attack or vulnerability may be related to finance and the court of law. Liability for manufacturers schedules to the patient and consequent injury or death based on the claims brought against the safety of the device the liability is to compensate.

In other words, it should be made mandatory for the governors to enforce heavy fines, product-bans, and any sort of legal liabilities relevant to these vendors, so that there is complete accountability in the medical device vendor business.

c) As per Australian cyber security laws, what should be the penalty for an attacker who manipulates a wireless device.

Thus, the exact punishments for such cyber-related crimes, including those threatening the healthcare systems and medical devices, are identified in the Criminal Code Act 1995 in Australia. Manipulation of a wireless medical device can come under several sections of such an Act: unauthorized access, data modification, and interference with a device, particularly if it threatens life or public safety. Given the very serious implications criminal tampering with a medical device may carry, the penalties for this offense can be severe.

Here are some of the key highlights that Australian law provides against such miscreants who tamper with medical wireless devices:

Unauthorized Disclosure or Tampering of Sensitive Information Beyond the Legal Constraints.

Any attacker, intending to cause unauthorized access or alteration with an intention to commit any fraud in relation to any data stored or transmitted by the medical device, shall be liable under this section. Imprisonment can extend from 2 years up to 10 years, depending on the severity of the crime and its impact, for unauthorized access or modification, respectively.

Sabotage of critical infrastructure

Since such devices are wireless and often integrated into the key healthcare infrastructure, computer-based attacks on these devices likely meet the definition of severe interference with essential services. These devices work at a core function level in human health; therefore, any malicious manipulations will disturb individual patient care and affect the whole healthcare system, placing several lives at risk. Accordingly, such hacker attacks could be brought to justice as an offense against critical infrastructure, to which most serious legal measures are usually applied.

The reprimanding has to be in proportion with the consequences of that attack. Where manipulating a wireless medical gadget result in death, great injury, or significant harm impacting health systems, the legal consequences will be far worse. For those cases where the attack results in the death of a person or widespread damage to the health infrastructure, imprisonment may range from ten years upwards to life imprisonment. Where the attack is particularly malicious, essentially reckless, or if the consequences are far-reaching in respect of patient safety and public health, the penalties escalate further to reflect the critical nature of healthcare infrastructure in maintaining general societal well-being.

Causing serious harm to the body or endangering life.

If such direct manipulation results in harm, for instance, causing death or serious injury to a patient, then charges against the attacker under provisions in relation to endangering life or causing grievous bodily harm can be imposed. This may be punishable by imprisonment, possibly to 25 years or even longer depending upon whether the act was deemed reckless or intentional.

Cyber Terrorism (Section 101.1)

When the attack is politically or ideologically motivated, it is intended to intimidate a government or section of the public. That said, the offense may rightfully be regarded as “cyber [5]” terrorism. It carries a maximum penalty of life imprisonment.

Aggravating Factors Financially Motivated or Ransomware: Where a threat is coupled with an extortion, such as the payment of ransom to return a normal function of them. Repeat Offenders: A penalty can also increase based on another conviction for the misuse of cyber elements.

Australian cybersecurity laws would come heavily upon such an attacker, even imprisoning life imprisonment in cases where this causes serious injury or puts lives at risk. The penalty varies according to the nature of the crime and its consequences and the surrounding circumstances; however, Australia adopts very strict approaches towards cybercrime when it concerns critical health infrastructures.

Conclusion

An increasing number of academics and educators are gravitating toward NS3 as their preferred alternative, even though NS2 has been an essential tool in network modeling for a considerable amount of time. Not only does NS3 offer improved performance and scalability, but it also offers more authentic modeling capabilities. Despite this, NS2 continues to be superior in terms of the availability of models and the respect it has received from the academic community.

It is possible that the choice between NS2 and NS3 will be determined by the specific needs of the project, the applicant's existing experience with either simulator, and the requirement for models or protocols. NS3 is often recommended for new applications, particularly those that require high performance or simulations that provide an accurate representation of the real world.

References

[1] R. M. AbouRizk and S. M. Hague, "A hybrid integrated approach for simulating construction projects," Journal of Construction Engineering and Management, vol. 129, no. 5, pp. 537–546, Oct. 2003, https://ascelibrary.org/doi/abs/10.1061/(ASCE)0733-9364(2003)129:5(537) [Accessed: Sep. 12, 2024]

[2] K. Salah, "Boost TCP Performance in Wired-Cum-Wireless Networks," in Simulation in Computer Network Design and Modeling: Use and Analysis, A. S. Sobh, Ed. Springer, 2012, pp. 77–97. [Online]. Available: https://link.springer.com/chapter/10.1007/978-1-4614-1406-3_4 [Accessed: Sep. 12, 2024]

[3] P. S. Katkar, "Comparative study of network simulator: NS2 and NS3," International Journal of Advanced Research in Computer Science and Software Engineering, vol. 6, no. 3, pp. 608–612, 2016. [Online]. Available: https://www.ijarcsse.com/docs/papers/Volume_6/3_March2016/V6I3-0391.pdf [Accessed: Sep. 12, 2024].

[4] M. Alwateer, B. G. Stewart, and S. L. Shimi, "A novel fuzzy-based network selection approach for Internet of Medical Things (IoMT)," Computer Communications, vol. 219, pp. 11-21, 2023. [Online]. Available: https://www.sciencedirect.com/science/article/abs/pii/S0140366423002621?via%3Dihub. [Accessed: Sep. 12, 2024]

[5] R. M. Parizi, "A Software Quality Model for Object-Oriented Software," International Journal of Information Technology Project Management (IJITPM), vol. 4, no. 1, pp. 31-44, Jan. 2013. [Online]. Available: https://www.igi-global.com/gateway/article/104520 [Accessed: Sep. 12, 2024]