Factors Influencing Wi-Fi Signal Speed and Attenuation
Table of Contents (linked to section)
1. Abstract
The purpose of the first experiment was to understand how a 5 GHz radio frequency (RF) signal, more specifically a wireless fidelity (Wi-Fi) signal, is affected after passing through various materials that are well-known for their RF signal dampening qualities. This lab consists of two different experiments. The first experiment aims to find the material(s) that block RF signals most effectively, and the second experiment test which orientation of the material is most effective at blocking RF signals. In both experiments, I collected data on two main variables: network speed, and network strength. This series of experiments was automated using various programs, which have been built using the language Python, of which some used for data collection and information gathering, and some used for data analysis and visualization. Using a directional wireless antenna, the signal coverage, direction, and amplitude can all be easily controlled. I will be using the data that I collect to refine the development of a working prototype “shield” that effectively blocks Wi-Fi signals from potential cybercriminals.
2. Introduction
Wi-Fi network security has been left on the backburner of the field of cybersecurity since the implementation of WPA2 encryption security. This protocol made it more difficult to crack Wi-Fi passcodes by encrypting a shared key between the client and host, and the client can only connect if the encrypted key matches that of the host. Advancements in password cracking, however, have lead to faster methods of gaining unauthorized access to wireless networks, despite the increased security. Popular programs such as Aircrack-ng, inSSIDer, and Airjack have allowed cybercriminals to crack a business’s Wi-Fi password in order to gain access to valuable information, without gaining physical access to the inside of the business.
Wireless Defender seeks to put an end to this problem by blocking Wi-Fi signals from leaving the walls of a small or medium business, the most targeted group in cybercrime. Utilizing radio frequency (RF) blocking technology, we can put an end to cybercriminals hijacking a business’s network, and restore peace of mind to business owners/management.
In order to build our shield, we need to conduct testing on the ways that a Wi-Fi signal is affected by various types of materials and orientations. In each of our experiments, we will be collecting data on three (3) different variables including network strength (dBm), ping speed (ms), and percentage of packets lost (%). Based on the data gathered from these experiments, I will develop the most efficient product in preventing RF signals from passing through the exterior walls of a business. I hypothesize that the copper sheet metal with RF dampening fabric will be best to use as the core material of the shield, because of it’s known frequency-blocking characteristics.
Wireless Defender seeks to put an end to this problem by blocking Wi-Fi signals from leaving the walls of a small or medium business, the most targeted group in cybercrime. Utilizing radio frequency (RF) blocking technology, we can put an end to cybercriminals hijacking a business’s network, and restore peace of mind to business owners/management.
In order to build our shield, we need to conduct testing on the ways that a Wi-Fi signal is affected by various types of materials and orientations. In each of our experiments, we will be collecting data on three (3) different variables including network strength (dBm), ping speed (ms), and percentage of packets lost (%). Based on the data gathered from these experiments, I will develop the most efficient product in preventing RF signals from passing through the exterior walls of a business. I hypothesize that the copper sheet metal with RF dampening fabric will be best to use as the core material of the shield, because of it’s known frequency-blocking characteristics.
3. Variables
3.1 Independent Variable |
Experiment 1: Core Material (Metal) Used
Experiment 2: Orientation of Core Material |
3.2 Dependent Variable |
Percentage of Packets Lost (%), Ping Speed (ms), Network Strength (dBm)
|
3.3 Control Variables |
Python Networking Constants:
|
constants.py
|
4. Material List
- Netgear AC 1000 Dual Band Wi-Fi Router
- APA-M25 Dual Band High-Gain Directional Antenna Panel
- 12in. x 24in. Aluminum Sheet
- 12in. x 24in. Expanded Steel Sheet
- 12in. x 24in. Copper Sheet
- TitanRF Faraday Fabric
4.1 Software |
4.1.1 Wireshark |
Wireshark is the most popular network protocol analyzer. It allows a user to capture and analyze every packet that is sent over the local network. If an individual packet is selected, as in Figure 1 (above), the data contained in the packet is also revealed, and can potentially be decrypted based on the protocol. In the image above, using the pingdata.py program on the right (See 4.2.2 Python Ping Data), 10 packets are sent over the local network, and the packet date is revealed using Wireshark on the left.
|
4.1.2 NetSpot |
NetSpot is an important tool in Wi-Fi security analysis, as it can help locate and eliminate rogue access points, detect unauthorized workstations, help avoid cross-channel interference and get rid of false-positive intrusion alerts. We will be using this software to collect data on the change of signal attenuation, or signal strength. This is measured in dBm (decibels relative to one milliwatt) found on the y-axis in Figure 2 (above).
|
When working on a Wi-Fi network that will provide an optimal coverage, you'll need to have conducted solid research to understand radio frequencies' behavior. The most effective way to visualize the signal's behavior from a source is to conduct a wireless site survey. This survey will reveal areas of channel interference and dead zones, and will help you tremendously to build a solid network. As seen in Figure 3 (above), the signal strength/attenuation changes based on the location(s) of the access point(s).
|
4.2 Source Code |
4.2.1 Host Communication - Python |
host_connection.py
|
Terminal
|
4.2.2 Ping Data Code - Python |
pingdata.py
|
Terminal
|
Data (CSV File) Parser - Python |
csv_parser.py
|
5. Procedures
5.1 Overview |
I will be conducting experiments on two (2) different factors that could affect the shield’s efficiency in mitigating Wi-Fi and other RF signals from passing through walls. I will be testing which core metal is most efficient and the orientation of the shield. In the first experiment regarding the core metal, I will test three (3) different metals including copper, corrugated steel, and aluminum sheet metal. I will also test the effectivity of covering the metal in RF blocking fabric. In the second experiment, using the best core metal from the preliminary experiment, I will be testing which of the three (3) orientations I have chosen will be best to further block the signals.
5.2 Control Experiment Layout5.3 Core Material and Orientation Experiments Layout5.4 Procedure for Ping Test & Packet Loss Test
5.5 Procedure for Network Strength Test
|
6. Results
6.1 Control Experiment Data (No Signal Interference)
|
6.2 Core Material (Metal) Experiment Data
|
6.3 Shield Orientation Experiment Data
|
7. Conclusion
My initial hypothesis was that the copper sheet metal with RF shielding fabric would prove to be the best use for my RF blocking shield. While this is mostly correct, I actually found that the copper metal worked best for reducing network strength (signal attenuation), I also found that the aluminum metal also worked best for reducing network speed.
I collected and analyzed my data through various Python scripts. I chose to use Python because it is very powerful for automation of data collection. The first python script I developed was to automate the process of pinging the router, or sending packets through the router. This script was able to conduct 3 trials of 50 packets each in a single terminal command. The second Python script I developed took the data I collected from the first script as a .CSV file (comma separated values), and compare the data from the independent variable, to the control data, and found the percent difference.
The data that I have collected is very valuable to the development and refinement of my RF-blocking shield technology, but also my understanding of radio frequency behavior as a whole. Because I concluded that copper and aluminum sheet metal work in unison to reduce network speed and signal strength/attenuation, I will be using both of these metals as the core of my RF-blocking shield. I also found that encasing the sheet metal in RF-shielding fabric significantly reduces both of these factors as well.
I collected and analyzed my data through various Python scripts. I chose to use Python because it is very powerful for automation of data collection. The first python script I developed was to automate the process of pinging the router, or sending packets through the router. This script was able to conduct 3 trials of 50 packets each in a single terminal command. The second Python script I developed took the data I collected from the first script as a .CSV file (comma separated values), and compare the data from the independent variable, to the control data, and found the percent difference.
The data that I have collected is very valuable to the development and refinement of my RF-blocking shield technology, but also my understanding of radio frequency behavior as a whole. Because I concluded that copper and aluminum sheet metal work in unison to reduce network speed and signal strength/attenuation, I will be using both of these metals as the core of my RF-blocking shield. I also found that encasing the sheet metal in RF-shielding fabric significantly reduces both of these factors as well.