Free deep network analyzer software for linux

DNA (Deep Network Analyser) is an open, flexible, and extensible deep network analyzer server and software architecture for passively gathering and analyzing network packets, network sessions, and applications protocols.
Deep Network Analyser project is designed to be used for Internet security, network management, intrustion detection, protocol and network analysis, information gathering, and network monitoring applications.
Main features:
- Extensible Java based network sensor (processing layers 2-7)
Configurable processing and output:
- Packet flows like Ethereal
- IP Flows like CISCO netflow
- Stateful Sessions (client/server flow pairs)
- Application protocol element output
- Configurable and extensible application protocol element parsing.
- Application protocol parsing toolkit APIs allows for new protocol parser to be easily developed and extended
- Targeting based full session capture facility, like a realtime targeted TCPDump.
- Flexible targeting from IPAddr, Port tuple to Application sensitive targeting.
- Configurable and extensible output forwarding (file, DB, Streams, JMS, RMI, etc.)
- Extensible realtime collection portable to many OS/Packet processing environments
Easily adaptable to packet processing environments:
- Specialized linux drivers mechanismon
- Network Appliances
- Network Switches / Routers
- Highly mutithreaded for increased performance over multi processor environments
Enhancements:
- Adoption of OpenAdaptor(tm) as the Output Adapter mechanism.
- Support for local-only administration.
- A new targeted packet capture parser, new run scripts, and a new install mechanism.
- Many bugfixes.

Gnome-Vector-Network-Analyzer is a GTK+/Gnome2 graphical front end for the IW3HEV Vector Network Analyzer, also has a signal generator.
Gnome-Vector-Network-Analyzer displays graphicaly SWR, Phase, Return Loss, X impedance, Serial resistance, |Z| Impedanze, and Inductance, and capacitance.
Enhancements:
- New version with support for the new 180 Mhz miniVNA and the old parallel port 70 Mhz VNA.
- Also with printing capabilities.

Network Traffic Analyser provides a script-driven network traffic monitor.

Network Traffic Analyser (formerly known as sniffer) is designed to be an extremely powerful, configurable, and versatile tool for monitoring network traffic.

It can be used as a plain sniffer, as a tool for accounting, dynamic firewall updates, and many more things.

It features scripting support and an event-driven architecture.

The idea behind this project is to create a powerful tool for playing around with network traffic. The basic concepts are simplicity and flexibility. Instead of building tool that does something specific (and does a good job at it), were trying to build a tool that will be able to do whatever you want it to do (and still be good at it :).

To put it very simply, you write a script that will be invoked for every packet that passes through your network. You write your scripts in a Tcl, fully blown, interpreted programming language. That fact guaranties that you wont be constrained in your creativity.

Funnel Web Analyzer provides essential Web site visitor and traffic analysis.
Every person who visits your companys Web site leaves a trail behind. Your Web server logs their every action and you can use this information to help improve your business. Funnel Web Analyzer provides essential Web site visitor and traffic analysis. It measures everything from server load and referrals to visitor demographics and marketing ROI.
Funnel Web Analyzer helps you optimize your web site by allowing you to analyze how users interact with your site and helps you make informed decisions about what changes you can make to improve their experience.
- What are the demographics of my customers?
- How many unique customers do I have, and how many of these are repeat visitors?
- How long does a visitor spend on each page?
- Which streaming media files are most popular?
- What are my most popular pages?
- How successful was my banner advertisement in attracting visitors to my site?
- What are the peak periods of activity on my site?
- What downloads are most popular?
- What search terms are people using to find my site?
Comprehensive Visitor Analysis
Give your executives and managers unique insight into what your customers are really interested in. Analyzer generates more than 50 different reports and graphs in 12 different languages. Reports can even be customized to reflect your corporate identity and published in a variety of formats including PDF, HTML, Word and Excel.
Identify where users come from before they arrive at your site with the referrals report. This is a great way to measure the effectiveness of promotional campaigns, press releases and affiliate/partner programs. You can even generate separate advertising reports to measure the click-through rates of individual banner ad campaigns.
Funnel Web Analyzer is freeware and provides everything you need to quickly analyze the traffic on your Web site. With virtually no setup, you get an extensive set of valuable reports right from the start.

Dependency Analyzer is a utility for graphically visualizing Maven2 artifacts dependency graphs. It is using Maven embedder for resolving dependencies and based the Java Universal Network/Graph Framework (Jung) for creating and visualizing the dependency graph. Spring rich client is used for building the GUI.
Enhancements:
- This release remembers previously opened pom details.
- It can show where the dependency comes from as a tool-tip on a link. It can show the path(s) from the main artifact to a dependency.
- A print command has been added. Using variables is supported.
- File drag and drop support has been added.

Dell 1600n network scanner driver is a driver for network scanning using a Dell 1600n Printer/Scanner/Fax/Copier.
It is implemented as a Perl script. In principle, this means that it should be cross-platform.
It has been tested under Linux (Debian) and Windows (NT4 with Cygwin) on Intel. Supported formats are TIFF and JPEG. With an external program (e.g. ImageMagick convert), PDF is supported.
Main features:
- TIFF and JPEG network scanning using a Dell 1600n MFP.
- PDF scanning support via an external program (eg: ImageMagick convert)

Python Traffic Analyzer is a Python base class and sample driver script written to retrieve and manipulate images from the TrafficLand cameras and calculate a numeric value representing the current traffic flow.

PyTrAn, an example driver script, an image collector and an image mask creator are available for download from the link shown at the bottom. To use the PyTrAn package begin by choosing a camera that you wish to analyze, for this example well use the camera captioned above.

We want to construct a mask over the area of the image that we are interested in, namely the road. In this particular example the road takes up the majority of the image but that is not always the case.

We will apply the mask over captured images to fine tune the area over which we are looking for movement. To create the mask we will first need to collect a sequential series of snapshots from the target camera. The image_collector.py script was written for this task:

$ mkdir mask_200003
$ cd mask_200003
$ ../image_collector.py 200003 30
Collecting 30 images...
30

Done.

The script is hard coded to capture images on a 2-second delay. The delay is necessary to ensure the image has changed. I believe 2-seconds to be the absolute minimum. Once complete, 30 images numbered 1 through 30 will be created in the current directory.

We construct a mask from these captured images by creating a diff-image for each sequential image pair and then adding each diff-image together. Naturally, a script was written to automate this task as well:

$ ../mask_maker.py 1 30
Creating a diff for each sequential image pair.
Diffing 29

Creating the initial mask from the first image pair.

Adding the rest of the diffs to the mask.
Masking 29

Done.

A number of .diff files are generated in this process. These files repesent the movement between individual sequence pairs.

The .diff files are simply intermediary files, the important bit is the mask file, which is generated as the sum of all differences.

The mask file may be dirty (as in this case) and require manual cleanup. The basic shape of the road however is clearly visible, evidence that we can with minimal effort automate the mask generation process. Also, this run was conducted at night, day-time images yield better results.

There are a few final steps we need to take before we can use the example PyTrAn driver script. First we need to convert the mask to ASCII (noraw) format:

$ pnmnoraw mask > mask_200003.ascii

Then we need to open an ImageMagick display window and get its X-window-ID using xwininfo. Finally, update camera_id and window_id in pytran_sampling.py and launch the driver:

$ ../pytran_sampling.py
DEBUG> grabbing frame from camera 200003
DEBUG> rotating image: pytran.this > pytran.last
DEBUG> refreshing image in 3 secs
taking a 5 minute sample at various thresholds.
DEBUG> grabbing frame from camera 200003
DEBUG> generating frame diff on pytran.last, pytran.this
DEBUG> displaying image: pytran.diff
DEBUG> converting pytran.diff to ascii
DEBUG> calculating traffic ratio...
ratio[5]: 55%
DEBUG> calculating traffic ratio...
ratio[10]: 52%
...
...
5 minute sample[5]: 67.88
5 minute sample[10]: 42.66
5 minute sample[15]: 30.57
5 minute sample[20]: 23.03
5 minute sample[25]: 18.39
5 minute sample[30]: 14.79
5 minute sample[35]: 12.42
5 minute sample[40]: 10.53
5 minute sample[45]: 9.06
5 minute sample[50]: 7.85

The sampling script will take 5 minute samples at varying color thresholds. The optimal threshold must be manually chosen. Furthermore, you will need to sample the traffic ratios during both heavy and light traffic times to get a good feel for your acceptable range. Also, keep in mind that the traffic ratio value is simply the percent change detected, or in other words the movement detected within the masked region. This means that a completely empty road will register similar values to a road so congested it looks like a parking lot. The time of day can be combined with the traffic ration to determine the logical truth.

With this task implemented and abstracted more complex systems can be built. When I find the time Id like to create a system that will take multiple potential travel routes and times, and during the travel time e-mail the traveler with the best route to take. Another idea I had would be to record the traffic flow values for each camera, for each day and for each half hour interval. Travelers and other interested parties can then analyze traffic patterns to determine the fastest route dependant on date/time.