Craig Shue and his colleagues at Indiana University have tested and seriously propose the use of just such a device for detecting denial of service attacks.
This bucket of Jell-o is a prototype 3D analog computer and you might really consider using one to defend your network against cyber attacks. In the late 1980s and early 1990s I worked on the design of an analog and hybrid digital/analog neural computer based around the Intel ETANN 80170NX chip. And I’ve had an interest in analog computing and unconventional computers ever since.
Well, they didn’t exactly use a bucket of Jell-o, but rather a “computational foam”. Mills et al, describe the device in more detail:
Bench Test EAC using Conductive Sheet
The latest versions of the device have progressed to a USB connectable device with the obligatory cool blinky things on top.
But it is what’s inside that is perhaps a bit more interesting. The device consists of a conductive material and a digital interface that allows control of voltages applied to it and read out of the resulting voltages. Shown here is an implementation of Rubel’s extended analog computer or EAC designed by Bryce Himebaugh at Indiana University in 2005 connected to a digital computer host, either a PC or a Macintosh, which runs the EAC operating system (jEAC) designed by Ryan Varick also at Indiana University in 2006.
The EAC is a machine that can “see” and “learn”.
The result is an entirely novel approach to use of computation such that students using the EAC prototypes are expected to extract characters from the so called “butterfly alphabet” as their initial project with the device. Consider writing the Java code to do this as a sort of “Hello World” application your first day using the language.
The first application of the EAC was studying butterfly wing pattern morphogenesis, and it was ” designed by translating a visual model of the butterfly wing to the conductive sheet”.
What emerges out of this idea is a type of machine where the programmer disappears and a user presents a problem without explicitly knowing how to solve it in advance. The machine sees and learns. This paradigm can be applied to other types of unconventional computers such as physarum or slime mold computing.
And about that Jell-o, Mills et al report:
Mills, Jonathan W., et al. “Empty space computes: The evolution of an unconventional supercomputer.” Proceedings of the 3rd conference on Computing frontiers. ACM, 2006.
Shue, Craig, Brian Kopecky, and Chris Weilemann. Denial of Service Attack Detection using Extended Analog Computers. IUCS Technical Report TR624, 2006.
Mills, Jonathan W., et al. “Extended analog computers: A unifying paradigm for VLSI, plastic and colloidal computing systems.” Workshop on Unique Chips and Systems (UCAS-1). Held in conjunction with IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS05), Austin, Texas. 2005.
L. A. Rubel, The Extended Analog Computer, Advances in Applied Mathematics,
14 pp. 39-50, (1993).
Kirchhoff-Lukasiewicz Machines, http://www.cs.indiana.edu/~jwmills/ANALOG.NOTEBOOK/klm/klm.html
Bournez, Olivier, and Manuel L. Campagnolo. “A survey on continuous time computations.” New Computational Paradigms. Springer New York, 2008. 383-423.
B. Himebaugh, Design of EAC R002, www.cs.indiana.edu/~bhimebau (2005).
R. Varick, Building tools for the analog researcher: an interaction design challenge, Senior Research Project Report, Indiana University (2006).