Is it feasible to create a hybrid solver using bsgs and kangaroo for ECDLP? Do you think it could actually work? Would it be quicker than using just kangaroo or bsgs on their own?
I think it is possible on this way
For example you define jumps like you have a starting points
you make a rule of jumps where you take |last 6 digits of X +1G|
after 5.000.000 of those iterations, I guarantee that all nearby points will go to the same point...
I already did that I mean proved that to myself ( )
But what you can do for example...
In case of puzzle 135
You can start jumping from
|last 6 digits of X +1G|
and put in "babystep" file every 1.000.000th iteration point and you put I do not know 200.000.000 points... and you calculate G added from starting point to 6th last point... This will be a BIG number and it will basically be you BIG GIANT JUMP
Then you start scan from
02145d2611c823a396ef6712ce0f712f09b9b4f3135e3e0aa3230fb9b6d08d1e16
With the same rule... after 6.000.000 iteration if you did not find point from the babystep file you can jump BIG GIANT JUMP
If you find the point then
private key = 7fffffffffffffffffffffffffffffffff + G added in line of babystep file - G added in scan at the moment of collision
So this should be a hybrid kangaroo and bsgs
I do not know I am just a guy that is trying something