| H.R. Amirazizi and M.E. Hellman, "Time-Memory-Processor Tradeoffs", IEEE-IT, vol.34, no. 3 (1988), pp. 505-512. |
....it would suffice to enumerate all elements and then feed only those elements satisfying the desired criterion into the domain dependent application. Schroeder and Shamir formalize the term polynomially enumberable, and this has given rise to still another class of algorithms for exhaustive search [2, 14]. The result of this paper is particularly important for the case when the search space is not polynomially enumberable. We define a search space, S, as follows. We assume that S is represented by a connected undirected graph. We assume that the graph S is given to us in an implicit ....
H. Amirazizi and M. Hellman, "Time-Memory-Processor Trade-Offs", IEEE Transactions on Information Theory 34(3), 1988, pp. 505--512.
....one can replace sorting by hashing, speeding up the process. On the other hand, there is no easy way to reduce space requirements (other than by increasing the running time) which are of order m jhgij 1=2 . For other examples of computational tradeoffs in cryptographic searches, see [AmiraziziH]] There are two other general algorithms for the discrete log problem that run in time O(jhgij 1=2 ) and very little space. Both methods are randomized and are due to Pollard [Pollard1] We sketch a version of one of those methods here. Let x 0 = 1 and for i 0 let x i 1 = 8 : x i h; ....
H. R. Amirazizi and M. E. Hellman, Time-memory-processor trade-offs, IEEE Trans. Inform. Theory 34 (1988), 505--512.
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H.R. Amirazizi and M.E. Hellman, "Time-Memory-Processor Tradeoffs", IEEE-IT, vol.34, no. 3 (1988), pp. 505-512.
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H.R. Amirazizi and M.E. Hellman, "Time-Memory-Processor Trade-Offs", IEEE Transactions on Information Theory, vol. 34, no. 3, May 1988.
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H. R. Amirazizi and M. E. Hellman, Time-memory-processor trade-off, IEEE Trans. Infor. Theory 34, 1988, pp. 505-512. 15
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H. R. Amirazizi and M. E. Hellman, Time-memory-processor trade-off, IEEE Trans. Infor. Theory 34, 1988, pp. 505-512.
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