In this solution, we are interacting with a computer program that assists in the decryption by computing the index of coincidence at various offsets, and the SAD correlation with the normal English distribution of distributions corresponding to different shifts of subset for each key position. Text supplied was ERXHD BADSP OZTQZ MAKZN MCWGW AMPHG XNBDR IWZIO BBVBM PKTXW ACFKZ FVITE IWSTO FTCGB UKQEX PMKGY EAOOI COQGO MFPCB AIIMP HQAFB ORTBQ BAQMI GEUGU HNTVG ZPNMG WWMGW WGQGC GBRTB NGXBA IOWWU STMMA BXKNK LQXAJ YVOOI CHVFS WFMFQ DMGCV CEPNB ASEBU TNQGB ZRVWZ IOBBV BMPHG XNBDR IGKHN XUFCQ YEVME WIKVC UCXBD VJCNE OAXZN XTOHT FPQGN BUXGI GLPRF SDHNT VQZPR BLVXM YWVVQ NQBTY GKGBP MEGHS PWFDL MPRVP LLCKT TZRXW DDHFM AZARX EWNBV RFIFX FBHRJ QFMLQ UCOIF WZUIK UNZQB GUVWK JQRIF PNBWA GTEXM WNZXI UQABJ NBRVZ BFCAB VBEEH UDHLQ AZPRY UKXWA GQABA YQQAI WZIFM MMJVE CZILT LVIBB KSQGX PXUOZ SYFXY UGFHJ PBAOM EOFTX ZZNVP VVUTT VYRCH GGUET NTOHT AMBVO ITTMR YLQAZ PRVIV MMSXQ TAJLP WEQBU XNMKU DRVIU ICOMN VXYBY AUWOL VCGHY KQAZC VMCWG ZZKCF PXHZA LYBRF VMAIQ MQFMC XMWGC WSHLU LWAWA GFTGB VGAQG BIVBV AITSZ RYIZR JQPMC WGWAY USDXH MMAZI AWMME MXXKC ZDZIZ BSQFB HOTKO MQBEI ILIGO ASRNP TBDRV SZINA MFKUR THQGO NETSY JNNIY RGFNJ XHZOM XSUCN AMFKV FXNPT BOLGA ASYEQ AMIAW MCIXJ VVCRJ MXZVT BRGNE BTGQC YQHSL BRSAQ KUUTB DGCZX NYTAV KZGHO AXIGP QKUCA MPRSB BBHBX ZVGVK UIBAC ZGVOX CVZAD RCKMN NAIGS WEXMI MQNJA WZVFR ZRYMZ UFMLB CIYOK HCGEU OKUAO UTVWI KBSHC GBRXI PMQQM PJRGO ZDNAM E Input maximum shift 60 *** Program prints out all shifts for which the IOC is >= 5%. Offset 10 ioc 0.053070 Offset 18 ioc 0.065058 Offset 36 ioc 0.072727 Offset 50 ioc 0.052117 Offset 54 ioc 0.083969 *** 18 looks like a good guess for the key length based on its *** recurrance at different multiples. Input guess for key length based on above 18 Best 2 matching shifts and SAD distances for character sets. Set 0: best shift 8, val 0.54; next best 23, val 0.83 Set 1: best shift 13, val 0.42; next best 1, val 0.86 Set 2: best shift 19, val 0.40; next best 8, val 0.85 Set 3: best shift 20, val 0.57; next best 24, val 0.78 Set 4: best shift 8, val 0.52; next best 12, val 0.83 Set 5: best shift 19, val 0.53; next best 8, val 0.93 Set 6: best shift 8, val 0.47; next best 19, val 0.91 Set 7: best shift 21, val 0.67; next best 22, val 0.75 Set 8: best shift 4, val 0.51; next best 8, val 0.91 Set 9: best shift 2, val 0.61; next best 12, val 0.83 Set 10: best shift 14, val 0.54; next best 18, val 0.91 Set 11: best shift 12, val 0.56; next best 25, val 0.88 Set 12: best shift 15, val 0.49; next best 0, val 0.91 Set 13: best shift 20, val 0.49; next best 5, val 0.82 Set 14: best shift 19, val 0.60; next best 23, val 0.76 Set 15: best shift 8, val 0.40; next best 12, val 0.77 Set 16: best shift 13, val 0.57; next best 17, val 1.03 Set 17: best shift 6, val 0.54; next best 21, val 0.67 Trial key is 012345678901234567 intuitivecomputing *** This looks promising, as the key obtained by taking the best SAD match for *** each subset is an English phrase. Decrypting with trial key yields 012345678901234567 weenvisionanewgene rationofintuitivec omputinginwhichuse rscollaborateinthe ireverydayactiviti eswithanintelligen tdigitalassistantt hatmodelsuserinten tandthatsuggestsor carriesoutactionsm ostlikelytosatisfy thatintentintuitiv ecomputingsystemsw illbelongtoindivid ualuserstravelwith themandunderstandt heirneedstheywilla ctivelymonitorthep hysicalenvironment seekoutandutilized istributedinformat ionandcomputationa lresourcescomputep romisingactionsint hefaceofcomplexinc ompleteorcontradic toryinputsandemplo ysophisticatedgrap hicalandnaturallan guageinterfacesint hecontextofourwork thetermintuitiveap pliesbothtouserint uitionregardingsys tembehaviorandtotw oformsofsystemintu itioninferencepred ictionofuserintent andselectionofprom isingactionstosati sfythatintentthese meaningsaremutuall ysupportiveinthese nsethatthemodeling andsupportofuserin tentwillmakesystem sdramaticallyeasie rtouseallowingthem tointeractwithhuma nbeingsinawaythatm oresatisfyinglyres emblesthewaysinwhi chhumanbeingsinter actwithoneanother *** Seems to be right. *** Solved with almost no effort on our part. *** All the automatic guesses were correct. Finished? (y/n y final decrypted text is weenvisionanewgenerationofintuitivecomputinginwhichuserscollaborateinthe ireverydayactivitieswithanintelligentdigitalassistantthatmodelsuserinten tandthatsuggestsorcarriesoutactionsmostlikelytosatisfythatintentintuitiv ecomputingsystemswillbelongtoindividualuserstravelwiththemandunderstandt heirneedstheywillactivelymonitorthephysicalenvironmentseekoutandutilized istributedinformationandcomputationalresourcescomputepromisingactionsint hefaceofcomplexincompleteorcontradictoryinputsandemploysophisticatedgrap hicalandnaturallanguageinterfacesinthecontextofourworkthetermintuitiveap pliesbothtouserintuitionregardingsystembehaviorandtotwoformsofsystemintu itioninferencepredictionofuserintentandselectionofpromisingactionstosati sfythatintentthesemeaningsaremutuallysupportiveinthesensethatthemodeling andsupportofuserintentwillmakesystemsdramaticallyeasiertouseallowingthem tointeractwithhumanbeingsinawaythatmoresatisfyinglyresemblesthewaysinwhi chhumanbeingsinteractwithoneanother *** And with added puctuation and capitalization - the most *** labor intensive part of the whole process... We envision a new generation of intuitive computing, in which users collaborate in their everyday activities with an intelligent digital assistant that models user intent, and that suggests or carries out actions most likely to satisfy that intent. Intuitive computing systems will belong to individual users, travel with them, and understand their needs. They will actively monitor the physical environment, seek out and utilize distributed information and computational resources, compute promising actions in the face of complex, incomplete, or contradictory inputs, and employ sophisticated graphical and natural language interfaces. In the context of our work the term "intuitive" applies both to user intuition regarding system behavior and to two forms of system intuition: inference prediction of user intent, and selection of promising actions to satisfy that intent. These meanings are mutually supportive, in the sense that the modeling and support of user intent will make systems dramatically easier to use, allowing them to interact with human beings in a way that more satisfyingly resembles the ways in which human beings interact with one another.