@InProceedings{boespflug20countermeasures,
  author       = {Boespflug, Etienne and Ene, Cristian and Mounier, Laurent and Potet, Marie-Laure},
  booktitle    = {2020 Workshop on Fault Detection and Tolerance in Cryptography (FDTC)},
  date         = {2020},
  title        = {Countermeasures Optimization in Multiple Fault-Injection Context},
  organization = {IEEE},
  pages        = {26--34},
  comment      = {* context: fault injection as a (security) attack vector
* understand *countermeasures check points* (CCPs) as important
  countermeasure

  * i.e., where program checks safety conditions at runtime

* focus on optimization

  * rather than on low overhead, as usual in literature

* formal descriptions

  * programs, execution, modification, injection and detection

* multi-fault injection

* can be extended, e.g., by duplicating CCPs

  * i.e., one for true, one for false branch
  * e.g.::

    condition = calculate_condition()
    if condition:
      if not condition:
        injection_detected()
      do_something()
    else
      if condition:
        injection_detected()

  * \# now, I think, if branches are attacked, there is a safety net

* code is being instrumented to contain CCPs
* algorithm to optimize (i.e., reduce) number of CCPs
* experiment

  * using Lazart

    * input: LLVM code, fault model, security property
    * dynamic symbolic execution

  * for single faults as example, 20% - 80% of CCPs can be
    removed (optimized)},
  file         = {:boespflug20countermeasures - Countermeasures Optimization in Multiple Fault-Injection Context.pdf:PDF},
  groups       = {fault tolerance},
  timestamp    = {2021-03-16},
}

{"_id":"QsXBgyjZtv2zu6Adp","bibbaseid":"boespflug-ene-mounier-potet-countermeasuresoptimizationinmultiplefaultinjectioncontext","author_short":["Boespflug, E.","Ene, C.","Mounier, L.","Potet, M."],"bibdata":{"bibtype":"inproceedings","type":"inproceedings","author":[{"propositions":[],"lastnames":["Boespflug"],"firstnames":["Etienne"],"suffixes":[]},{"propositions":[],"lastnames":["Ene"],"firstnames":["Cristian"],"suffixes":[]},{"propositions":[],"lastnames":["Mounier"],"firstnames":["Laurent"],"suffixes":[]},{"propositions":[],"lastnames":["Potet"],"firstnames":["Marie-Laure"],"suffixes":[]}],"booktitle":"2020 Workshop on Fault Detection and Tolerance in Cryptography (FDTC)","date":"2020","title":"Countermeasures Optimization in Multiple Fault-Injection Context","organization":"IEEE","pages":"26–34","comment":"* context: fault injection as a (security) attack vector * understand *countermeasures check points* (CCPs) as important countermeasure * i.e., where program checks safety conditions at runtime * focus on optimization * rather than on low overhead, as usual in literature * formal descriptions * programs, execution, modification, injection and detection * multi-fault injection * can be extended, e.g., by duplicating CCPs * i.e., one for true, one for false branch * e.g.:: condition = calculate_condition() if condition: if not condition: injection_detected() do_something() else if condition: injection_detected() * # now, I think, if branches are attacked, there is a safety net * code is being instrumented to contain CCPs * algorithm to optimize (i.e., reduce) number of CCPs * experiment * using Lazart * input: LLVM code, fault model, security property * dynamic symbolic execution * for single faults as example, 20% - 80% of CCPs can be removed (optimized)","file":":boespflug20countermeasures - Countermeasures Optimization in Multiple Fault-Injection Context.pdf:PDF","groups":"fault tolerance","timestamp":"2021-03-16","bibtex":"@InProceedings{boespflug20countermeasures,\n author = {Boespflug, Etienne and Ene, Cristian and Mounier, Laurent and Potet, Marie-Laure},\n booktitle = {2020 Workshop on Fault Detection and Tolerance in Cryptography (FDTC)},\n date = {2020},\n title = {Countermeasures Optimization in Multiple Fault-Injection Context},\n organization = {IEEE},\n pages = {26--34},\n comment = {* context: fault injection as a (security) attack vector\n* understand *countermeasures check points* (CCPs) as important\n countermeasure\n\n * i.e., where program checks safety conditions at runtime\n\n* focus on optimization\n\n * rather than on low overhead, as usual in literature\n\n* formal descriptions\n\n * programs, execution, modification, injection and detection\n\n* multi-fault injection\n\n* can be extended, e.g., by duplicating CCPs\n\n * i.e., one for true, one for false branch\n * e.g.::\n\n condition = calculate_condition()\n if condition:\n if not condition:\n injection_detected()\n do_something()\n else\n if condition:\n injection_detected()\n\n * \\# now, I think, if branches are attacked, there is a safety net\n\n* code is being instrumented to contain CCPs\n* algorithm to optimize (i.e., reduce) number of CCPs\n* experiment\n\n * using Lazart\n\n * input: LLVM code, fault model, security property\n * dynamic symbolic execution\n\n * for single faults as example, 20% - 80% of CCPs can be\n removed (optimized)},\n file = {:boespflug20countermeasures - Countermeasures Optimization in Multiple Fault-Injection Context.pdf:PDF},\n groups = {fault tolerance},\n timestamp = {2021-03-16},\n}\n\n","author_short":["Boespflug, E.","Ene, C.","Mounier, L.","Potet, M."],"key":"boespflug20countermeasures","id":"boespflug20countermeasures","bibbaseid":"boespflug-ene-mounier-potet-countermeasuresoptimizationinmultiplefaultinjectioncontext","role":"author","urls":{},"metadata":{"authorlinks":{}},"downloads":0,"html":""},"bibtype":"inproceedings","biburl":"https://bibbase.org/network/files/AsPiHTmHHGjgy6xSQ","dataSources":["wjZw5s4JL49uLwn3p"],"keywords":[],"search_terms":["countermeasures","optimization","multiple","fault","injection","context","boespflug","ene","mounier","potet"],"title":"Countermeasures Optimization in Multiple Fault-Injection Context","year":null}