in the end I ingored a lot of feedbacks, sory jfl
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@ -13,8 +13,9 @@ After that, we will also look at contributions that sought to encode results ins
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Some situations, like reflection of dynamic code loading, are difficult to solve with static analysis and require a different approach: dynamic analysis.
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With dynamic analysis, the application is actually executed, and the reverse engineer observes its behaviour.
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Monitoring the behaviour can be achieved by various strategies: observing the filesystem, the display screen, the process memory, the kernel, ...
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Depending on the chosen level of observation, it can be technically difficult.
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Monitoring the behaviour can be achieved by various strategies: observing the filesystem, the display screen, the process memory, the kernel, etc.
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Depending on the chosen level of observation, dynamic analysis can become a serious technical challenge.
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A basic example of dynamic analysis is presented by Bernardi #etal~@bernardi_dynamic_2019: the logs generated by `strace` are used to list the system calls generated in response to an event to determine if an application is malicious or not.
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More advanced methods are more intrusive and require modifying either the #APK, the Android framework, runtime, or kernel.
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@ -49,7 +50,7 @@ For instance, StaDynA only provide the call graph, and cannot be used as is to i
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This is unfortunate: the reverse engineer's next step will depend on the context.
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Not being able to reuse the result of a previous analysis with any ad hoc tools greatly limits their options.
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AppSpear has an interesting solution to this issue: the code it intercepts is repackaged inside a new #APK file that Android analysis tools should be able to analyse.
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We will now explore further the contributions that take this approach of using actual applications to encode their results.
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We will now explore further the contributions that take this approach to encode results inside applications.
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//#todo[RealDroid sandbox bases on modified ART?]
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//#todo[force execution?]
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