CN114637664A - Detection method and device for android application program properties - Google Patents
Detection method and device for android application program properties Download PDFInfo
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Abstract
The invention discloses a method and a device for detecting properties of android application programs, which comprises the steps of constructing a state diagram based on Activity information and jump information among activities for each application program in different android equipment, and combining the state diagrams as intelligent agents to obtain a probabilistic multi-intelligent-agent system; depicting the target property as a probability cognition logic formula; and inputting the probability multi-agent system and the probability cognitive logic formula into a model detection tool to obtain a detection result of the target property. The method can prove that the property is satisfied or give an unsatisfied counterexample, can model a system under the condition that the same android application runs on different devices, and verifies the property related to interaction between the android applications running on different devices; the property of a system formed by android application programs running on a plurality of devices can be analyzed, and the method has positive significance for debugging the programs by developers, improving the usability of the programs and reducing program bugs.
Description
Technical Field
The invention belongs to the field of program analysis and safety, and particularly relates to a method and a device for detecting the property of an android application program.
Background
With the rapid development of smart phones, the android system is more and more widely used in daily life. However, as an open system, many developers develop applications that bring convenience and are accompanied by many abnormal behaviors such as bugs and hidden dangers. These abnormal behaviors may affect the use experience of the application program and may even cause privacy disclosure or property loss of the user. Therefore, how to ensure the correctness of the android application, i.e. eliminate the abnormal behavior, becomes an important research problem.
Most of the prior art is based on software test, and checks whether the behavior of the application program meets the requirements by executing a formulated test case. However, the software test is limited by the path coverage rate, and only can try to find the existing abnormal behavior, and the absence of the abnormal behavior cannot be proved. Model detection can solve this problem by traversing the reachable state space to prove that abnormal behavior is not present (or to find out what abnormal behavior is present).
At the present stage, the research on applying the model detection technology to the android application program is less, and how to establish the model of the android application program, how to depict the property to be verified and how to apply the model detection algorithm are not given.
Disclosure of Invention
The invention provides a method and a device for detecting properties of an android application program, which are characterized in that text information in Activities and jump information among Activities are extracted from an android application program installation package by using a static analysis method, then a model of a single application program is constructed, a plurality of models are combined together to construct a probabilistic multi-agent system, and finally a probabilistic cognitive logic model detection method is used to verify whether the android application program meets the required properties.
The technical content of the invention comprises:
a detection method for android application program properties comprises the following steps:
1) aiming at each application program in different android devices, constructing a state diagram based on Activity information and jump information between activities, and combining the state diagrams as intelligent agents to obtain a probabilistic multi-intelligent-agent system;
2) the target property is characterized as a probability cognition logic formula;
3) and inputting the probability multi-agent system and the probability cognitive logic formula into a model detection tool to obtain a detection result of the target property.
Further, the method for extracting Activity information and jump information between activities includes: and extracting from the application program installation package by using a static analysis tool.
Further, the static resolution tool comprises: gator or BACKSTAGE.
Further, the state diagram is constructed by:
1) taking the Activity information as a state and a vertex of a state diagram, wherein the first Activity information entered after the application program is opened is taken as an initial state;
2) constructing the edge of the state diagram by using the jumping information between Activities;
3) on the corresponding edge, marking an event triggering page migration as an action;
4) and setting corresponding atom propositions and state label functions.
Further, the elements of the state diagram further include: the probability of migration.
Further, the probabilistic cognitive logic formula comprises: a state formula and a path formula.
Further, the state formula
Wherein
Is a state formula, p is an atom proposition,
taking a non-operational character, taking a conjunction operational character,
in the form of a probability operator, the probability operator,
representing four relations of greater than, greater than or equal to, less than or equal to, and less than or equal to, d represents in [0,1 ]]A real number in between (c) and (d),
is a knowledge-aware operator, i is an agent,
for each person knowledge cognitive operator, G is a multi-agent set,
for the distributed knowledge-aware operator, ψ is the path formula.
Further, the path is formulated as
Where X is the next operator, U is the up to operator,
is a state formula.
A storage medium having stored therein a computer program, wherein the computer program is arranged to perform the above-mentioned method when executed.
An electronic device comprising a memory having a computer program stored therein and a processor arranged to run the computer to perform the method as described above.
Compared with the prior art, the invention has the following advantages:
1) using model detection techniques, it can be demonstrated that properties are satisfied or give an unsatisfied counter-example.
2) The method can model a system under the condition that the same android application runs on different devices, and verify the properties related to interaction between the android applications running on different devices;
3) the property of a system formed by android application programs running on a plurality of devices can be analyzed, and the method has positive significance for debugging the programs by developers, improving the usability of the programs and reducing program bugs.
Drawings
FIG. 1 is a system architecture diagram of the present invention.
Fig. 2 is a flow chart of the present invention.
FIG. 3 is a single application model of an embodiment of the present invention.
Detailed Description
The invention will be further described by way of example with reference to the accompanying drawings.
According to the detection method, a model is built from the android application installation package file, the property to be verified and an application model detection algorithm are described by using a logic formula, and a path which does not meet the property in the android application can be found out or a conclusion that the property is met can be given by applying the set of method.
1. System components
The system architecture of the invention is shown in figure 1 and mainly comprises 4 modules, namely an android application program analysis tool module, a model construction module, a property input module and a model detection module.
2. Workflow process
The working flow of the invention is shown in figure 2:
(1) first, data including jump information between Activity information and Activity is extracted from the android application installation package through a static parsing tool, such as gate (http:// web. cs. o. hio-state. edu/presto/software/gate /), BACKSTAGE (https:// www.st.cs.uni-sarland. de/uploading/BACKSTAGE /), and the like.
(2) These data are then used to build a state diagram for the individual application. The state diagram for a single application includes the following elements: a limited set of states, an initial state, a limited set of actions, a state migration function, a limited set of atomic propositions, and a state tagging function. The specific construction method comprises the following steps: taking Activity as a state; taking the first Activity entered after the application program is opened as an initial state; taking an event (such as clicking a button and the like) which can trigger page migration on a page as an action; taking the jump between activities as migration, wherein the migration related to network connection needs to introduce probability factors because network transmission has certain failure probability (for example, when a user clicks a login button on a login page, an application enters the next page with the probability of 0.99, and stays on the login page with the probability of 0.01); the atomic proposition and state label function can give different definitions according to different application scenarios.
Figure 3 gives an example of a simple single application model.
(3) Then, each single application program is regarded as an agent, and a plurality of application program clients running on different devices are combined into a probabilistic multi-agent system, namely, the global state is the combination of each local state, the global action is the combination of the local actions, and the global migration is the combination of the local migration. Each agent can only get local information, i.e. only knows in which state it is, and not in which state the other agents are.
(4) The properties in the present invention are characterized using probabilistic cognitive logic. The logic integrates probabilistic computational tree logic and cognitive logic. The logic includes a state formula and a path formula, wherein the state formula
Wherein, the meaning of each element of the state formula is as follows:
(ii) atomic propositions p, e.g. "variable s has a value of 3";
② taking non-operational characters
Order to
Represents a formula of states, then
To represent
The method is not established;
③ to get an operator ^ to make
And
respectively represent two state formulas, then
To represent
And
simultaneously, the two steps are carried out;
probability operator
Wherein
Representing four relations of greater than, greater than or equal to, less than or equal to, and less than or equal to, d represents in [0,1 ]]Real number in between. Let psi denote a path formula, then
Indicates that the probability of psi being satisfied
The relationship (c) in (c).
Fifth cognitive operator, including Knowledge (Knowledge)
Knowledge of each person (Everyone's Knowledge)
Distributed Knowledge (Distributed Knowledge)
Where i represents an agent (which in the present invention may be a user, or a client), and G is a multi-agent set. Order to
Represents a formula of states, then
Indicating a state equivalent to the current state from the user i's perspective,
are all true, i.e. user i knows
This is true. Accordingly, the number of the first and second electrodes,
all users in the representation G know
It is true that the first and second sensors,
the user in the representation G can know if the user can share the information
This is true.
The path is formulated as
Wherein, the meaning of each element of the state formula is as follows:
next (Next) operator X, order
Represents a formula of states, then
It is shown that after the next step,
if true;
② Up to (Until) operator U, order
And
respectively represent two state formulas, then
To represent
Will be established after a future step, before
This is always true.
By combining the above operators, we can express many properties, such as "user _ count>＝2∧KBobsAlice"the number of users is greater than 2 and the user Bob knows that Alice has logged in" in the entire system.
(5) And finally, inputting the probabilistic multi-agent system obtained in the step (3) and the property formula obtained in the step (4) into a probabilistic cognitive logic model detection tool (https:// github. com/fuchen1991/epmc-petl) for model detection so as to verify whether the property is met.
The above embodiments are only intended to illustrate the technical solution of the present invention and not to limit the same, and a person skilled in the art can modify the technical solution of the present invention or substitute the same without departing from the spirit and scope of the present invention, and the scope of the present invention should be determined by the claims.
Claims (10)
1. A detection method for android application program properties comprises the following steps:
1) aiming at each application program in different android devices, constructing a state diagram based on Activity information and jump information between activities, and combining the state diagrams as intelligent agents to obtain a probabilistic multi-intelligent-agent system;
2) depicting the target property as a probability cognition logic formula;
3) and inputting the probability multi-agent system and the probability cognitive logic formula into a model detection tool to obtain a detection result of the target property.
2. The method of claim 1, wherein extracting Activity information and jump between activities information comprises: extracted from the application installation package using a static parsing tool.
3. The method of claim 2, wherein the static resolution tool comprises: gator or BACKSTAGE.
4. The method of claim 1, wherein the state diagram is constructed by:
1) taking the Activity information as a state and a vertex of a state diagram, wherein the first Activity information entered after the application program is opened is taken as an initial state;
2) constructing the edge of the state diagram by using the jumping information between Activities;
3) on the corresponding edge, marking an event triggering page migration as an action;
4) and setting corresponding atom propositions and state label functions.
5. The method of claim 4, wherein the elements of the state diagram further comprise: the probability of migration.
6. The method of claim 1, wherein the probabilistic cognitive logic formula comprises: a state formula and a path formula.
7. The method of claim 6, wherein the state formula
Wherein p is an atomic proposition,
taking a non-operational character, taking a combined operational character,
in the form of a probability operator, the probability operator,
representing four relations of greater than, greater than or equal to, less than or equal to, and less than or equal to, d represents in [0,1 ]]The real number in between (a) and (b),
is a knowledge-aware operator, i is an agent,
for each person knowledge-aware operational characters, g is a multi-agent set,
for the distributed knowledge-aware operator, ψ is the path formula.
8. The method of claim 6, wherein the path formula
Where ψ is the path formula, X is the next operator, U is the up to operator,
is a state formula.
9. A storage medium having a computer program stored thereon, wherein the computer program is arranged to, when run, perform the method of any of claims 1-8.
10. An electronic device comprising a memory having a computer program stored therein and a processor arranged to run the computer program to perform the method according to any of claims 1-8.
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| CN115496017A (en) * | 2022-09-06 | 2022-12-20 | 中国科学院软件研究所 | Similar SVA (singular value analysis) extension and formal verification method for Chisel assertion language |
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