Verification of Branch-Time Property Based on Dynamic Description Logic

Description logics provide powerful languages for representing and reasoning about knowledge of static application domains. The main strength of description logics is that they offer considerable expressive power going far beyond propositional logic, while reasoning is still decidable. There is a demand to bring the power and character of description logics into the description and reasoning of dynamic application domains which are characterized by actions. In this paper, based on a combination of the propositional dynamic logic PDL, a family of description logics and an action formalism constructed over description logics, we propose a family of dynamic description logics DDL(X @) for representing and reasoning about actions, where X represents well-studied description logics ranging from the to the , and X @ denotes the extension of X with the @ constructor. The representation power of DDL(X @) is reflected in four aspects. Firstly, the static knowledge of application domains is represented as RBoxes and acyclic TBoxes of the description logic X. Secondly, the states of the world and the pre-conditions of atomic actions are described by ABox assertions of the description logic X @, and the post-conditions of atomic actions are described by primitive literals of X @. Thirdly, starting with atomic actions and ABox assertions of X @, complex actions are constructed with regular program constructors of PDL, so that various control structures on actions such as the "Sequence", "Choice", "Any-Order", "Iterate", "If-Then-Else", "Repeat-While" and "Repeat-Until" can be represented. Finally, both atomic actions and complex actions are used as modal operators for the construction of formulas, so that many properties on actions can be explicitly stated by formulas. A tableau-algorithm is provided for deciding the satisfiability of DDL(X @)-formulas; based on this algorithm, reasoning tasks such as the realizability, executability and projection of actions can be effectively carried out. As a result, DDL(X @) not only offers considerable expressive power going beyond many action formalisms which are propositional, but also provides decidable reasoning services for actions described by it.

As a family of dynamic description logics, DDL(X) is constructed by embracing actions into the description logic X, where X represents well-studied description logics ranging from the ALC to the SHOIQ. The usage of distributed computation techniques in reasoning is an important premise for the adoption of Dynamic Description Logics in a real-world setting. Practical scalability of DDL(X) reasoning inspired recently a proposal of Distributed Dynamic Description Logics (D3L) framework. D3L is a natural generalization of the DDL(X) framework, which is designed to model the distributed dynamically-changing knowledge repositories interconnected by semantic mappings and to accomplish reasoning in distributed, heterogeneous environments. In this paper, we investigate the reasoning mechanisms in D3L and propose a tableau-based reasoning algorithm for D3L, built as a composition of the state of the art tableaux reasoners for DDL(X).

All currently available Network-based Intrusion Detection Systems (NIDS) rely upon passive protocol analysis which is fundamentally flawed as an attack can evade detection by exploiting ambiguities in the traffic stream as seen by the NIDS. We observe that different attack variations can be derived from the original attack using simple transformations. This paper proposes a semantic model for attack mutation based on dynamic description logics (DDL(X)), extensions of description logics (DLs) with a dynamic dimension, and explores the possibility of using DDL(X) as a basis for evasion composition. The attack mutation model describes all the possible transformations and how they can be applied to the original attack to generate a large number of attack variations. Furthermore, this paper presents a heuristics planning algorithm for the automation of evasion composition at the functional level based on DDL(X). Our approach employs classical DL-TBoxes to capture the constraints of the domain, DL-ABoxes to present the attack, and DL-formulas to encode the objective sequence of packets respectively. In such a way, the evasion composition problem is solved by a decidable tableau procedure. The preliminary results certify the potential of the approach.KeywordsIntrusion Detection/Prevention SystemsMulti-protocol EvasionsAdvanced Evasion TechniquesKnowledge Representation and ReasoningDynamic Description Logics

A service composition task for service broker is to discovery and compose provider’s services to satisfy user’s request. Many researchers model the context utilizing ontology-based or attribute-based method to assist service composition. We propose a new context model by combining the context logic with the dynamic description logic (DDL), where user’ context, provider’s context and broker’s context are described by DDL separately and reasoned under the context logic. The reasoning results finally can be used to discovery and compose services intelligently. We evaluate this model on a simple, yet realistic example, and the results show that our context model provides a practical solution.

As a new software paradigm, cloud computing provides services dynamically according to user requirements. However, it tends to disclose personal information due to collaborative computing and transparent interactions among software as a service (SaaS) services. We propose a private data disclosure checking method that can be applied to the collaboration interaction process. First, we describe the privacy requirement with ontology and description logic. Second, with dynamic description logic, we validate whether SaaS services are authorized to obtain a user’s privacy attributes, to prevent unauthorized services from obtaining their private data. Third, we monitor authorized SaaS services to guarantee privacy requirements. Therefore, we can prevent users’ private data from being used and propagated illegally. Finally, we propose privacy disclosure checking algorithms, and demonstrate their correctness and feasibility by experiments.

Specifying and verifying interaction protocols in a temporal action logic

Model checking as an approach to the automatic verification of finite state systems has focussed predominantly on system specifications expressed in temporal logic. In the distributed systems community, logics of knowledge (epistemic logics) have been advocated for expressing desirable properties of protocols and systems. A range of logics combining temporal and epistemic components have been developed for this purpose. However, the model checking problem for temporal logics of knowledge has received (comparatively) little attention. In this paper, we address ourselves to this problem. Following a brief survey of the relevant issues and literature, we introduce a temporal logic of knowledge (Halpern and Vardi’s logic CKL n). We then develop an approach to CKL n model checking that combines ideas from the interpreted systems semantics for knowledge with the logic of local propositions developed by Engelhardt et al. With our approach, local propositions provide a means to reduce CKL n model checking to linear temporal logic model checking. After introducing and exploring the ideas underpinning our approach, we present a case study (the bit transmission problem) in which spin was used to establish temporal epistemic properties of a system implemented in PROMELA.

Current approaches to analyzing dynamic systems are mostly grounded in propositional (temporal) logics. As a consequence, they often lack expressivity for modelling rich data structures and reasoning about them in the course of a computation. To address this problem, we propose a rich modelling framework based on first-order logic over background theories (arithmetics, lists, records, etc) and state transition systems over corresponding interpretations. On the reasoning side, we introduce a tableau calculus for bounded model checking of properties expressed in a certain fragment of CTL* over that first-order logic. We also describe a k-induction scheme on top of that calculus for proving safety properties, and we report on first experiments with a prototypical implementation.

Formal properties represent a cornerstone of the system-correctness proofs based on formal verification techniques such as model checking. Formalizing requirements into temporal properties may be very complex and error prone, due not only to the ambiguity of the textual requirements but also to the complexity of the formal language. Finding a property specification language that balances simplicity, expressiveness, and tool support remains an open problem in many real-world contexts. In this paper, we propose a new temporal logic, which extends First-Order Linear-time Temporal Logic with Past adding two operators "at next" and "at last", which take in input a term and a formula and represent the value of the term at the next state in the future or last state in the past in which the formula holds. We consider different models of time (including discrete, dense, and super-dense time) and Satisfiability Modulo Theories (SMT) of the first-order formulas. The "at next" and "at last" functions can be seen as a generalization of Event-Clock operators and can encode some Metric Temporal operators also with counting. They are useful to formalize properties of component-based models because they allow to express constraints on the data exchanged with messages at different instants of time. We provide a simple encoding into equisatisfiable formulas without the extra functional symbols. We implement a prototype tool support based on SMT-based model checking.

Dynamic linear time temporal logic

UML state chart is lack of dynamic and temporal semantics defined strictly, so it is difficult to implement formal analysis and verification on the systems described by it. Description Logics (DLs), a formal language of knowledge representations, has very strong ability of representation and deduction, but the traditional DLs can only represent the knowledge about static application domains. Temporal logics (TLs) makes representation and reasoning about dynamic models more concise than using formalism such as pure DLs. TDLs (temporal description logics), the combination of DLs and TLs, can express both the dynamic and temporal semantics. So, we combine the advantages of DLs and TLs, a novel formalization of UML state chart with TDLs is proposed in this paper. Example indicates that the method is feasible, the semantic accuracy and expression ability of UML state chart are improved.

Ad Hoc workflow is a workflow system which does not need to define the predefined workflow business process and organize migrating workflow union. In this case a single work place is unable to get the full system information, and the ability of the single work place in the system for goal decomposition and service understanding is limited. Some goals which can be completed by Ad Hoc Workflow System may be unknown for a certain work place. This paper focusing on the problem of Ad Hoc workflows goal planning for the unknown goal, presents a planning method of the unknown goal in Mobile Agent migration process. The method describes goals with Dynamic Description Logic, packages the unknown goal, and achieves dynamic goal planning. Goal Description, Goal Inference and methods and algorithms of dynamic goal planning are mentioned in this paper.

Modalities for model checking: branching time logic strikes back

: The question of whether branching-time temporal logic or linear-time temporal logic is best for reasoning about concurrent programs is one of the most controversial issues in logics of programs. Concurrent programs are usually modelled by labelled state-transition graphs in which some state is designated as the initial state. For historical reasons such graphs are called Kripke structures. In linear temporal logic operators are provided for describing events along a single time path (i.e., along a single path in a Kripke structure). In a branching-time logic the temporal operators quantify over the futures that are possible from a given state (i.e., over the possible paths that lead from a state). It is well known that the two types of temporal logic have different expressive powers. Linear temporal logic, for example, can express certain fairness properties that cannot be expressed in branching-time temporal logic. On the other hand, certain practical decision problems like model checking are easier for branching-time temporal logic than for linear temporal logic. This paper provides further insight on which type of logic is best. It is shown that if two finite Kripke structures can be distinguished by some formula that contains both branching-time and linear-time operators, then the structures can be distinguished by a formula that contains only branching time operators. Specifically, we show that if two finite Kripke structures can be distinguished by some formula of the logic CTL (i.e., if there is some CTL formula that is true in one but not in the other), then they can be distinguished by some formula of the logic CTL.

Based on the Kripke structure, linear temporal logic and generalized possibility measure, this article studies the model checking problems of generalized possibilistic fuzzy linear temporal logic (GPoFTL). The generalized possibilistic Kripke structure is introduced to describe the system model. The syntax of GPoFTL, which includes fuzzy temporal operators such as ``soon'', ``presently'', ``gradually'', ``within'', ``last'', ``nearly always'', ``almost alwayss'', ``in the long distant future'', ``in the middle of'', ``nearly until'' and ``almost until'', and its language semantics and path semantics under generalized possibility measure are given. Next, we explain the semantics of fuzzy temporal operators through some examples and prove that GPoFTL is an extension of generalized possibilistic linear temporal logic in fuzzy time temporal logic. Furthermore, the GPoFTL model checking algorithm is given by explicit calculation formulas one by one for any GPoFTL formula involving fuzzy temporal operators using fuzzy matrix operations. Last, the algorithm of necessary threshold model checking of GPoFTL is studied using automata theory and its time complexity is discussed.