Access control policies (ACPs) are essential for creating a secure access control system. ACPs are often studied and specified based on access control models, such as attribute-based access control (ABAC). Moreover, the execution of business process instances is typically recorded in a business process event log. Ensuring conformance with ABAC policies for the process log at the time of post-execution is crucial. To perform conformance testing of ABAC policies for event logs, it is necessary to formalize the ABAC policies. However, this formalization is typically carried out manually, leading to low efficiency and maintainability, as well as a high risk of errors and difficulty in detecting them. Also, the top-down approach for ABAC policy engineering is often less feasible due to the challenges and costs associated with manually developing ABAC policies, which makes it difficult to document security requirements. Besides, there is a lack of an ABAC metamodel that supports the formalization and conformance testing of ABAC policies, and little attention is paid to constructing ABAC policies from existing event logs. This paper presents a fine-grained and highly automated model-driven framework enabling the formalization and conformance testing of ABAC policies for business processes. In our approach, an ABAC metamodel and its patterns are proposed to solve the problems mentioned above. The approach is experimented with and evaluated on three business processes: One simulated and two real-world processes.

Event logs often record the execution of business process instances. Detecting traces in the event logs that do not comply with access control policies, such as role-based access control (RBAC) policies, is essential to ensuring system security. Moreover, process mining has been extensively utilized for security analysis in recent years. However, pattern-based approaches for designing and analyzing RBAC policies in the context of business processes through process mining are notably absent. In this paper, we present a systematic framework for checking the conformance of RBAC implemented in the event logs of business processes with the RBAC policies specified in domain knowledge. To facilitate the representation of the RBAC policies derived from the domain knowledge, we employ an RBAC domain-specific language (DSL) combined with our RBAC-driven object constraint language (OCL) invariant patterns built from the various types of RBAC constraints. The implemented RBAC in an event log is represented as snapshots within our framework. Then, we validate the snapshots with the RBAC policies to be able to detect RBAC conformance issues. The proposed framework is experimented with and evaluated on two business process logs, one simulated log and one real-world event log named “BPI Challenge 2017”.

Reflection is a technique that enables a system to inspect or change its structure and/or behavior at runtime. It is a key enabler of many techniques for developing systems that have to function despite rapidly changing requirements and environments. A crucial issue in developing reflective systems is to ensure the correctness of their behaviors, because object-level behaviors are affected by metalevel behaviors. In this paper, we present an extended labeled transition system (LTS), which we call a metalevel LTS (MLTS), that supports data representation of another LTS for use in modeling a reflective tower. We show that two of the existing state reduction techniques for an LTS (symmetry reductionanddivergence-sensitive stutter bisimulation) are also applicable to an MLTS. Then, we introduce two strategies for implementing an MLTS model in Promela, thereby enabling verification with the SPIN model checker. We also present case studies of applying MLTSs to two reflection applications: self-adaptation of a reconnaissance robot system, and dynamic evolution of an Internet-of-things (IoT) system. The case studies demonstrate the applicability of our approach and its scalability improvement through the state reduction techniques.

Anti-spam measures include methods for determining unsolicited email from the email content and methods for using sender information. If it can be determined from the sender's IP address of sender information and the sender's domain name whether the email should be received, it is possible to reduce the processing of the spam filter by the email content that has a high processing load for the determination. This study uses sender authentication technology to identify the sender of forwarded email. We consider that the sender of this forwarded email is the legitimate email sender to receive, and propose to use these as an allow list. In this paper, we propose a method to further improve the method we proposed and reduce misjudgment of the allow list. We verified that this new method is effective by using the log information of the emails actually received.

In recent years, just about all subjects require students to learn panoramic information. Because the need exists for cross-curriculum learning aimed at relating subject areas, it is useful for multiple-choice questions to include panoramic information for learners. A question including panoramic information refers to content that includes transverse related information and makes respondents grasp the whole knowledge. However, it is costly to manually generate and collect appropriate multiple-choice questions for questioners and learners. Therefore, in this research, we propose a method for the automatic generation of multiple-choice questions including panoramic information using Linked Data. Linked Data is graphical data that can link structured data, and it is used as a technology for data integration and utilization. Some attempts have been made to use Linked Data as a resource for creating teaching material, and the possibility of using Semantic Web technology in education has been verified. In this paper, we aim to realize a system for automatically generating two types of multiple-choice questions by implementing an approach to generating questions and choices. An evaluation method for the generation of questions and choices involves setting indicators for each evaluation item, such as validity and the degree of the inclusion of panoramic information.

Contemporary societies face many urban issues. To address these issues, governments, corporations and individuals should disclose and share their related statistical and sensory data. However, existing published data appear in various formats and contain defects. Therefore, few problems have been solved using these data. In this research, we sought to address this problem, by considering a university campus as a microcosm of society, designed data integration schema, and consolidated data into a knowledge graph. We then, applied and modified existing completion methods. In particular, regarding the bicycle environment, we trained our knowledge graph and evaluated it with the conventional method and our proposed derivative method, respectively. Using approximately 650 parking data with various dates and times, our method correctly estimated 54.5 more bicycles than the conventional method by comparing each time's mean absolute error.

In order to keep up with a changing business environment, organizations need to understand their current business processes and business goals. The business process model and the goal model are complementary elements and are effective means for describing the present state of the organization. There are various methods to repair these models, but in order to analyze the current state of the organization, it is necessary to analyze not only these conceptual models but also logs of organizational daily operations. Although process mining is an effective means, there is no established technique for repairing both goal models and business process models according to logs. In this paper, we propose a pattern-based method to repair goal models dealing with the repair of business process models. By doing so, it is possible to analyze the current situation of business processes and business goals while maintaining the relationship between the goal model and the business process model. We represented the effectiveness of our method by carrying out a case study.

Many surprising recipes which have different the ingredients or the cooking processes from the normal recipes exist in the user-generated recipe sites. The easiest way to find surprising recipes is to use the search function of the recipe sites. However, the title of surprising recipes do not always include the keyword “surprise”. Therefore, we cannot find surprising recipes in an easy way. In this paper, we propose a method to extract surprising recipes from the user-generated recipe sites. We propose RF-IIF (Recipe Frequency-Inverse Ingredient Frequency) based on TF-IDF (Term Frequency-Inverse Ingredient Frequency). First, we calculate the surprising value of the ingredients by using RF-IIF. Then, we calculate the surprising value of each recipe by summing the surprising value of the ingredients appearing in a recipe. Finally, we extract recipes which have high surprising value of the recipe as surprising recipes of the dish category. In the evaluation experiment, the subjects were requested an evaluation about each surprising recipe. As a results, we showed that the extracted recipes were valid recipe and had the element of surprise. And, we showed the usefulness of the our proposed method.

Nowadays, anybody can easily express their opinion publicly through Consumer Generated Media. Because of this, a phenomenon of flooding criticism on the Internet, called flaming, frequently occurs. Although there are strong demands for flaming management, namely, a service to reduce damage caused by a flaming after one occurs, it is very difficult to properly do so in practice. We are trying to keep the flaming from happening. Concretely, we propose methods to identify a potential tweet which will be a likely candidate of a flaming on Twitter, considering public opinion among twitter users. We divide flamings into three categories: criminal episodes, struggles between conflicting values and secret exposures. The first two represent the vast majority of flaming cases. As for the CEs, a Naive Bayes-based method has been promising to identify the cases. As for the SBCVs, we propose a dynamic P/N analysis based on daily polarity, which represents the strength of the polarity of public opinion on a given topic. An experiment using a past flaming case has shown that the method has successfully explained the case as one caused by a gap between the polarity of the tweet and that of public opinion.

There is a need for the development of systems that are compliant with laws in public administration, because their administrative activities are based on laws. When new laws are made or existing laws are amended, however, civil servants need to develop or modify the systems in the short time before the laws are issued. Related work in requirements elicitation from the legal texts includes approaches using ontology but there are difficulties in building an ontology for practical use. In this paper we propose pre-defined templates with the expression of functional requirements to identify legal texts, including their functional requirements, and a support tool consisting of two functions, one for automatic summary creation from complicated legal texts and one for the suggestion of the legal texts, including their functional requirements. We have also applied this approach to Japanese laws and have evaluated its accuracy. Our research revealed that using this approach can identify functional requirements with high accuracy.

Recently, the video hosting is one of the most popular services on the Web. The service user can search movies by title, tag, date, and so on. However, the user can hardly obtain information on a particular scene of a movie. Thus, it is very difficult to determine whether a movie contains interesting scenes or not. This research aims to provide information in order to help a user to choose a movie. Concretely, this paper proposes a method for labeling scenes in a movie using a video hosting service called "Nico Nico Douga". The proposed method extracts important scenes in a movie from "Nico Nico Douga" based on the statistics of social annotations attached to them. Also, using the characteristics of folksonomy the authors extract feature words for labeling. Moreover, in order to take advantage of the feature words, the authors estimate their semantic categories. We use the attached comments themselves to label the important scenes. In order to select the comments, the authors take into account the importance of the feature words with semantic categories in a scene. Finally, the authors carry out experiments to evaluate the proposed method and to discuss future works.

This paper discusses the Top SE program established to bridge the industry-academia gap. The program features extensive use of software engineering tools, not only to introduce students to the tools, but also as a conduit for learning the techniques and guidelines needed to apply the tools to practical software development situations. The curriculum is organized around practical problems mainly from the area of digital home appliances and focuses on upper stream software development processes. The Top SE program is developed and operated by a close collaboration between industry and academia. We illustrate our discussion with examples from one of the courses, verification of design models, which takes up model checking technologies, including three specific tools: SPIN, SMV, and LTSA.

Web services technology for interoperability, dynamic discovery and integration of distributed components is to be applied in various environments, such as networks of relatively narrow and unstable wireless connections. However, in such environments it is necessary to deal with resource limitation. Our work adopts mobile agent technology in response to this problem and presents a mobile agent framework for Web Services integration. This framework utilizes BPEL (Business Process Execution Language for Web Services) for description of the integration logic, and provides declarative descriptions for physical behaviors (migration and cloning). This facilitates addition or change of physical behaviors according to the environmental conditions while preserving the integration logic. This paper especially focuses on formal definition and discussion of our framework.

As wide-area open networks like the Internet and intranets grow larger, mobile agent technology is attracting more attention. Agents are units of software that can deal with environmental changes and the various requirements of open networks through features such as autonomy, mobility, intelligence, cooperation, and reactivity. However, since the usual development methods of the agent systems are not sufficiently investigated, the technology is not yet widespread. In previous papers, we introduced behavior patterns for mobile agent systems and the development method. The behavior patterns represent typical and recurring structures and behaviors of agents. The patterns are classified according to their appropriate architectural levels and the degree to which they depend on specific agent platforms. We evaluate the advantages of our method from the development process viewpoints. Our evaluation focuses on the development efficiency, the applicability, the extensibility and the understandability of our method.

As wide-area open networks such as the Internet and intranets grow larger, agent technology is attracting more attention.Agents are units of software that can deal with environmental changes and the various requirements of open networks through features such as autonomy, mobility, intelligence, cooperation, and reactivity.However, since the usual development method of the agent systems is not sufficiently investigated, the technology is not yet widespread.This paper proposes a method of agent system development based on agent patterns that represent typical and recurring structures and behaviors of agents.The agent patterns are classified according to their appropriate architectural levels and the degree to which they depend on specific agent platforms.Our method enables developers to design agent systems efficiently since' they can construct complicated system architectures and behaviors by dividing the design process into two architectural levels and applying the appropriate agent patterns.In addition, the higher level designs are independent of specific agent platforms and can be therefore easily reused.

This paper proposes a method of agent system development based on agent patterns that represent typical and recurring structures and behaviors of agents. The agent patterns are classified according to their appropriate architectural levels and the degree of their dependence on specific agent platforms. Our method enables developers to design agent systems efficiently since they can construct complicated system architectures and behaviors by dividing the design process into two architectural levels and applying the appropriate agent patterns. In addition, the higher level designs are independent of specific agent platforms and can be therefore easily reused.

We propose two new concepts, evolutional agent and field. The main purpose of the work is to provide a framework for building software which adapts to changes of requirements autonomously. In open networks, the adaptability to changes of requirements or environments is essential, while there are many free applications and components to serve various requirements. Focusing on this point, we introduce concurrent objects with meta-base architecture, agents, and fields, another kind of object. In our model, adaptive agents, called evolutional agents, adapt to changes by traversing a network and acquiring components as their own functions. Fields are receptacles of software components in networks. Agents evolve into enhanced ones by traveling to fields and acquiring components from the fields. Flage is a framework for building the software architecture based on these concepts.

We propose Flage, a language for building software modules (agents) which adapt to a change of environment in an open distributed system. Environments are defined as multiple agents and specifications which consist of constraints for cooperation among the agents. Flage provides a description of environments by the notion of agents and fields. We describe the concept of Flage and the adaptation technique.>