This paper presents the concept of Digital Ji-in, a framework for managing permanent digital identifiers whose structure is based on a peer to peer network. The origin of the term Digital-Ji-in is explained in the paper. We describe several types of identifiers and explain why their management is already an important issue. We show that some identifiers have been reused, creating significant problems. We propose a framework for maintaining identifier information safely over a long period of time. We present its structure based on a secure network of peers. We also describe some use cases of this framework. However, as only identifiers are recorded mechanically, problems may arise if data should be associated with them. We discuss this issue at the end of the paper.

Researching for malware detection using machine learning is becoming active. However, conventional detection techniques do not consider the impact of attacks on machine learning, which has become complicated in recent years. In this research, we focus on data poisoning attack, which is one of the typical attacks on machine learning, and aim to clarify the influence of attacks on malware detection technology. Data poisoning attack is an attack method that intentionally manipulates the predicted result of a learned model by injecting poisoning data into training data, and by applying this, it is possible to embed a backdoor that induces mis-prediction of only specific input data. In this paper, we first propose an attack framework for backdoor embedding that prevents detection of only specific types of malware by data poisoning attack. Next, we will describe a method to generate poisoning data efficiently while avoiding attack detection by solving the optimization problem. Furthermore, we take malware detection technology using logistic regression and show the effectiveness of the our method through evaluation experiments using two datasets.

In this paper we discuss the optimization problems with noisy fitness function. On financial optimization problems, Monte-Carlo method is commonly used to evaluate the optimization criteria such as value at risk. The evaluation model is often very complex which needs considerable computational overheads. In order to realize efficient optimization of financial problems, we propose a method to decide the number of samples used to estimate the optimization criteria. Selection efficiency proposed in this paper is a index that shows how close the population approaches to the convergence to a good solution. In general, it is difficult to calculate selection efficiency analytically. Thus we also employ bootstrap method to estimate selection efficiency. The resulting algorithm is applied to the optimization of the procurement plan optimization problem. The result shows that value at risk of the problem is optimized efficiently by the proposed method.

In order to improve the responsiveness to changes and uncertainties around production activity, we should have the integrated methodology which allows us to uniformly model and design the total system including production and planning resource and related information exchanged among resources. We propose the agent model and the modeling methodology. There are two types of the agent in our model. One is a service agents that offers some processing functions. The other is a mobile agent that moves among service agents. A manufacturing resource is modeled as one of the service agents since it provides manufacturing functions. On the other hand, each lot or production instruction information controlling production progress can be model as one of the mobile agents.

Cooperative work is done not only by workers but with some software used by each worker. They do various communications including interaction between worker and software in cooperative works. To develop computer supported cooperative work systems, it is important to support various communications among them. A computational model that can represent communicative objects such as workers and software and various communications among them is necessary for that purpose. We propose this communication computation model as such a model. A worker and software are represented as the Autonomous Object, and a group is represented as the Group Field in this model. Various communications are represented by communicative functions that correspond to each communication form. We show that our model is effective for modeling various communications in cooperative work.