To conduct empirical research on industry software development, it is necessary to obtain data of real software projects from industry. However, only few such industry data sets are publicly available; and unfortunately, most of them are very old. In addition, most of today's software companies cannot make their data open, because software development involves many stakeholders, and thus, its data confidentiality must be strongly preserved. To that end, this study proposes a method for artificially generating a “mimic” software project data set, whose characteristics (such as average, standard deviation and correlation coefficients) are very similar to a given confidential data set. Instead of using the original (confidential) data set, researchers are expected to use the mimic data set to produce similar results as the original data set. The proposed method uses the Box-Muller transform for generating normally distributed random numbers; and exponential transformation and number reordering for data mimicry. To evaluate the efficacy of the proposed method, effort estimation is considered as potential application domain for employing mimic data. Estimation models are built from 8 reference data sets and their concerning mimic data. Our experiments confirmed that models built from mimic data sets show similar effort estimation performance as the models built from original data sets, which indicate the capability of the proposed method in generating representative samples.

We propose a new security model based on MLS Policy to achieve a better security performance on confidentiality, integrity and availability. First, it realizes a combination of BLP model and Biba model through a two-dimensional independent adjustment of integrity and confidentiality. And, the subject's access range is adjusted dynamically according to the security label of related objects and the subject's access history. Second, the security level of the trusted subject is extended to writing and reading privilege range respectively, following the principle of least privilege. Third, it adjusts the objects' security levels after adding confidential information to prevent the information disclosure. Fourth, it uses application-oriented logic to protect specific applications to avoid the degradation of security levels. Thus, it can ensure certain applications operate smoothly. Lastly, examples are presented to show the effectiveness and usability of the proposed model.

Authenticated encryption schemes are very useful for private and authenticated communication. In 2010, Rasslan and Youssef showed that the Hwang et al.'s authenticated encryption scheme is not secure by presenting a message forgery attack. However, Rasslan and Youssef did not give how to solve the security issue. In this letter, we give an improvement of the Hwang et al.'s scheme. The improved scheme not only solves the security issue of the original scheme, but also maintains its efficiency.

This paper deals with security issues in a mobile agent system, especially protecting agent data from malicious servers. For this purpose, one-time key generation system, OKGS in short, is proposed. In OKGS, we integrate notions of an one-way hash function and a coupler. A one-way function plays a major role in ensuring confidentiality and integrity of agent data. And the notion of a coupler is used to establish inter-relationship among consecutive encryption keys for agent data, i.e,. all agent keys form a unidirectional chain. With these two features of OKGS, therefore, only the agent owner, who creates the agent bearing data, can decrypt and protect all agent data which are gathered in its itinerary.