Software Security Analysis: an Example Case Study

It has been reported in the literature that about twenty new software vulnerabilities are reported weekly. This situation has increased the security awareness in the software community. Nowadays, software services are expected not only to satisfy functional requirements but also to resist malicious attacks. As demand for more trustworthy systems is increasing, the software industry is adjusting itself to security standards and practices by increasing security assessment and testing effort. Even though there is a consensus that better software engineering is to improve software quality in the early stage of software development, so far, various approaches that have been proposed to analyze and quantitatively measure the software security target, primarily show the finished software products in their operational life. There are few achievements on how to reduce or effectively mitigate the security risks faced by software products during the development process. In this chapter, the authors introduce a novel model-driven perspective on secure software engineering, which integrates seamlessly software security analysis with traditional software development activities. A systematic security engineering process that starts in the early stages of the software development process and spans the entire software lifecycle is presented. Fundamental software security concepts and analysis techniques are also introduced, and several illustrative examples are presented, with focus on security requirements and risk analysis.

The main applications of AI technology in Internet finance include decision-making early warning, intelligent risk control, intelligent customer service, etc. Based on the above applications, this paper analyzes the security risks faced by Internet finance, including the intelligent evolution of hacker attacks, and self-learning that makes illegal intrusion difficult to detect, and then uses the deep learning algorithm to analyze the current defects, and the application effect of intelligent investment consulting is poor; Illegal acquisition or use of personal information makes it difficult to protect user privacy; There are security risks in intelligent risk control, and it is impossible to prevent risk control loopholes by antagonizing samples. On this basis, this paper uses deep learning to propose corresponding security management strategies from the four perspectives of algorithm, supervision, ethics and cooperation. The simulation results show that the algorithm proposed in this paper can effectively monitor its vulnerabilities.

Information society is rapidity developing in the various fields of banking, trade, medical service, energy, and education using information system. Evaluation for security risk analysis should be done before security management for information system and security risk analysis is the best method to safely prevent it from occurrence, solving weaknesses of information security service. In this paper, modeling it did the CBR (case-based reasoning) evaluation function it will be able to establish the evaluation plan of optimum. CBR evaluation functions manage a security risk analysis evaluation at project unit. It evaluates the evaluation instance for beginning of history degree of existing. It seeks the evaluation instance which is similar and result security risk analysis evaluation of optimum about under using planning.

Digitalization forces manufacturing companies to shift towards customer-oriented, highly data-driven forms of value creation. This results in a changing IT security risk landscape as data becomes an attractive target for adversaries leading to an increasing number of attacks. In order to successfully protect data, it is essential that it is assessed in an integrated manner. Although IT security and data-based value creation have been studied by large research bodies, the existing literature fails to provide guidance on IT security risk analysis in data-based value chains. To contribute to the closure of this research gap, we propose a modeling approach which allocates different data types to value activities and analyses the data types in relation to the properties of relevant IT security risks. The evaluation, conducted with industry experts, reveals that it is not only a company’s primary assets that are of concern but also less important data types subject to significant levels of exposure that bear considerable IT security risks.

Advanced technologies can improve the efficiency of business processes, but incorrect system implementation can also become a huge source of damage. Therefore, the issue of IT security is very important. The concept of IT security has many aspects. One of them is security risk analysis, which must be considered by each system developer. The article describes one of the risk analysis methods - the CORAS method. The goal of research was to complete the risk analysis of the loan comparison platform. As a result, the risk mitigation recommendations were developed.

Despite a long-standing need to incorporate human factors into security risk analysis, taking a balanced approach to analysing security and usability concerns remains a challenge. Balancing security and usability is difficult due to human biases in security perception, and managing the sheer volume of data arising from risk and task analysis. This paper presents an approach for qualitatively and quantitively analysing and visualising the results of risk and task analysis. We demonstrate this approach using a realistic example, and we discuss how these techniques fit within the larger context of secure systems design.

Due to the dramatic increase in intrusive activities architecture security analysis and design has emerged as an important aspect of the development of software services. It is a well-accepted fact in software engineering that security concerns like any other quality concerns should be dealt with in the early stages of software development. However, current software security risk analysis approaches still heavily rely on ad hoc techniques. These involve significant amount of subjective efforts creating greater potential for inaccuracies. In this paper, we propose a User System Interaction Effect (USIE) model that can be used systematically to derive and analyze security concerns from service-oriented software architectures. Many aspects of the model derivation and analysis can be automated, which limit the amount of user involvement, and thereby reduce the subjectivity underlying typical security risk analysis process. The model can be used as a foundation for systematic analysis of software services from different security perspectives.

Network security risk assessment of football matches based on data mining technology

This document presents the security automated Risk Assessment Methodology (RAM) prototype tool developed by Sandia National Laboratories (SNL). This work leverages SNL's capabilities and skills in security risk analysis and the development of vulnerability assessment/risk assessment methodologies to develop an automated prototype security RAM tool for critical infrastructures (RAM-CITM). The prototype automated RAM tool provides a user-friendly, systematic, and comprehensive risk-based tool to assist CI sector and security professionals in assessing and managing security risk from malevolent threats. The current tool is structured on the basic RAM framework developed by SNL. It is envisioned that this prototype tool will be adapted to meet the requirements of different CI sectors and thereby provide additional capabilities.

Chapter 1 - Domain 1: Information Security Governance and Risk Management

The increasing complexity of the medical regulatory environment and the inherent complexity of medical devices, especially due to the increased use of connected devices and embedded control software, impose adoption of new methods and tools for the system design, safety and security analyses. In this paper, we propose a method and an associated toolchain to couple model-based system engineering and safety/security analyses at the design phase of medical devices. The method is compliant with ANSI/AAMI/ISO TIR57 safety and security guidance, and compatible with INCOSE Biomedical-Healthcare Model-Based Systems Engineering works. The toolchain is based on a system architecture modelling tool and supports medical device domain specific reference architecture, as well as tools for safety and security risk analyses. The proposed method and toolchain are illustrated by considering a RGB’s TOF-CUFF monitor device analyzed in the scope of the AQUAS project as a medical device use case.

Public Data Center is the Information Heart of the Government, this article focuses on security risk analysis, continuously deepens research on safety precautions and standard safety management systems, and establishes an overall framework for improving safety systems to ensure the safety and reliability of data centers.

It is intended in this work to review the bookNetworks and Network Analysis for Defence and Security, 978-3-319-04146-9 published in Springer Series “Lecture Notes in Social Networks”. In this book the following areas are covered: Defence and security risk analysis; Criminal intelligence; Cyber crime;Cognitive analysis; Counter-terrorism and Social Network Analysis; Transnational Crime; Critical infrastructure analysis; Support to defence and security intelligence, emphasizing the idea that network analysis is a “key enabler in supporting defence and security”.Not only man-made threats against nation’s security are considered but also the ones resulting from natural hazards. With the emergence and enormous progress in“big data” analysis together with innovative interpretative approaches, network analysis facilitates a greater understanding of complex networks: their entities, inter dependencies and vulnerabilities.

Application of AI Technology in Internet Finance and Analysis of Security Risks

With the advancement of the construction of the power Internet of Things, the transformation of network applications to interconnection and data applications to interactive sharing has brought new challenges to power grid security protection. This paper conducts an in-depth analysis and research on the network security risks faced by all levels of the power Internet of Things, and proposes corresponding security protection measures and safety development suggestions to provide security service guarantees for various power Internet of Things businesses.