Enhancing Secure Development in Globally Distributed Software Product Lines: A Machine Learning-Powered Framework for Cyber-Resilient Ecosystems

Embracing software product lines(SPLs)is pivotal in the dynamic landscape of contemporary software devel-opment.However,the flexibility and global distribution inherent in modern systems pose significant challenges to managing SPL variability,underscoring the critical importance of robust cybersecurity measures.This paper advocates for leveraging machine learning(ML)to address variability management issues and fortify the security of SPL.In the context of the broader special issue theme on innovative cybersecurity approaches,our proposed ML-based framework offers an interdisciplinary perspective,blending insights from computing,social sciences,and business.Specifically,it employs ML for demand analysis,dynamic feature extraction,and enhanced feature selection in distributed settings,contributing to cyber-resilient ecosystems.Our experiments demonstrate the framework’s superiority,emphasizing its potential to boost productivity and security in SPLs.As digital threats evolve,this research catalyzes interdisciplinary collaborations,aligning with the special issue’s goal of breaking down academic barriers to strengthen digital ecosystems against sophisticated attacks while upholding ethics,privacy,and human values.

Virtual earth cloud: a multi-cloud framework for enabling geosciences digital ecosystems

Humankind is facing unprecedented global environmental and social challenges in terms of food,water and energy security,resilience to natural hazards,etc.To address these challenges,international organizations have defined a list of policy actions to be achieved in a relatively short and medium-term timespan.The development and use of knowledge platforms is key in helping the decision-making process to take significant decisions(providing the best available knowledge)and avoid potentially negative impacts on society and the environment.Such knowledge platforms must build on the recent and next coming digital technologies that have transformed society–including the science and engineering sectors.Big Earth Data(BED)science aims to provide the methodologies and instruments to generate knowledge from numerous,complex,and diverse data sources.BED science requires the development of Geoscience Digital Ecosystems(GEDs),which bank on the combined use of fundamental technology units(i.e.big data,learning-driven artificial intelligence,and network-based computing platform)to enable the development of more detailed knowledge to observe and test planet Earth as a whole.This manuscript contributes to the BED science research domain,by presenting the Virtual Earth Cloud:a multi-cloud framework to support GDE implementation and generate knowledge on environmental and social sustainability.

Digital Entrepreneurship Ecosystem as a New Form of Organizing： The Case of Zhongguancun

Digital innovation is becoming increasingly important in today＇s economy. Many digital innovations are developed not within organizations, but in innovation-driven entrepreneurial ecosystems, where various entrepreneurship related stakeholders collaborate and cooperate. Despite its significance, studies on digital entrepreneurship ecosystems （DEEs） are limited and the concept is largely undertheorized. This study intends to fill that gap by studying how a DEE organizes. This organizing issue is challenging, because stakeholders of a DEE are self-organizing and are not governed by any formal authority. To answer that question, we adopt forms of organizing as a theoretical lens, which provides structure to examine organizing issues. Through an in-depth case study of Zhongguancun, the Silicon Valley of China, we unveil eight processes around the themes of division of labor and integration of efforts. We further show that the forms of organizing feature a balance of centralized design and de-centralized emergence. This balanced view extends the forms of organizing literature, which takes an either/or perspective. Ecosystem architects and policy makers who intend to build entrepreneurship ecosystems to promote local economies can derive practical implications from our findings.

A Chinese View on Social Media and Its Implications on Cyber Security

Social media development creates new challenges to the sphere of cyberspace security and privacy.WeChat and Weibo have also been targeted by phishers.This analysis places particular emphasis on how social networks influence information systems protection in China,including the aspects of strategic insights on enterprises,social governance,information security,and national security.It addresses both,major depth of reach,such as AI-based adversary reconnaissance,as well as the weaknesses-such as the use of social networks for global intelligence capture.It also discusses China’s separation and individuals with the encompassing methods of containment including legal,as well as modern methods,to counter the unique threats posed by an uncontrollable landscape of social networks.