Considerations for a Planned Democratizing Data Framework for Valid and Trusted Data

A key requirement of today’s fast changing business outcome and innovation environment is the ability of organizations to adapt dynamically in an effective and efficient manner. Becoming a data-driven decision-making organization plays a crucially important role in addressing such adaptation requirements. The notion of “data democratization” has emerged as a mechanism with which organizations can address data-driven decision-making process issues and cross-pollinate data in ways that uncover actionable insights. We define data democratization as an attitude focused on curiosity, learning, and experimentation for delivering trusted data for trusted insights to a broad range of authorized stakeholders. In this paper, we propose a general indicator framework for data democratization by highlighting success factors that should not be overlooked in today’s data driven economy. In this practice-based research, these enablers are grouped into six broad building blocks: 1) “ethical guidelines, business context and value”, 2) “data leadership and data culture”, 3) “data literacy and business knowledge”, 4) “data wrangling, trustworthy & standardization”, 5) “sustainable data platform, access, & analytical tool”, 6) “intelligent data governance and privacy”. As an attitude, once it is planned and built, data democratization will need to be maintained. The utility of the approach is demonstrated through a case study for a Cameroon based start-up company that has ongoing data analytics projects. Our findings advance the concepts of data democratization and contribute to data free flow with trust.

Data Trust/CeMs安全认证系统

PKI(Public Key Infrastructure,公开密钥基础设施)是在公开密钥技术基础上发展起来的一种综合安全平台,它能够透明地提供基于公开密钥的加密和数字签名等安全服务;构建PKI的主要目的是为了对密钥和证书进行管理.利用PKI可以方便地建立和维护一个可信的网络环境,从而使得人们在这个无法直接相互面对的环境里,能够确认彼此的身份和安全的交换信息,能够安全地从事商务活动.

Ensuring User Privacy and Model Security via Machine Unlearning: A Review

As an emerging discipline,machine learning has been widely used in artificial intelligence,education,meteorology and other fields.In the training of machine learning models,trainers need to use a large amount of practical data,which inevitably involves user privacy.Besides,by polluting the training data,a malicious adversary can poison the model,thus compromising model security.The data provider hopes that the model trainer can prove to them the confidentiality of the model.Trainer will be required to withdraw data when the trust collapses.In the meantime,trainers hope to forget the injected data to regain security when finding crafted poisoned data after the model training.Therefore,we focus on forgetting systems,the process of which we call machine unlearning,capable of forgetting specific data entirely and efficiently.In this paper,we present the first comprehensive survey of this realm.We summarize and categorize existing machine unlearning methods based on their characteristics and analyze the relation between machine unlearning and relevant fields(e.g.,inference attacks and data poisoning attacks).Finally,we briefly conclude the existing research directions.

A Private User Data Protection Mechanism in TrustZone Architecture Based on Identity Authentication

In Trust Zone architecture, the Trusted Application（TA） in the secure world does not certify the identity of Client Applications（CA） in the normal world that request data access, which represents a user data leakage risk. This paper proposes a private user data protection mechanism in Trust Zone to avoid such risks. We add corresponding modules to both the secure world and the normal world and authenticate the identity of CA to prevent illegal access to private user data. Then we analyze the system security, and perform validity and performance tests.The results show that this method can perform effective identity recognition and control of CA to protect the security of private user data. After adding authentication modules, the data operation time of system increases by about0.16 s, an acceptable price to pay for the improved security.

Multikernel:Operating system solution to generalized functional safety

With the trend of digitalization,intelligence,and networking sweeping the world,functional safety and cyber security are increasingly intertwined and overlapped,evolving into the issue of generalized functional safety.Traditional system reliability technology and network defense technology cannot provide quantifiable design implementation theories and methods.As the cornerstone of software systems,operating systems in particular are in need of efficient safety assurance.The DHR architecture is a mature and comprehensive solution,and it is necessary to implement an OS-level DHR architecture,for which the multi-kernel operating system is a good carrier.The multi-kernel operating system takes the kernel as the processing scenario element and constructs redundancy,heterogeneity,and dynamism on the kernel,so it has the generalized robustness of the DHR architecture.This article analyzes the significance and requirements of OS-level DHR architecture,and systematically explains how the multi-kernel operating system responds to the requirements of OS-level DHR architecture by analyzing the technical routes of multi-kernel operating systems and develops an operating system solution idea for the generalized functionally safety.

Towards building a firm metaverse security base

The Metaverse is a significant field that is currently receiving considerable attention from both the industry and academia.The transformation of the Metaverse from science fiction to reality is being actively promoted by technology,industry,and capital.However,the development of the Metaverse is still in its early stages,and the system architecture and theoretical technology of the Metaverse are not yet mature.This paper provides a comprehensive analysis of the Metaverse and summarizes its holographic,omnipotent,multidimensional,and multifaceted characteristics.The development of the Metaverse is founded on the relevant infrastructure,and we elaborate on the primary components of the Metaverse infrastructure.Furthermore,we systematically summarize the security risks inherent in the Metaverse infrastructure.Based on this,we propose utilizing the system security technology concept to guide the construction of a Metaverse security protection system from various perspectives at each level of computing,cloud,network,digital assets,and terminals,in order to construct a secure foundation for addressing the Metaverse’s security risks and challenges.

Trust Attestation Mechanism for the Sensing Layer Nodes of Internet of Things

The main function of Internet of Things is to collect and transmit data.At present,the data transmission in Internet of Things lacks effective trust attestation mechanism and trust traceability mechanism of data source.To solve the above problems,a trust attestation mechanism for sensing layer nodes is presented.First a trusted group is established,and the node which is going to join the group needs to attest its identity and key attributes to the higher level node.Then the dynamic trust measurement value of the node can be obtained by measuring the node data transmission behavior.Finally the node encapsulates the key attributes and trust measurement value to use short message group signature to attest its trust to the challenger.This mechanism can measure the data sending and receiving behaviors of sensing nodes and track the data source,and it does not expose the privacy information of nodes and the sensing nodes can be traced effectively.The trust measurement for sensing nodes and verification is applicable to Internet of Things and the simulation experiment shows the trust attestation mechanism is flexible,practical and efficient.Besides,it can accurately and quickly identify the malicious nodes at the same time.The impact on the system performance is negligible.