Mutual information maximizing GAN inversion for real face with identity preservation

Recent generative adversarial networks (GANs) have yielded remarkable performance in face image synthesis. GAN inversion embeds an image into the latent space of a pretrained generator, enabling it to be used for real face manipulation. However, current inversion approaches for real faces suffer the dilemma of initialization collapse and identity loss. In this paper, we propose a hierarchical GAN inversion for real faces with identity preservation based on mutual information maximization. We first use a facial domain guaranteed initialization to avoid the initialization collapse. Furthermore, we prove that maximizing the mutual information between inverted faces and their identities is equivalent to minimizing the distance between identity features from inverted and original faces. Optimization for real face inversion with identity preservation is implemented on this mutual information-maximizing constraint. Extensive experimental results show that our approach outperforms state-of-the-art solutions for inverting and editing real faces, particularly in terms of face identity preservation.     

Cybersecurity through the lens of Digital Identity and Data Protection: Issues and Trends

The use of a secure and robust digital identification system that is capable of protecting privacy is an essential, reliable and user-friendly element for a strong cyber resilience strategy and is a source of new business opportunities and applications for banks, private sector with a return on their investment.The march towards Digital Identity is well underway therefore, focus should be on both adoption and adaption of the new structures and regulations. These are needed to govern the associated services and transactions as well as establishing laws that enforce penalties for violations.There is no doubt then that more and more entities and institutions would move to the cloud. Security challenges affecting the cloud may not be new but the mode of addressing them would be different. The authors develop a Data Colouring technique for securing data processed or stored on both cloud and non-cloud platforms. The technique combines Public Key Infrastructure (PKI), concatenated fingerprints and digital watermarking. Using this technique, data can be secured at creation or during storage and remains secure during processing.     

Validation and application of a German version of the Dietarian Identity Questionnaire: Revealing differences between omnivores,vegetarians, and vegans

The Dietarian Identity Questionnaire (DIQ; Rosenfeld & Burrow, 2018) assesses how an individual thinks, feels, and behaves regarding the consumption or eschewal of animal products. This instrument offers a useful method for understanding how omnivores, vegetarians, and vegans alike construct their eating behaviours. In the current study (N = 961), we validated a German translation of the DIQ – the DIQ-D – and compared the dietarian identity profiles of omnivores, vegetarians, and vegans. Confirmatory factor analyses replicated the factor structure reported for the DIQ in English-speaking samples. Compared to omnivores, vegetarians considered their diet to be more central to their overall sense of identity, felt stronger motivations to follow their diet, adhered to their diet more strictly, evaluated their dietary in-group more favourably, evaluated their dietary out-group more negatively, and felt as though their dietary in-group was judged more negatively by others. For all of these effects, vegans reported more extreme scores than did vegetarians. Exploratory analyses of more nuanced dietary subgroups revealed differences in dietarian identity profiles between vegans who consume honey versus vegans who eschew honey and between pescetarians who self-identify as vegetarians versus pescetarians who do not. Our findings suggest that the DIQ-D offers a valuable method for identifying psychological correlates of people’s dietary relationships with animal products.     

基于密钥共享的分层混合认证模型

随着信息时代的迅速发展,云计算数据访问安全已经成为了用户最关心的问题。身份认证技术是确保参与者在开放的网络环境中实现安全通信的一种重要手段,如何利用身份认证技术为云环境安全保驾护航,成为学者研究的热点。文中通过公钥基础设施(Public Key Infrastructure,PKI)颁发CA证书以在不同云服务间建立信任,将多个采用身份密码体制(Identity-Based Encryption,IBE)的云联合起来；采用分层身份加密体系,引入共享密钥技术,通过选取成环结构,提出一种PKI-IBE混合认证模型方案,并对方案的安全性进行分析,从理论上证明了云环境下PKI-IBE(Public Key Infrastructure-Identity-Based Encryption)同层成环模型提供服务的可行性。同时文中设计了一种基于该模型的签密技术,通过公私密钥对实现云内认证以及跨云认证。安全性理论证明与性能分析表明,该方案在计算量稍增加的前提下,保证了足够的安全性,更加满足云环境下的用户分属不同云域的认证以及用户安全访问的需求,有效解决了云环境中数据访问的安全问题。     

基于哈希链的软件定义网络路径安全

针对软件定义网络中，控制器无法保证下发的网络策略能够在转发设备上得到正确执行的安全问题，提出一种新的转发路径监控安全方案。首先以控制器的全局视图能力为基础，设计了基于OpenFlow协议的路径凭据交互处理机制；然后采用哈希链和消息验证码作为生成和处理转发路径凭据信息的关键技术；最后在此基础上，对Ryu控制器和Open vSwitch开源交换机进行深度优化，添加相应处理流程，建立轻量级的路径安全机制。测试结果表明，该机制能够有效保证数据转发路径安全，吞吐量消耗比SDN数据层可信转发方案（SDNsec）降低20%以上，更适用于路径复杂的网络环境，但时延和CPU使用率的浮动超过15%，有待进一步优化。     

A Privacy-Preserving Attribute-Based Reputation System in Online Social Networks

Online social networks (OSNs) have revolutionarily changed the way people connect with each other. One of the main factors that help achieve this success is reputation systems that enable OSN users to ...     

适用于无线体域网的动态口令认证协议

无线体域网中传输的是与生命高度相关的敏感数据，身份认证是信息安全保护的第一道防线。现有的基于人体生物信息的身份认证方案存在信息难提取、偶然性大和误差性大的问题，基于传统密码学的认证方案需较大计算资源和能量消耗，并不适用于无线体域网环境。为此，在动态口令和非对称加密机制基础上，提出一种适用于无线体域网的动态口令双向认证轻量协议，并对其进行形式化分析。通过理论证明、SVO逻辑推理及SPIN模型检测得出：该协议满足双向认证，且能够抵御重放攻击、伪装攻击、拒绝服务器攻击和口令离线攻击，具有较高安全性。