Edge-Cloud Collaborative Defense against Backdoor Attacks in Federated Learning.

Federated learning has a distributed collaborative training mode, widely used in IoT scenarios of edge computing intelligent services. However, federated learning is vulnerable to malicious attacks, mainly backdoor attacks. Once an edge node implements a backdoor attack, the embedded backdoor mode will rapidly expand to all relevant edge nodes, which poses a considerable challenge to security-sensitive edge computing intelligent services. In the traditional edge collaborative backdoor defense method, only the cloud server is trusted by default. However, edge computing intelligent services have limited bandwidth and unstable network connections, which make it impossible for edge devices to retrain their models or update the global model. Therefore, it is crucial to detect whether the data of edge nodes are polluted in time. This paper proposes a layered defense framework for edge-computing intelligent services. At the edge, we combine the gradient rising strategy and attention self-distillation mechanism to maximize the correlation between edge device data and edge object categories and train a clean model as much as possible. On the server side, we first implement a two-layer backdoor detection mechanism to eliminate backdoor updates and use the attention self-distillation mechanism to restore the model performance. Our results show that the two-stage defense mode is more suitable for the security protection of edge computing intelligent services. It can not only weaken the effectiveness of the backdoor at the edge end but also conduct this defense at the server end, making the model more secure. The precision of our model on the main task is almost the same as that of the clean model.

An Android Inline Hooking Framework for the Securing Transmitted Data.

Information leaks can occur through many Android applications, including unauthorized access to sensors data. Hooking is an important technique for protecting Android applications and add security features to them even without its source code. Various hooking frameworks are developed to intercept events and process their own specific events. The hooking tools for Java methods are varied, however, the native hook has few methods. Besides, the commonly used Android hook frameworks cannot meet the requirement of hooking the native methods in shared libraries on non-root devices. Even though some approaches are able to hook these methods, they have limitations or are complicated to implement. In the paper, a feasible hooking approach for Android native methods is proposed and implemented, which does not need any modifications to both the Android framework and app's code. In this approach, the method's reference address is modified and control flow is redirected. Beyond that, this study combines this approach with VirtualXposed which aims to run it without root privileges. This hooking framework can be used to enforce security policies and monitor sensitive methods in shared objects. The evaluation of the scheme demonstrates its capability to perform hook operation without a significant runtime performance overhead on real devices and it is compatible and functional for the native hook.

An Identity-Based Anti-Quantum Privacy-Preserving Blind Authentication in Wireless Sensor Networks.

With the development of wireless sensor networks, IoT devices are crucial for the Smart City; these devices change people's lives such as e-payment and e-voting systems. However, in these two systems, the state-of-art authentication protocols based on traditional number theory cannot defeat a quantum computer attack. In order to protect user privacy and guarantee trustworthy of big data, we propose a new identity-based blind signature scheme based on number theorem research unit lattice, this scheme mainly uses a rejection sampling theorem instead of constructing a trapdoor. Meanwhile, this scheme does not depend on complex public key infrastructure and can resist quantum computer attack. Then we design an e-payment protocol using the proposed scheme. Furthermore, we prove our scheme is secure in the random oracle, and satisfies confidentiality, integrity, and non-repudiation. Finally, we demonstrate that the proposed scheme outperforms the other traditional existing identity-based blind signature schemes in signing speed and verification speed, outperforms the other lattice-based blind signature in signing speed, verification speed, and signing secret key size.