Biblio
With the implementation of W ⊕ X security model on computer system, Return-Oriented Programming(ROP) has become the primary exploitation technique for adversaries. Although many solutions that defend against ROP exploits have been proposed, they still suffer from various shortcomings. In this paper, we propose a new way to mitigate ROP attacks that are based on return instructions. We clean the scratch registers which are also the parameter registers based on the features of ROP malicious code and calling convention. A prototype is implemented on x64-based Linux platform based on Pin. Preliminary experimental results show that our method can efficiently mitigate conventional ROP attacks.
Device-to-device communication is widely used for mobile devices and Internet of Things. Authentication and key agreement are critical to build a secure channel between two devices. However, existing approaches often rely on a pre-built fingerprint database and suffer from low key generation rate. We present GeneWave, a fast device authentication and key agreement protocol for commodity mobile devices. GeneWave first achieves bidirectional initial authentication based on the physical response interval between two devices. To keep the accuracy of interval estimation, we eliminate time uncertainty on commodity devices through fast signal detection and redundancy time cancellation. Then, we derive the initial acoustic channel response for device authentication. We design a novel coding scheme for efficient key agreement while ensuring security. Therefore, two devices can authenticate each other and securely agree on a symmetric key. GeneWave requires neither special hardware nor pre-built fingerprint database, and thus it is easyto-use on commercial mobile devices. We implement GeneWave on mobile devices (i.e., Nexus 5X and Nexus 6P) and evaluate its performance through extensive experiments. Experimental results show that GeneWave efficiently accomplish secure key agreement on commodity smartphones with a key generation rate 10× faster than the state-of-the-art approach.