To deal with the exhausting annotations, self-supervised representation learning from unlabeled point clouds has drawn much attention, especially centered on augmentation-based contrastive methods. However, specific augmentations hardly produce sufficient transferability to high-level tasks on different datasets. Besides, augmentations on point clouds may also change underlying semantics. To address the issues, we propose a simple but efficient augmentation fusion contrastive learning framework to combine data augmentations in Euclidean space and feature augmentations in feature space. In particular, we propose a data augmentation method based on sampling and graph generation. Meanwhile, we design a data augmentation network to enable a correspondence of representations by maximizing consistency between augmented graph pairs. We further design a feature augmentation network that encourages the model to learn representations invariant to the perturbations using an encoder perturbation. We comprehensively conduct extensive object classification experiments and object part segmentation experiments to validate the transferability of the proposed framework. Experimental results demonstrate that the proposed framework is effective to learn the point cloud representation in a self-supervised manner, and yields state-of-the-art results in the community. The source code is publicly available at: https://github.com/VCG-NJUST/AFSRL.

Abstract The quality of service (QoS) is a momentous performance index of wireless ad hoc networks. However, unreasonable channel allocation will degrade the QoS. During the process of channel allocation, if user requests for idle channels are rejected, the QoS will lower accordingly. In this paper, we propose a dynamic channel allocation strategy for QoS enhancement to enhance the QoS and reduce the rejection rate of idle channel requests. First of all, the channel availability model is modeled as a Continuous Time Markov Chain in a bid to calculate the channel availability which is used to compute the channel availability factor (CAF) and the channel availability threshold (CAT). Then, the dynamic channel allocation process is achieved based on the comparison result of CAF and CAT. Ultimately, the QoS is guaranteed by exploiting the earliest deadline first algorithm to forward packets and enhanced by using the packet segmentation algorithm to divide packets into packet flows. The simulation results prove that the proposed channel allocation strategy increases the packet delivery ratio and throughput, decreases the end‐to‐end delay and total overhead and shows a QoS enhancement than existing schemes.

Multiple cylinders detection from large-scale and complex point clouds is a historical but challenging problem, considering the efficiency and accuracy. We propose a novel framework, named slicing-tracking-detection (STD), that detects multiple cylinders accurately and simultaneously from point clouds of large-scale and complex process plants. In this framework, the 3D cylinder detection problem is reformulated as a cylinder ingredients tracking task based on multi-object tracking (MOT). First, we generate slices from the input point cloud, and render them to slice sequence. Then, the cycle of a cylinder is modeled with a Markov Decision Process (MDP), where the ingredient is tracked with a template and the miss tracking is associated with ingredient proposals through reinforcement learning. Finally, by applying MDP for each cylinder, multiple cylinders can be detected simultaneously and accurately. Extensive experiments show that the proposed STD framework can significantly outperform the state-of-the-art approaches in efficiency, accuracy, and robustness. The source code is available at http://zhiyongsu.github.io.

Software-defined networking (SDN) has become a promising trend for managing the Industrial Internet of Things (IIoT) devices. As the core of sensitive data storage and business interaction, the SDN is vulnerable to advanced persistent threats (APTs) attacks, while honeypots have shown great promise against APT attacks. In this article, we propose a new SDN-based dynamic bounded rational honeypot-APT game model in IIoT. Specifically, the defender maximizes the utility by chossing the period strategy of honeypot collecting and analyzing the data, while the attacker maximizes utility by choosing the period strategy of its latency and attack. To describe the bounded rationality, we model the simultaneous dynamic attack and defense process through the prospect theory, in which the Prelec function and the value function are both introduced. Experiment results show that bounded rationality affects strategy selection and reduces defender and attacker’s utilities. Furthermore, our strategy outperforms the existing work in defensive performance.

With the development of detection algorithms on malicious dynamic domain names, domain generation algorithms have developed to be more stealthy. The use of multiple elements for generating domains will lead to higher detection difficulty. To effectively improve the detection accuracy of algorithmically generated domain names based on multiple elements, a domain name syntax model is proposed, which analyzes the multiple elements in domain names and their syntactic relationship, and an adaptive embedding method is proposed to achieve effective element parsing of domain names. A parallel convolutional model based on the feature selection module combined with an improved dynamic loss function based on curriculum learning is proposed, which can achieve effective detection on multielement malicious domain names. A series of experiments are designed and the proposed model is compared with five previous algorithms. The experimental results denote that the detection accuracy of the proposed model for multiple-element malicious domain names is significantly higher than that of the comparison algorithms and also has good adaptability to other types of malicious domain names.

A quantum secret sharing scheme based on orbital angular momentum (OAM) is proposed. The dealer generates single particles in OAM basis or angular position (ANG) basis randomly. The participants encode their private keys into the particles through performing quantum Fourier transforms. Then the dealer can use the single‐particle measurements to get the shared secret. In the authors’ scheme, the secret is protected by the distinguishability of OAM basis and ANG basis. Compared to the traditional two‐dimensional schemes, the authors’ scheme can use the higher dimension of OAM to increase the detecting rate of eavesdropping, and enhance the security in practice. Besides, only the single particles are needed in their scheme. Compared to the schemes based on entangled particles, the authors’ scheme will be more practical with the present technology.

Wireless covert channel is an emerging covert communication technique which conceals the very existence of secret information in wireless signal including GSM, CDMA, and LTE. The secret message bits are always modulated into artificial noise superposed with cover signal, which is then demodulated with the shared codebook at the receiver. In this paper, we first extend the traditional KS test and regularity test in covert timing channel detection into wireless covert channel, which can be used to reveal the very existence of secret data in wireless covert channel from the aspect of multiorder statistics. In order to improve the undetectability, a wireless covert channel for OFDM-based communication system based on constellation shaping modulation is proposed, which generates additional constellation points around the standard points in normal constellations. The carrier signal is then modulated with the dirty constellation and the secret message bits are represented by the selection mode of the additional constellation points; shaping modulation is employed to keep the distribution of constellation errors unchanged. Experimental results show that the proposed wireless covert channel scheme can resist various statistical detections. The communication reliability under typical interference is also proved.

Network flow watermarking (NFW) is an emerging flow correlation technique to deanonymize an anonymous communication system or detect stepping stones, in which a watermark is encoded into a network flow by manipulating some flow characteristics, predominantly by altering timing information. Although interval-based NFWs that employ time intervals as carrier have proven to be capable of resisting moderate network interference, they are vulnerable to some statistic-based attacks, which may expose the very existence of watermark and enable attackers to damage or remove watermark from the observed flow. In this study, using insider swapping of time intervals and an adaptive centroid quantization framework, we design a highly invisible NFW scheme, which is undetectable by multi-flow attacks (MFA), Kullback-Leibler divergence (KLD) test, Kolmogorov-Smirnov (K-S) test, and spread spectrum flow watermark (SSFW) detection. Experimental results using real traffic and public dataset show that the proposed NFW scheme can outperform three typical NFW schemes on invisibility while maintaining a strong interference-resistance capability of network jitter, packet loss, and dummy packet insertion.

This paper investigates the joint authentication of topology and geometry information of 2D engineering computer-aided design graphics, which focus more on topological modeling than geometric modeling of objects. A robust hashing scheme is proposed for joint topology and geometry authentication. The covariance matrices of descriptors are explored to fuse and encode both topology and geometry features of different types into a compact representation. First, a normalized binary shape texture is rendered for each geometric object through the render-to-texture technique. Then, for each geometric object, geometry features are computed based on statistical features that are extracted from image rings. Additionally, topology features are generated according to the topological relations among joint objects. To generate hash codes of the graphic, all geometric objects are first grouped according to their geometry features. Then, for each group, the covariance matrices of descriptors are applied to fuse both the topology and geometry features of all objects, and the intermediate hash codes of each group are computed based on the covariance matrices. The final hash sequence is formed by concatenating the intermediate hash codes that correspond to each group. Secret keys are introduced into both feature extraction and hash construction. The hashes are robust against topology-preserving graphic manipulations and sensitive to malicious attacks. By decomposing the hashes, the locations of tampered objects can be determined. Experimental results are presented to evaluate the performance and show the effectiveness of the method.

Abstract As the detection methods of covert channels can provide a better way to detect the existence of advanced persistent threat, it has become a hot research topic in the field of network security. Although the existing methods can achieve feasible performance for detecting the JitterBug covert timing channel, they are ineffective when the covert timing channels are implemented with sparse embedding, especially for low embedding probability. In this paper, a new method to detect JitterBug covert timing channel with sparse embedding is proposed, in which the timing intervals are first modeled in histogram statistics, and then the Kolmogorov–Smirnov statistic is used for detection. In addition, the diversifications of the references and the model updating scheme in practical usage are analyzed. The experimental results show that the proposed method is effective when the embedding probability is 0.3, while the existing methods can effective only when the embedding probability is larger than 0.6. Copyright © 2016 John Wiley & Sons, Ltd.

In existing model-based timing channels, the requirement for the target model to be shared between the sender and the receiver limits the sender's ability to adapt to changes in the inter-packet delay (IPD) distribution of the application traffic. In this paper, using analog fountain codes (AFCs) with a general model-fitting coding framework, we design timing channel schemes that allow the sender to change the target model without synchronizing with the receiver. We first propose analog fountain timing channels based on symbol transition when the application packet streams have IPD distribution that is shape similar to the distribution of AFC code symbol values. For more general packet streams, we then propose analog fountain timing channels based on symbol split in which the linearly mapped symbols are split using a symbol probability split matrix to mimic the IPD distribution of the application traffic. We use real VoIP and SSH traffic to compare the proposed schemes with model-based timing channels using LT codes and AFC. Experimental results show that both the proposed schemes are model-secure. The robustness of the two schemes is higher than the model-based timing channels using LT codes whereas not as good as those using AFC when the sender and receiver sides are synchronized with respect to the target model. Moreover, when the sender and the receiver are not synchronized with respect to the model, the robustness of the proposed schemes is significantly higher than model-based timing channels.

Abstract Matrix embedding schemes based on linear codes have been widely used in the field of steganography, which is an important branch of covert communication. Nevertheless, they appear weak for some conditions of high reliability demand or “active attack” because of the poor robustness. In this paper, with robustness analysis of matrix embedding based on Tanner graph, a general framework of damage‐resistance matrix embedding (DR‐ME) is described to take account of both robustness and embedding efficiency, which has a fair chance to recover the secret message when stego object is partly damaged. The approximated robustness–efficiency bound is derived to reveal the contradiction between robustness and embedding efficiency. Then, based on the parity‐check concatenation of systematic convolutional codes and syndrome‐trellis codes (STCs), we propose the practical damage‐resistance STCs (DR‐STCs). Experimental results show that DR‐STCs are near‐optimal DR‐ME schemes, which can approach the derived upper bound. Copyright © 2014 John Wiley & Sons, Ltd.

ABSTRACT An identity‐based threshold signcryption scheme for multiple receivers is proposed. For thenspecified receivers, the ciphertext can be decrypted and verified when arbitrarytor more receivers work together. The steps of the private keys extraction, the signcryption, the decryption, and the verification are introduced in detail. The chosen‐ciphertext security of the scheme is proved formally. The comparisons to the existing schemes show that the proposed scheme is more secure, more flexible, and the simulative game of the security proof in the scheme is more perfect. Copyright © 2010 John Wiley & Sons, Ltd.

Quantization-embedder (QE) is the basic embedding manner, which is composed of partition function, quantization function, conversion function and encoding function. For achieving statistical security, a steganographcial method based on combination of QEs is proposed to preserve the distribution of stego signal toward that of cover signal, and a practical algorithm is implemented in prediction-error domain. Experimental results show that the proposed method has high preservation ability to keep statistical security.

A novel steganographic method based on non-uniform generalized LSB is proposed. Different from the traditional distortion measure MSE and PSNR, the structural-similarity based image quality assessment is used to measure the distortion caused by the data hiding. With the given maximum allowable distortion, dynamic programming is performed to find the optimum substitution depth vector to achieve the maximum capacity. Experiments show the proposed method can achieve higher embedding payload while keeping smaller distortion.

To achieve high robustness against collusion and geometric attacks, video watermarking schemes often employ local-content-based methods in which watermarks are embedded in several semantically independent regions that partitioned from video-segments. For these schemes, self-synchronization is also an important issue that needs to be taken into account in the design of watermark detectors. In this paper, a simple and fast object-based watermarking algorithm is proposed. It is based on the techniques of motion segmentation and block matching, which is consistent with MPEG-2 standard. In the proposed algorithm, a spread spectra watermark that similar to a CDMA signal is inserted into selected video blocks so that different video contents can be protected accordingly. Experimental results have demonstrated the advantage of the scheme over other exist local content-based ones in terms of computational complexity, resistance against attacks include cropping, pixel shift and recompression etc.

In this paper, a secure voice communication system based on TMS320VC5410 is proposed, which includes the hardware design and the software design. Among them, the A/D and D/A conversions of voice signals are implemented by the MC145480, while data transmission is performed by the TL16C554. A chaotic voice encryption algorithm combining cat map and logistic map is implemented in this system. Experiments of both encrypted and non-encrypted voice communication over short distance have been performed, which demonstrates the feasibility of the proposed system.

Video encryption is a suitable method to protect video data. There are some disadvantages in the algorithms proposed before. In this paper, we propose a novel fast MPEG video encryption algorithm, which encrypts run length codes with chaotic run-length encryption algorithm (CREA), encrypts the signs of motion vectors with security-enhanced chaotic stream cipher (SECSC) and distributes keys with chaotic key distributor (CKD) at the same time. Its security, compression ratio and computational complexity are analyzed in details. Experimental results show that, the algorithm has less effect on compression ratio than the algorithms confusing DCT coefficients do, does not change file format, and is of low cost. Thus, it is suitable for secure video encoding with real-time requirement.