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Due to its open source and large user base, Android has emerged as the most popular operating system. Android's popularity and openness have made it a prime target for malicious attackers. Permissions have received great attention from researchers because of their effectiveness in restricting applications’ access to sensitive resources. However, existing malware detection methods based on permissions are easily bypassed by inter-application resource access. To address these issues, we combine inter-application resource access-related intent features with permission features. Besides, we designed a customized convolutional neural network using two squeeze-and-excitation blocks to learn the inherent relationships between multi-type features. The two basic SE blocks perform squeezing operations based on average pooling and max pooling, respectively, to compute channel-wise attention from multiple perspectives. We designed a series of experiments based on real-world samples to evaluate the efficacy of the proposed framework. Empirical results demonstrate that our framework outperforms state-of-the-art methods, achieving an accuracy of 96.29%, precision of 97.52%, recall of 94.63%, F1-score of 96.06% and MCC of 92.60%. These promising experimental results consistently demonstrate that AMERDroid is an effective approach for Android malware detection.

As the global data strategy deepens and data elements accelerate integrating and flowing more rapidly, the demand for data security and privacy protection has become increasingly prominent. Confidential computing emerges as a crucial security technology to solve security and privacy problem, and it is also a hot subject of in contemporary security technologies. Leveraging collaborative security in both hardware and software, it builds a trusted execution environment to ensure confidentiality and integrity protection for data in use. This paper provides a comprehensive overview of the development process of confidential computing, summarizing its current research status and issues, which focuses on the security requirements for data security and privacy protection. Furthermore, it deeply analyses the common technical features of confidential computing, and proposes a trusted confidential computing architecture based on collaborative hardware and software trust. Then, it elaborates on the research status and issues of confidential computing from four aspects: hardware security, architecture and key technologies, applications, and standards and evaluation. Finally, this paper provides a synthesis and outlook for the future development of confidential computing. In summary, confidential computing is currently in a rapidly developing stage and will play an important role in cyber security in the future.

This paper investigates an intelligent reflecting surface (IRS) assisted downlink short packet transmission system, where an access point sends short packets to multiple devices with the help of an IRS. Specifically, a performance comparison between the frequency division multiple access and time division multiple access is conducted for the considered system, from the perspective of average age of information (AoI). To minimize the maximum average AoI among all devices, the resource allocation and passive beamforming are jointly optimized. However, the formulated problem is difficult to solve due to the non-convex objective function and coupled variables. Thus, an alternating optimization based algorithm is proposed by exploiting the semidefinite relaxation and bisection search techniques. Simulation results show that time division multiple access can achieve lower AoI by exploiting the time-selective passive beamforming of IRS for maximizing the signal to noise ratio of each device consecutively. Moreover, it also shows that as the length of information bits becomes sufficiently large as compared to the available bandwidth, the proposed frequency division multiple access transmission scheme becomes more favourable due to more flexible power allocation.

A column-weight $�k$ LDPC code with the parity-check matrix $�H$ is called decomposable if there exists a permutation $�\pi$ on the rows of $�H$, such that $��\pi �\left(�H�\right)�$ can be decomposed into $�k$ column-weight one matrix. In this paper, some variations of edge coloring of graphs are used to construct some column-weight three decomposable LDPC codes with girths at least six and eight. Applying the presented method on several known classes of bipartite graphs, some classes of column-weight three decomposable LDPC codes are derived having flexibility in length and rate. Interestingly, the constructed parity-check matrices based on the proper edge coloring of graphs can be considered as the base matrix of some high rate column-weight three quasi-cyclic (QC) LDPC codes with maximum-achievable girth 20. The paper also leads to a simple characterization of elementary trapping sets of the decomposable codes based on the chromatic index of the corresponding normal graphs. This characterization corresponds to a simple search algorithm finds all possible existing elementary trapping sets in a girth-6 or girth-8 column-weight 3 LDPC code which are layered super set of a short cycle in the Tanner graph of the code. Simulation results indicate that the QC-LDPC codes with large girths lifted from the constructed base matrices have good performances over AWGN channel.

The purpose of this work is to explore the decrease of total used power in cell-free millimetre-wave (mm-Wave) massive multiple-input multiple-output (MIMO) systems, which can be regarded an essential technology for future wireless generations to improve system performance. One of the most important strategies for reducing total power consumption is to activate and deactivate radio frequency (RF) chains at each access point (AP) in the coverage region. Nonetheless, the optimization issue for this methodology is NP-hard, and an exhaustive search method may be used to determine the ideal number of RF chains at each AP in the cell-free network. Unfortunately, the exhaustive searching approach is prohibitively complicated, indicating that it is unworkable when there are a significant number of APs in the service region. Furthermore, present RF chain selection approaches prioritize decreasing consumed power and complexity at the price of system performance in terms of total possible rate. This research solves this issue by introducing a unique RF chain selection approach that combines Hungarian and genetic algorithms. The fact that the genetic algorithm (GA) can readily determine the ideal number of active RF chains, yet this technique generally entails significant complexity in large-scale cell-free networks, prompted this notion. As a result, the Hungarian method is used early in the GA to overcome the complexity problem while still retaining system performance. In addition, the suggested system employs a semi-centralized hybrid beamforming architecture in which all analogue combiners for all APs are operated at a central processing unit using channel state information. In addition, each AP has a fully linked phase shifters network and restricted RF chains connecting to its antennas. Finally, simulation findings reveal that, when compared to state-of-the-art techniques, the suggested approach achieves the maximum attainable rate and overall energy efficiency with a tolerable computational complexity.

This paper discusses the operation of a massive multiple-input multiple-output (MIMO) system from a different perspective. The system is performed in the presence of an eavesdropper who is trying to disrupt the message being transmitted between the base station (BS) and the users. An attempt has been made to maximize the secure energy efficiency (EE) of the system by allocating appropriate power to each user. The channel state information (CSI) between users and the BS is considered imperfect and the employed precoding scheme is the zero forcing (ZF). The CSI related to the eavesdropper is considered to be perfect and its precoding is assumed to be the maximum ratio transmission (MRT). The problem of optimization that is for maximizing the EE has two constraints including the maximum transmission power and the minimum user data rate. To improve the performance of system, the cell division technique is applied, which results in approaching the performance of system to the without eavesdropper scenario. Five various scenarios have been investigated in this research, and it is proved that the proposed method improves the system performance in all cases. The numerical and simulation results obtained from implementation of the proposed algorithm confirm the claim.

In order to solve the network congestion problem caused by burst service flows in heterogeneous cognitive radio networks (Het-CRN), a two-stage dual-threshold random early detection (TD-RED) control mechanism is proposed here. Meanwhile, a three-state Markov modulated Poisson process (MMPP-3) is used to model the burst service to analyze its arrival in depth. Moreover, a performance evaluation system (PES) is proposed to quantify the interference of burst services to different classes of services and their quality of service, which can comprehensively evaluate the performance enhancement of the TD-RED control mechanism for each service. The system examines performance metrics such as packet loss rate, average delay, average captain etc. PES simulation results show that TD-RED significantly reduces the packet rejection rate and transmission delay compared to the no congestion control (NCC) and random early detection (RED) methods, thus providing superior quality of service to all services. thereby providing a superior quality of service to cognitive users. Its lower average captain fully proves that TD-RED can effectively alleviate congestion.

In unmanned aerial vehicle ad-hoc network (UANET), the node speed of unmanned aerial vehicles (UAVs) may reach up to 400 km/h. The fast or slow movement of UAV nodes leads to different speeds of topology change of the nodes. Traditional optimized link state routing (OLSR) protocol cannot adaptively adjust the routing update period when the network topology changes, which may lead to the nodes calculating incorrect routing tables. This increases the average end-to-end delay and packet loss rate for packet transmission. To enhance the adaptability of OLSR routing protocol to network topology changes, this paper proposes a multi-agent independent deep deterministic policy gradient-OLSR (MA-IDDPG-OLSR) routing protocol based on distributed multi-agent reinforcement learning. The protocol deploys DDPG algorithm on each UAV node, and each UAV node adaptively adjusts the Hello and TC message sending intervals, according to the one-hop neighbouring nodes as well as its own state. Simulation results show that the proposed protocol is able to improve the throughput and reduce the packet loss rate as compared to traditional AODV, GRP, OLSR, and distributed multiple-agent independent proximal policy optimization-OLSR (MA-IPPO-OLSR), distributed multiple-agent independent twin delayed deep deterministic policy gradient-OLSR (MA-ITD3-OLSR) routing protocols. Since MA-IDDPG-OLSR relies only on local information, there is a minor performance degradation in MA-IDDPG-OLSR compared to centralized single-agent DQN-OLSR routing protocol. But it is more suitable to a completely distributed UAV network without a centralized node.

Communication security has become particularly crucial with the rapid development of the Internet of Things (IoT). Frequency hopping spread spectrum (FHSS) technology, a prevalent method in wireless communication, has a wide range of applications in the Internet of Things. Enhancing the security of frequency hopping sequences is an essential means to improve the security of frequency hopping communication in the Internet of Things, as the performance of frequency hopping sequences plays a crucial role in frequency hopping systems. This paper proposes constructing secure adaptive frequency hopping sequence sets based on the advanced encryption standard (AES) algorithm. As a block cipher algorithm with superior security, the AES algorithm can provide a fundamental guarantee for the security of the proposed frequency hopping sequences. The mapping methods from ciphertext sequences to frequency hopping sequences proposed in this paper can achieve the construction of frequency hopping sequences of any frequency set size to meet the requirements of adaptive frequency hopping. In addition, we also model and analyse the problem of overlapping spectrum band of the IoT groups in the industrial, scientific, and medical (ISM) band, aiming to achieve better packet transmission performance by adjusting the frequency set size.

Reconfigurable intelligent surface (RIS) can provide unprecedented spectral efficiency gains and excellent ability to manipulate electromagnetic waves. This article considered a RIS-assisted multiuser multiple-input multiple-output (MIMO) downlink system, where the beamforming at the base station and RIS are jointly designed to maximize the sum-rate. For the large dimension scenario and high-rank beamforming matrix, the accurate deterministic approximations from random matrix theory are then utilized to simplify the RIS-assisted MIMO systems. The asymptotical signal-to-interference-plus-noise ratio values obtained through random matrix theory is infinitely close to the theoretical limits calculated by accurately iteration. And the performance of the proposed algorithm computed via the sharing second-order channel statistics matches that of the RIS algorithm with sharing full channel state information asymptotically. The deterministic approximations are instrumental to get improvement into the structure of the optimal beamforming and to reduce the implementation complexity in large-scale MIMO system. Numerical simulations results are provided to evaluate and verify the accuracy of the asymptotic results obtained from the proposed algorithm in the finite system regime. With the complex operation process of large dimension matrix reducing to the deterministic approximations, a lower computational complexity can be obtained compared with other methods.