Current Issue : October-December Volume : 2023 Issue Number : 4 Articles : 5 Articles
Due to the expanding scope of Industry 4.0, the Internet of Things has become an important element of the information age. Cyber security relies heavily on intrusion detection systems for Internet of Things (IoT) devices. In the face of complex network data and diverse intrusion methods, today’s network security environment requires more suitable machine learning methods to meet its security needs, and the current machine learning methods are hardly competent. In part because of network attacks by intruders using cutting-edge techniques and the constrained environment of IoT devices themselves, the most widely used algorithms in recent years include CNN and LSTM, with the former being particularly good at extracting features from the original data space and the latter concentrating more on temporal features of the data. We aim to address the issue of merging spatial and temporal variables in intrusion detection models by introducing a fusion model CNN and C-LSTM in this paper. Fusion features enhanced parallelism in the training process and better results without a very deep network, giving the model a shorter training time, fast convergence, and computational speed for emerging resource-limited network entities. This model is more suitable for anomaly detection tasks in the resource-constrained and time-sensitive big data environment of the Internet of Things. KDDCup-99, a publicly available IBD dataset, was applied in our experiments to demonstrate the model’s validity. In comparison to existing deep learning implementations, our proposed multiclass classification model delivers higher accuracy, precision, and recall....
Existing application-layer distributed denial of service (AL-DDoS) attack detection methods are mainly targeted at specific attacks and cannot effectively detect other types of AL-DDoS attacks. This study presents an application-layer protocol communication model for AL-DDoS attack detection, based on the explicit duration recurrent network (EDRN). The proposed method includes model training and AL-DDoS attack detection. In the AL-DDoS attack detection phase, the output of each observation sequence is updated in real time. The observation sequences are based on application-layer protocol keywords and time intervals between adjacent protocol keywords. Protocol keywords are extracted based on their identification using regular expressions. Experiments are conducted using datasets collected from a real campus network and the CICDDoS2019 dataset. The results of the experiments show that EDRN is superior to several popular recurrent neural networks in accuracy, F1, recall, and loss values. The proposed model achieves an accuracy of 0.996, F1 of 0.992, recall of 0.993, and loss of 0.041 in detecting HTTP DDoS attacks on the CICDDoS2019 dataset. The results further show that our model can effectively detect multiple types of AL-DDoS attacks. In a comparison test, the proposed method outperforms several state-of-the-art approaches....
CXL (Compute Express Link) technology is a relatively new high-speed interconnect standard that was developed to enable faster communication between CPUs, GPUs, and other high-performance components in data center systems. This paper aims to provide a comprehensive technical overview of CXL technology, including its features, advantages, and potential applications in the modern data center environment. CXL Technology Research: CXL technology is based on Peripheral Component Interconnect Express (PCIe) and its extensions. CXL 1.0 is a switch-based interconnect architecture that operates on PCIe Gen5 electrical signaling, achieving data speeds of up to 32 Giga transfers per second (GT/s) per lane. CXL technology provides hardware- based support for cache coherency and memory semantics. CXL technology architecture consists of three main components: 1) CXL Devices: Devices that are compatible with the CXL interface can include processors, accelerators such as Graphics Processing Units (GPUs), and Smart Storage Devices; 2) CXL Switch: The switch enables communication between devices that support CXL. The switch can be external or embedded, allowing for more complex topologies; 3) CXL Memory: CXL memory devices support the CXL protocol for the efficient sharing of System memory....
HTTP cookie covert channel is a covert communication method that encodes malicious information in cookie fields to escape regulatory audits. It is difficult to detect this kind of covert channel according to the cookie content because cookie fields are mainly encoded in custom modes. To effectively identify the HTTP cookie covert channel, this paper proposes a detection method based on the interaction features of the session flow. First, we split the HTTP session flow into fine-grained “interaction process” subflows to comprehensively describe the communication process of the cookie. Then, we compare and analyze the differences between HTTP cookie covert channels and normal cookie communications based on the interaction process, design three types of 7-dimensional features, and build the detection model combined with the machine learning algorithm. Experimental results show that our method can effectively detect HTTP cookie covert channels, and the detection rate can reach 99%. We also prove that our method has advantages in stability and time performance compared with the existing detection methods through experiment and analysis. In addition, our method has certain practicability in the simulation environment with imbalanced data....
The additional diversity gain provided by the relays improves the secrecy capacity of communications system significantly. The multiple hops in the relaying system is an important technique to improve this diversity gain. The development of an analytical mathematical model of ensuring security in multicasting through fading channels incorporating this benefit of multi-hop relaying is still an open problem. Motivated by this issue, this paper considers a secure wireless multicasting scenario employing multi-hop relaying technique over frequency selective Nakagami-m fading channel and develops an analytical mathematical model to ensure the security against multiple eavesdroppers. This mathematical model has been developed based on the closedform analytical expressions of the probability of non-zero secrecy multicast capacity (PNSMC) and the secure outage probability for multicasting (SOPM) to ensure the security in the presence of multiple eavesdroppers. Moreover, the effects of the fading parameter of multicast channel, the number of hops and eavesdropper are investigated. The results show that the security in multicasting through Nakagami-m fading channel with multi-hop relaying system is more sensitive to the number of hops and eavesdroppers. The fading of multicast channel helps to improve the secrecy multicast capacity and is not the enemy of security in multicasting....
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