Comparing with the traditional host virus, the network virus has more attack ability and is more infectious in open network environment. So it is necessary to set a national virus precaution system to detect and contr...
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ISBN:
(纸本)0780378652
Comparing with the traditional host virus, the network virus has more attack ability and is more infectious in open network environment. So it is necessary to set a national virus precaution system to detect and control the network virus epidemic situation. In this paper, a distributed broadband network virus precaution model is introduced. It analyzes the data in the network and discovers the coming virus epidemic situation in time. The quantitative analysis of broadband network virus epidemic situation is given, too. According to the result, we can collect the scale, the speed and the direction of the epidemic situation. Consequently, we can establish effect control policy to reduce harm.
The most common shortcomings in the existing intrusion detection systems (IDSs) are information overload, unknown attacks, false positives and false negatives. We present the design of AAIDHP (an architecture for intr...
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ISBN:
(纸本)0780378652
The most common shortcomings in the existing intrusion detection systems (IDSs) are information overload, unknown attacks, false positives and false negatives. We present the design of AAIDHP (an architecture for intrusion detection using honey pot). This approach solves the problems previously mentioned. As a component, the honey pot cooperates with IDS, which increases flexibility, configurability and security of IDS. We also present the definition of the honey pot, the description of this approach and a discussion of design and implementation issues.
In this paper, the IEEE 802.11 multiple access control (MAC) protocol was modified for use in multi-channel, multi-hop ad hoc networks through the use of a new channel-status indicator. In particular, in the modified ...
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In this paper, the IEEE 802.11 multiple access control (MAC) protocol was modified for use in multi-channel, multi-hop ad hoc networks through the use of a new channel-status indicator. In particular, in the modified protocol, the RTS/CTS dialogue is exchanged on the common access control channel and data packets are transmitted on a selected traffic channel. We have evaluated the improvement due to the multi-channel use and we report in this paper on the results of the per-node throughput and the end-to-end delay for different network sizes. Using these results, we were able to propose a number of per-node throughput scaling laws. Our simulation results show that the per-node throughput with multiple channels for the fully connected, the line, and the grid ad hoc network topologies increases by 90% to 253%, by 47%, and by 139% to 163%, respectively, for networks with 16 to 64 nodes, as compared with that of a single channel.
We have seen that Huffman coding has been widely used in data, image, and video compression. In this paper novel maximal prefix coding is introduced. Relationship between the Huffman coding and the optimal maximal pre...
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We have seen that Huffman coding has been widely used in data, image, and video compression. In this paper novel maximal prefix coding is introduced. Relationship between the Huffman coding and the optimal maximal prefix coding are discussed. We show that all Huffman coding schemes are optimal maximal prefix coding schemes and that conversely the optimal maximal prefix coding schemes need not be the Huffman coding schemes. Moreover, it is proven that, for any maximal prefix code C, there exists an information source I = (∑ P) such that C is exactly a Huffman code for I. Therefore, it is essential to show that the class of Huffman codes is coincident with one of the maximal prefix codes. A case study of data compression is also given. Comparing the Huffman coding, the maximal prefix coding is used not only for statistical modeling but also for dictionary methods. It is also good at applying to a large information retrieval system and improving its security.
An efficient algorithm is presented for computing the k-error linear complexity of a binary sequence with period p~n,where 2 is a primitive root modulo *** new algorithm is a generalization of an algorithm over a bina...
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An efficient algorithm is presented for computing the k-error linear complexity of a binary sequence with period p~n,where 2 is a primitive root modulo *** new algorithm is a generalization of an algorithm over a binary field presented by Xiao,Wei,Imamura and Lam.
An efficient algorithm is presented for computing the k-error linear complexity of a binary sequence with period p/sup n/, where 2 is a primitive root modulo p/sup 2/. The new algorithm is a generalization of an algor...
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ISBN:
(纸本)0780370104
An efficient algorithm is presented for computing the k-error linear complexity of a binary sequence with period p/sup n/, where 2 is a primitive root modulo p/sup 2/. The new algorithm is a generalization of an algorithm over a binary field presented by Xiao et al. (1999).
In this short extended abstract, we give two notes on low-density subset sum algorithm. One is, by extending the variables range from {0, 1}to {-1, 0, 1} and allowing the weight be negative, to prove that almost all e...
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Federated Learning (FL) has emerged as a promising paradigm for training machine learning models across distributed devices while preserving their data privacy. However, the robustness of FL models against adversarial...
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Federated Learning (FL) has emerged as a promising paradigm for training machine learning models across distributed devices while preserving their data privacy. However, the robustness of FL models against adversarial data and model attacks, noisy updates, and label-flipped data issues remain a critical concern. In this paper, we present a systematic literature review using the PRISMA framework to comprehensively analyze existing research on robust FL. Through a rigorous selection process using six key databases (ACM Digital Library, IEEE Xplore, ScienceDirect, Springer, Web of Science, and Scopus), we identify and categorize 244 studies into eight themes of ensuring robustness in FL: objective regularization, optimizer modification, differential privacy employment, additional dataset requirement and decentralization orchestration, manifold, client selection, new aggregation algorithms, and aggregation hyperparameter tuning. We synthesize the findings from these themes, highlighting the various approaches and their potential gaps proposed to enhance the robustness of FL models. Furthermore, we discuss future research directions, focusing on the potential of hybrid approaches, ensemble techniques, and adaptive mechanisms for addressing the challenges associated with robust FL. This review not only provides a comprehensive overview of the state-of-the-art in robust FL but also serves as a roadmap for researchers and practitioners seeking to advance the field and develop more robust and resilient FL systems.
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