Biblio

Aiming at the problems of low accuracy and poor effect caused by the lack of data labels in most real network traffic, an optimized density peak clustering based on the improved salp swarm algorithm is proposed for traffic anomaly detection. Through the optimization of cosine decline and chaos strategy, the salp swarm algorithm not only accelerates the convergence speed, but also enhances the search ability. Moreover, we use the improved salp swarm algorithm to adaptively search the best truncation distance of density peak clustering, which avoids the subjectivity and uncertainty of manually selecting the parameters. The experimental results based on NSL-KDD dataset show that the improved salp swarm algorithm achieves faster convergence speed and higher precision, increases the average anomaly detection accuracy of 4.74% and detection rate of 6.14%, and reduces the average false positive rate of 7.38%.

In order to improve the reliability of power supply in adjacent hydropower stations, the auxiliary power systems of the two stations are connected through a contact transformer. The magnetizing inrush current generated by the connecting transformer of a hydropower station has the characteristics of high frequency, strong energy, and multi-coupling. The harm caused by the connecting transformer is huge. In order to prevent misoperation during the closing process of the connecting transformer, this article aims at the problem of setting the switching current of the connecting transformer of the two hydropower stations, and establishes the analysis model of the excitation inrush current with SimPowerSystem software, and carries out the quantitative simulation calculation of the excitation inrush current of the connecting transformer. A setting strategy for overcurrent protection of tie transformers to suppress the excitation inrush current is proposed. Under the conditions of changing switch closing time, generator load, auxiliary transformer load, tie transformer core remanence, the maximum amplitude of the excitation inrush current is comprehensively judged Value, and then achieve the suppression of the excitation inrush current, and accurately determine the protection setting of the switch.

Due to its anonymity, there has been a dramatic growth of underground drug markets hosted in the darknet (e.g., Dream Market and Valhalla). To combat drug trafficking (a.k.a. illicit drug trading) in the cyberspace, there is an urgent need for automatic analysis of participants in darknet markets. However, one of the key challenges is that drug traffickers (i.e., vendors) may maintain multiple accounts across different markets or within the same market. To address this issue, in this paper, we propose and develop an intelligent system named uStyle-uID leveraging both writing and photography styles for drug trafficker identification at the first attempt. At the core of uStyle-uID is an attributed heterogeneous information network (AHIN) which elegantly integrates both writing and photography styles along with the text and photo contents, as well as other supporting attributes (i.e., trafficker and drug information) and various kinds of relations. Built on the constructed AHIN, to efficiently measure the relatedness over nodes (i.e., traffickers) in the constructed AHIN, we propose a new network embedding model Vendor2Vec to learn the low-dimensional representations for the nodes in AHIN, which leverages complementary attribute information attached in the nodes to guide the meta-path based random walk for path instances sampling. After that, we devise a learning model named vIdentifier to classify if a given pair of traffickers are the same individual. Comprehensive experiments on the data collections from four different darknet markets are conducted to validate the effectiveness of uStyle-uID which integrates our proposed method in drug trafficker identification by comparisons with alternative approaches.

In this paper we give improved constructions of several central objects in the literature of randomness extraction and tamper-resilient cryptography. Our main results are: (1) An explicit seeded non-malleable extractor with error � and seed length d=O(logn)+O(log(1/�)loglog(1/�)), that supports min-entropy k=Ω(d) and outputs Ω(k) bits. Combined with the protocol by Dodis and Wichs, this gives a two round privacy amplification protocol with optimal entropy loss in the presence of an active adversary, for all security parameters up to Ω(k/logk), where k is the min-entropy of the shared weak random source. Previously, the best known seeded non-malleable extractors require seed length and min-entropy O(logn)+log(1/�)2O�loglog(1/�), and only give two round privacy amplification protocols with optimal entropy loss for security parameter up to k/2O(�logk). (2) An explicit non-malleable two-source extractor for min entropy k � (1��)n, some constant �\textbackslashtextgreater0, that outputs Ω(k) bits with error 2�Ω(n/logn). We further show that we can efficiently uniformly sample from the pre-image of any output of the extractor. Combined with the connection found by Cheraghchi and Guruswami this gives a non-malleable code in the two-split-state model with relative rate Ω(1/logn). This exponentially improves previous constructions, all of which only achieve rate n�Ω(1). (3) Combined with the techniques by Ben-Aroya et. al, our non-malleable extractors give a two-source extractor for min-entropy O(logn loglogn), which also implies a K-Ramsey graph on N vertices with K=(logN)O(logloglogN). Previously the best known two-source extractor by Ben-Aroya et. al requires min-entropy logn 2O(�logn), which gives a Ramsey graph with K=(logN)2O(�logloglogN). We further show a way to reduce the problem of constructing seeded non-malleable extractors to the problem of constructing non-malleable independent source extractors. Using the non-malleable 10-source extractor with optimal error by Chattopadhyay and Zuckerman, we give a 10-source extractor for min-entropy O(logn). Previously the best known extractor for such min-entropy by Cohen and Schulman requires O(loglogn) sources. Independent of our work, Cohen obtained similar results to (1) and the two-source extractor, except the dependence on � is log(1/�)poly loglog(1/�) and the two-source extractor requires min-entropy logn poly loglogn.

Randomness extractors and error correcting codes are fundamental objects in computer science. Recently, there have been several natural generalizations of these objects, in the context and study of tamper resilient cryptography. These are seeded non-malleable extractors, introduced by Dodis and Wichs; seedless non-malleable extractors, introduced by Cheraghchi and Guruswami; and non-malleable codes, introduced by Dziembowski, Pietrzak and Wichs. Besides being interesting on their own, they also have important applications in cryptography, e.g, privacy amplification with an active adversary, explicit non-malleable codes etc, and often have unexpected connections to their non-tampered analogues. However, the known constructions are far behind their non-tampered counterparts. Indeed, the best known seeded non-malleable extractor requires min-entropy rate at least 0.49; while explicit constructions of non-malleable two-source extractors were not known even if both sources have full min-entropy, and was left as an open problem by Cheraghchi and Guruswami. In this paper we make progress towards solving the above problems and other related generalizations. Our contributions are as follows. (1) We construct an explicit seeded non-malleable extractor for polylogarithmic min-entropy. This dramatically improves all previous results and gives a simpler 2-round privacy amplification protocol with optimal entropy loss, matching the best known result. In fact, we construct more general seeded non-malleable extractors (that can handle multiple adversaries) which were used in the recent construction of explicit two-source extractors for polylogarithmic min-entropy. (2) We construct the first explicit non-malleable two-source extractor for almost full min-entropy thus resolving the open question posed by Cheraghchi and Guruswami. (3) We motivate and initiate the study of two natural generalizations of seedless non-malleable extractors and non-malleable codes, where the sources or the codeword may be tampered many times. By using the connection found by Cheraghchi and Guruswami and providing efficient sampling algorithms, we obtain the first explicit non-malleable codes with tampering degree t, with near optimal rate and error. We call these stronger notions one-many and many-manynon-malleable codes. This provides a stronger information theoretic analogue of a primitive known as continuous non-malleable codes. Our basic technique used in all of our constructions can be seen as inspired, in part, by the techniques previously used to construct cryptographic non-malleable commitments.