With the advent of Industry 4.0,water treatment systems(WTSs)are recognized as typical industrial cyber-physical systems(iCPSs)that are connected to the open *** information technology(IT)benefits the WTS in the aspec...
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With the advent of Industry 4.0,water treatment systems(WTSs)are recognized as typical industrial cyber-physical systems(iCPSs)that are connected to the open *** information technology(IT)benefits the WTS in the aspects of reliability,efficiency,and ***,the vulnerabilities exposed in the communication and control infrastructure on the cyber side make WTSs prone to cyber *** traditional IT system oriented defense mechanisms cannot be directly applied in safety-critical WTSs because the availability and real-time requirements are of great *** this paper,we propose an entropy-based intrusion detection(EBID)method to thwart cyber attacks against widely used controllers(e.g.,programmable logic controllers)in WTSs to address this *** of the varied WTS operating conditions,there is a high false-positive rate with a static threshold for ***,we propose a dynamic threshold adjustment mechanism to improve the performance of *** validate the performance of the proposed approaches,we built a high-fidelity WTS testbed with more than 50 measurement *** conducted experiments under two attack scenarios with a total of 36attacks,showing that the proposed methods achieved a detection rate of 97.22%and a false alarm rate of 1.67%.
Proprietary(or semi-proprietary)protocols are widely adopted in industrial control systems(ICSs).Inferring protocol format by reverse engineering is important for many network security applications,e.g.,program tests ...
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Proprietary(or semi-proprietary)protocols are widely adopted in industrial control systems(ICSs).Inferring protocol format by reverse engineering is important for many network security applications,e.g.,program tests and intrusion *** protocol reverse engineering methods have been proposed which are considered time-consuming,tedious,and ***,automatical protocol reverse engineering methods have been proposed which are,however,neither effective in handling binary-based ICS protocols based on network traffic analysis nor accurate in extracting protocol fields from protocol *** this paper,we present a framework called the industrial control system protocol reverse engineering framework(ICSPRF)that aims to extract ICS protocol fields with high *** is based on the key insight that an individual field in a message is typically handled in the same execution context,e.g.,basic block(BBL)*** a result,by monitoring program execution,we can collect the tainted data information processed in every BBL group in the execution trace and cluster it to derive the protocol *** evaluate our approach with six open-source ICS protocol *** results show that ICSPRF can identify individual protocol fields with high accuracy(on average a 94.3%match ratio).ICSPRF also has a low coarse-grained and overly fine-grained match *** the same metric,ICSPRF is more accurate than AutoFormat(88.5%for all evaluated protocols and 80.0%for binary-based protocols).
With the wide application of network attached storage (NAS), the security problem is becoming more and more serious, together with the increasingly fierce attacks against NAS devices of different manufacturers. In ord...
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Stance detection, a natural language processing technique, captures user attitudes on controversial social media topics. However, the semantic ambiguity of social texts makes accurate stance determination challenging....
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ISBN:
(数字)9798350368741
ISBN:
(纸本)9798350368758
Stance detection, a natural language processing technique, captures user attitudes on controversial social media topics. However, the semantic ambiguity of social texts makes accurate stance determination challenging. Existing annotated data is often domain-specific, resulting in poor model generalization for unseen targets and cross-domain scenarios. To tackle this challenge, we introduce inference tasks related to stance detection as auxiliary tasks and use a multitask learning approach to improve the model’s understanding of textual semantics. Meanwhile, to alleviate the scarcity of annotated data, we use argumentation corpus with abundant resources as the source domain to train the basic stance detection model. We integrate this model with a large-scale framework to facilitate weakly supervised learning for machine annotation of unlabeled social texts, thereby boosting the model’s adaptability across different targets and domains. Experimental results on four Twitter datasets demonstrate that our method can significantly improve the model’s stance discriminative ability and generalization performance.
The Sunway processor is a unique heterogeneous many-core processor used by Sunway TaihuLight supercomputer. However, developing parallel programs on the Sunway processor is still complex. In this paper, a source-to-so...
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Industrial network boundary protection equipment faces threats from attackers when protecting the industrial control system network. The similarity and static characteristics caused by large-scale and long-term deploy...
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Network device is an important part of cyberspace, and accurate identification of network device is the basis of network management and security analysis. The current identification method based on MAC address is rely...
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Existing IP landmark mining technologies mainly focus on IPv4, and less attention is paid to the association between IPv4 and IPv6. The current IPv6 network has fewer reliable landmarks with limited accuracy, while th...
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Information technology facilitates people’s lives greatly, while it also brings many security issues, such as code plagiarism, software in-fringement, and malicious code. In order to solve the problems, reverse engin...
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Two-dimensional（2D） ferromagnetic materials have been discovered with tunable magnetism and orbital-driven nodal-line features. Controlling the 2D magnetism in exfoliated nanoflakes via electric/magnetic fields enab...
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Two-dimensional（2D） ferromagnetic materials have been discovered with tunable magnetism and orbital-driven nodal-line features. Controlling the 2D magnetism in exfoliated nanoflakes via electric/magnetic fields enables a boosted Curie temperature（TC） or phase transitions. One of the challenges, however, is the realization of high TC2D magnets that are tunable, robust and suitable for large scale fabrication. Here, we report molecular-beam epitaxy growth of wafer-scale Fe3+XGeTe2films with TCabove room temperature. By controlling the Fe composition in Fe3+XGeTe2, a continuously modulated TCin a broad range of 185–320 K has been achieved. This widely tunable TCis attributed to the doped interlayer Fe that provides a 40% enhancement around the optimal composition X = 2. We further fabricated magnetic tunneling junction device arrays that exhibit clear tunneling signals. Our results show an effective and reliable approach, i.e. element doping, to producing robust and tunable ferromagnetism beyond room temperature in a large-scale 2D Fe3+XGeTe2fashion.
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