提高網(wǎng)絡(luò)安全，科學(xué)家在努力

重慶 龔 勇

主題語(yǔ)境：科技與信息 篇幅：314詞 建議用時(shí)：7分鐘

1Network-based technologyhasbecome increasingly widespread,and it is now being used by countless individuals,professionals,and businesses worldwide.Despite the technology's advantages,most network-based systems are highly weak to malicious attacks.The consequences of a malicious attack on network-based systems can be extremely severe and devastating.For instance,an attack on a power utility network could leave millions of individuals and offices without electricity,while attacks on social media networks can lead to the disclosure of user information.

2To overcome the weaknesses of network-based systems,computer scientists worldwide have been trying to develop advanced intrusion(入侵)detection systems(IDSs)that could help to identify malicious attacks,increasing a network's safety.In recent years,machine learning(ML)algorithms(算法)have been found to be particularly promising for automatically detecting attacks and intrusions on a network's functioning.

3A key step in the development and training of ML-based IDSs is the selection of data features that a model can rely on or focus on when making predictions.Ideally,by analyzing large datasets,researchers should be able to identify the most suitable features for solving a given task using ML tools,and this is also applicable to intrusion detection.

4Researchers at Canadian University Dubai in the UAE have recently developed a new feature selection method that could enable the development of more effective ML-based IDSs.This method,presented in a paper pre-published on arXiv,was found to perform remarkably well when compared with other commonly employed feature selection techniques.“Our goal is to study feature selection in network traffic data with the aim of detecting potential attacks,”Firuz Kamalov,Sherif Moussa,Rita Zgheib and Omar Mashaal,the researchers who carried out the study,wrote in their paper.“We consider various existing feature selection methods and propose a new feature selection algorithm to identify the most effective features in network traffic data.”

Reading

Check

1.What's the function of the two examples mentioned in paragraph 1?

A.To present the power of network-based systems.

B.To show the weaknesses of network-based systems.

C.To explain the variety of malicious attacks.

D.To illustrate the serious results of malicious attacks.

2.How do IDSs improve a network's safety?

A.By preventing malicious attacks.

B.By recognizing malicious attacks.

C.By imitating malicious attacks.

D.By devastating malicious attacks.

3.What's the key to the development of ML-based IDSs?

A.The settlement of tasks.

B.The analysis of datasets.

C.The prediction of the model.

D.The choosing of data features.

Language

Study

Ⅰ.Useful expressions

for instance例如；比如

rely on依靠；依賴

be able to do能夠做……

compare with與……相比較

Ⅱ.Difficult sentences

1.To overcome the weaknesses of network-based systems,computer scientists worldwide have been trying to develop advanced intrusion detection systems(IDSs)that could help to identify malicious attacks,increasing a network's safety.為了克服基于網(wǎng)絡(luò)的系統(tǒng)的弱點(diǎn)，世界各地的計(jì)算機(jī)科學(xué)家一直在嘗試開發(fā)先進(jìn)的入侵檢測(cè)系統(tǒng)，這類系統(tǒng)可以幫助識(shí)別惡意攻擊，提高網(wǎng)絡(luò)的安全性。

【點(diǎn)石成金】該句的主干為computer scientists worldwide have been trying to develop advanced intrusion detection systems(IDSs)；that could help to identify...safety為that引導(dǎo)的定語(yǔ)從句，修飾先行詞intrusion detection systems，且關(guān)系代詞that在從句中作主語(yǔ)；To overcome...systems為不定式結(jié)構(gòu)作目的狀語(yǔ)。

2.A key step in the development and training of ML-based IDSs is the selection of data features that a model can rely on or focus on when making predictions.基于機(jī)器學(xué)習(xí)的入侵檢測(cè)系統(tǒng)開發(fā)和訓(xùn)練的關(guān)鍵步驟是選擇模型在進(jìn)行預(yù)測(cè)時(shí)可以依賴或關(guān)注的數(shù)據(jù)特征。

【點(diǎn)石成金】該句的主干為A key step is the selection of data features；in the development and training of ML-based IDSs為介詞結(jié)構(gòu)作后置定語(yǔ)，修飾A key step；that a model can rely...focus on為that引導(dǎo)的定語(yǔ)從句，修飾先行詞data features，且關(guān)系代詞that在從句中作賓語(yǔ)；when making predictions為when引導(dǎo)的時(shí)間狀語(yǔ)從句的省略形式，省略了主語(yǔ)a model和be動(dòng)詞is。