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【国外新品】人工智能和机器学习(ML)
2020/6/22 16:11:00   中国安防行业网      关键字:国外新品 人工智能 机器学习      浏览量:
  AI and machine learning (ML)
  AI and machine learning (ML) are industry buzzwords that have been used extensively over the past five years or so. Like so many examples of IT jargon they have tended to add more confusion than anything, particularly for the C-suite, as to how it is being applied effectively in the context of information security. However, over the past two years there appears to have been a growing appetite for companies in adopting these innovative tech, says a cyber firm.
  A Capgemini report from 2019 threw some light on this emerging trend, including the fact that 61 percent of enterprises say that they cannot detect breach attempts today without the use of AI technologies, and that 48 percent of companies planned to increase their AI in cybersecurity by an average of 29 percent in 2020.
  It is understandable that companies are looking for new innovative ways to combat the cyber threat. Cybercriminals are using increasingly sophisticated tools and methods to gain access to the valuable data that so many companies now hold. Those companies who are not proactive and sit behind legacy systems in the hope that they are protected, are increasingly finding that they are not.
  The cost of data breaches are also increasing, with the global average cost according to IBM around $3.92m. Add to this cost of regulatory fines (or potential fines), reputational damage and more recently customers suing companies who have experienced data breaches (easyJet is facing a $22billion class action lawsuit over its 2020 data breach). Therefore, the need to find ways to address the threat is crucial and companies are turning to AI. The Capgemini report also saw 69 per cent of enterprises believe that AI will be necessary to respond to cyberattacks.
  One of the stats from the Capgemini saw that 51 percent of executives are making extensive AI provisions for cyber threat detection, outpacing prediction and response by a wide margin. So, whilst many firms see the potential in AI and machine learning in helping to detect threats, most are not using it to its full potential.
  Darren Craig, founder at RiskXchange says: ML models if used to their full extent can determine if a company is at risk of a breach based on an analysis of the company抯 external facing digital footprint. Companies can therefore, be proactive in their defence, rather than passively waiting for AI to identify a possible threat.
  揥ith a sufficient amount of quality data available, ML techniques can easily outperform traditional, manual static based security controls based assessment. Adding risk scoring analytics to a prevention strategy built on AI/ML learning is a great way to raise the bar in securing today抯 corporate networks.
  揑t is promising that companies seem to be starting to embrace AI/ML for cybersecurity, but in order to be more fully secure, companies need to take a proactive approach, using the technology抯 full potential. In doing so companies are in a much stronger position to protect themselves from an increasingly sophisticated criminal, and the huge associated cost.

  人工智能和机器学习(ML)
  人工智能和机器学习(ML)是在过去五年左右的时间里使用最广泛的行业流行语之一。像许多IT术语的一样,对于在信息安全环境中如何有效地应用它,尤其是对于高层主管而言。然而,一家网络公司表示,在过去两年中,采用这些创新技术的公司的需求似乎越来越大。
  一个来自2019年的Capgemini报告揭示了这一新兴趋势的亮点。其中包括,即61%的企业表示,如果不使用AI技术,他们今天就无法发现违规企图。2020年48%的公司计划通过计划提高他们的AI网络安全水平到29%的平均水平。
  可以理解的是,企业正在寻找新的创新方法来应对网络威胁。网络罪犯正在使用越来越复杂的工具和方法来访问许多公司现在拥有的有价值的数据。那些守旧,不积极地的躲在旧系统后面寄希望能受到保护的公司发现那些保护渐渐失去了作用。
  数据泄露的成本也在增加,根据IBM的数据,全球平均损失约为392万美元。再加上监管罚款(或潜在罚款),声誉损失以及最近客户起诉经其历数据泄露的公司的费用(2020年的数据泄露案,easyJet面临着220亿美元的集体诉讼)。因此,寻找解决威胁的方法至关重要,并且越来越多的公司正在转向AI。从Capgemini报告还看到,有69%的企业认为AI是应对网络攻击所必需的。
  Capgemini的一项统计数据显示,有51%的高管们规定了广泛的AI条款用于网络安全检测,而这种反响却大大超越了他们的预期。因此,尽管许多公司看到了AI和机器学习在检测威胁方面的潜力,但大多数公司并未充分利用它。
  RiskXchange创始人Darren Craig 表示:“如果充分利用ML,则可以根据对公司外部数字足迹的分析来确定公司是否有遭受违约的风险。因此,公司可以进行主动防御,而不是被动地等待AI识别可能的威胁。
  “有了足够可用的高质量数据,机器学习技术就可以轻松胜过传统的基于手动静态安全控制的评估。将风险评分分析添加到基于AI / ML学习的预防策略中,这是提高保护当今企业网络安全性的绝佳方法。
  “值得一提的是,企业似乎已开始采用AI / ML来保护网络安全,但是要想更加充分地保护其安全,企业就需要采取更加积极主动的方法,并充分利用该技术的潜力。这样一来,企业就可以保护自己免受日益复杂的犯罪分子和相关巨额费用的侵害。”
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