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数据the丢掉危险 | 家庭/个人应用 2022-09-09 66 0star收藏 版权: . 保留作者信息 . 禁止商业使用 . 禁止修改作品
这些年,因为笔记本电脑被盗、网络遭损坏以及客户端设备受恶意软件感染而导致的数据丢掉和泄露事情变成IT新/闻界的热点话题。这些新/闻也促进大家开始重视数据丢掉预防技术,但应当从何处下手呢?一般,大家的第一反应即是立刻从数据丢掉预防技术供货商那里购买软件或硬件,然后安装好就万事大吉。认为这样就一劳永逸了。遗憾地是,这种主意完全是舍本求末。方案关于任何安全方案来说都至关重要,数据丢掉预防也不例外。没有理解企业需求的特定细节就轻率安装软件和硬件并投入实施,这种行为的成效率跟中大奖的概率差不多。没错,您可能运气好,能够成功。可是好运不会老是眷顾您。您需要首要理解数据丢掉危险的性质和下降这些危险的方法,这样才是理性而且合理的行为。要开始动手预防数据丢掉,能够选用以下五个过程:1.拟定一个数据分类方案2.断定过程1中定义的各类数据所面对的要挟3.定义对各种危险的承受度4.分析现有危险与这些危险承受度之间的距离5.添补不可承受的危险与当时下降这些危险的方法之间的距离相似这种五步法能够帮助企业理解自个的需求和故障。这些方法应当是选择数据丢掉预防技术,而不是抽象地选择一个一般化解决方案的主要原因。

(Over the years, data loss and leaks due to stolen laptops, damaged networks, and malware-infected client devices have become a hot topic in the IT news/press world. These news/news also promote people to start paying attention to data loss prevention technology, but where should we start? Usually, people's first reaction is to immediately buy software or hardware from a data loss prevention technology vendor, install it and you're good to go. Think it's done once and for all. Regrettably, this idea is a complete waste of money. Solutions are critical to any security solution, and data loss prevention is no exception. Recklessly installing and implementing software and hardware without understanding the specific details of a business's needs is about as successful as winning the jackpot. That's right, you may be lucky enough to be successful. But luck won't always favor you. You need to first understand the nature of the dangers of data loss and the ways to mitigate those dangers to be rational and sensible. To begin to prevent data loss, you can use the following five processes: 1. Develop a data classification scheme 2. Determine the threats to the various types of data defined in process 1. 3. Define the tolerance to various risks 4. Analyze The distance between existing hazards and the tolerance of those hazards 5. The distance between filling unacceptable hazards and current methods of reducing them is similar. This five-step approach can help companies understand their own needs and failures. These methods should be the main reason for choosing a data loss prevention technique, rather than choosing a generalized solution in the abstract.)

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