加拿大IT作业代写 数据和隐私保护

Keywords:加拿大IT作业代写 数据和隐私保护

随着世界范围内数据的不断增长，数据的隐私和保护成为人们关注的焦点。我们看到，数据隐私和保护问题与日俱增。越来越多的数据被收集、收集和生成。因此，如果任何数据被不恰当地掩盖，就会对其隐私造成损害，并泄露给用户。因此，大数据通过其生产者在道德上拥有和使用而进入画面。在今天的情况下，个人访问数据是不现实的，数据可能被删除到足以降低其隐私问题的程度。需要关注的主要事情是通过几个渠道进行的在线沟通，这些渠道特别需要通过硬件和软件渠道来完成。研究人员提出的解决此类隐私问题的建议包括:数据的合法使用、数据的安全使用、确保数据在网络上的安全传输，以及开发上下文感知框架，以管理无线连接和数据隐私的可预测性不足。无论是数据处理和共享的安全，还是一些知识产权、用户的安全、个人隐私、商业秘密和金融信息，都是智慧城市关注的首要问题。智能城市的另一个潜在问题是传感器网络的海量多样化数据，然后是欺诈用户和因恶意数据和合法服务造成的经济损失。Kaisler等人(2013)认为，大量社交媒体组织不受监管的数据积累是对安全的最大威胁，因为大量的数据诱惑着网络攻击者。因此，需要通过严格的法律条款和条件在技术、政府和商业政策以及公共层面实现数据安全(Kaisler et al.， 2013)。为了解决这种安全漏洞，研究人员提出了开发移动云框架等方法来解决数据过度收集的问题，可以作为各种web应用程序的基准。一些数据预处理技术，如数据清洗、数据集成和数据转换和约简，被用来减少数据噪音和不一致性，同时保护数据。
加拿大IT作业代写 数据和隐私保护
With increasing data all around the world the thing that is of concern is the data privacy and protection. We see that the data privacy and protection issues are increasing with each day. More and more data are being collected, harvested and generated. So, if any data that is improperly masked can cause harm to its privacy and get revealed to its users. Thus, the Big data comes into the picture by being ethically owned and used by its producers. Individual access to the data in today’s scenario is made impracticable, data are likely to be de-identified to such an extent that is sufficient to lower down its privacy concerns. Some of the major things of concern are online communication via several channels that particularly needed to be done by hardware and software channels. Suggestions by researchers to deal with such privacy issues is Legal provisioning that is on using the data, use of data for safely ensuring safe travel of data over the networks and development of a context-aware framework for managing the lack of predictability of wireless connectivity and data privacy.Security of data is something of prime importance whether it be the security of data processing and sharing, some intellectual property, the security of users, the personal privacy, commercial secrets and financial information are some of the concerns in smart cities. The vast diversified data by sensor networks and then the fraudulent users and financial losses due to malicious data and legitimate services are other potential issues in the smart cities. According to Kaisler et al. (2013), the unregulated accumulation of data by numerous social media organizations is the biggest threat to security, as large sets of data tempt cyber attackers. Therefore, the security of data needs to be implemented at the technological, government and business policy and public levels through strict legal terms and conditions (Kaisler et al. , 2013). For addressing such security breach, researchers have suggested methods like developing a mobile-Cloud framework to solve the data over-collection problem, which can be set as a benchmark for various web applications. Several Data pre-processing techniques such as data cleaning, data integration and data transformation and reduction has been used to reduce data noise and inconsistencies while securing data.

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