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    Home»Technology»Data Scientist to Escalate Cybersecurity
    Technology

    Data Scientist to Escalate Cybersecurity

    Soft2share.comBy Soft2share.com14 February 20204 Mins Read
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    Cyber-attacks have outrageously become one of the major issues that are on the rise. According to Pew Research, this will pose a threat causing significant loss of property, loss of life, theft and damage at around tens of billions of dollars.

    The Digital Life in 2025 Research Project canvassed on near about 1642 experts on the topic of whether there will be any major harm to the nation’s security and capacity that will be caused by cyber-attack in 2025.

    As a result, 61% of the respondents agreed that there will be huge losses to the nation while 39% disagreed. Those that agreed were from the four themes including – banking and finance, energy, transportation, and defense have been inviting targets for cybercriminals.

    The role of data science in cybersecurity

    During the past decades, organizations have trusted technology for the development of reliable security systems. However, you will need to extensively rely on data science. Doing so will help you analyze data from different sources as well as to detect threats as well.

    Data science professionals and IT professionals will aid in developing algorithms that can strengthen the security systems of any organization.

    Most of the tasks are related to analyzing data and the job role of a data scientist entails for the individual to assess the data, check for their liability, originality, authenticity, and security. For example, if an organization utilizes data science extensively, this will be proven beneficial for the organization since it will be able to boost security by predicting various upcoming risks.

    This could be one of the most reliable approaches a data science professional can take up based on assessing the possible risk an organization might face.

    Possible ways how data scientists can help augment cybersecurity

    It is highly essential to involve data science professionals while making data-security related decisions.

    Due to technology advancements data security processes, have become complicated. This situation thus heightens the need for the organization to take precautions. While organizations are constantly receiving data, processing data, and even storing sensitive data from their customers. Further on, it has driven cybercriminals to acquire such data for criminal activities.

    To solve such cases, data scientists can easily prevent such activities by implementing the below approaches: –

    • Predictive analysis – the significant part about the data science industry is that most professionals working in this domain are aware of the kind of data they handle. Data scientists being the major factor who can solve such risks are being wanted by the industry today. They help in preventing risks based on the data they have previously acquired. Their core responsibilities include analyzing the current data, comparing it with their database, and further identify the current or future risks that might take place in the organization. Types of attacks can be detected using regression models that regularly scans the network for possible risks and threats.
    • Machine learning – machine learning network helps is learning certain behaviors that do not look logical. Data scientists strategically make use of machine learning to detect irregular trends taking place in data reception, data storage, and data sharing. Taking up this process helps them in identifying the loopholes that criminals might use to get through the organization’s data. The organization ensures that they work along with ethical hackers to make sure they seal all the unwanted loopholes through which a criminal might have a chance to get inside the organization.
    • Associate rule learning (ARL) – a method wherein machine learning predicts the methods to protect data. The ARL helps in studying multiple characteristics of the data that already exists and then generates a response whenever there’s a deviation that is detected. Thus, the system automatically keeps itself updated ensuring it keeps up with the momentum of detecting every small kind of anomaly taking place.

    Endnote

    While cybercriminals are present everywhere, organizations must ensure they follow the industry’s best practices to prevent the risk of cyber-attack.

    B2B Leads Database
    data science industry data science professionals
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