For enquiries call:
+1-469-442-0620
HomeBlogData ScienceData Science in Cyber Security: Applications, Importance, Future
The volume of data generated every day is increasing at a surprising rate. Nearly 5 quintillion bytes of data are being created daily. With the rise in data, there has also been a surge in data breaches. Hacking and penetrating a system using various tools has become a significant cause of concern for organizations and individuals worldwide. Sophisticated data science techniques are now widely used by attackers to break into a system. The question is if data science can be used to take charge of the system, can it be used to prevent it from hacking? The answer is yes; with the use of data science in cyber security, it has become easy to predict vulnerability in a system, which in turn prevents the potential risk of breach by taking appropriate measures.
According to the Identity theft Resource Centre (ITRC)’s 2022 report, there have been 817 publicly-reported data compromises in the United States this year alone. This year we may see a loss of $ 4.35 million due to data breaches. Cyber-attackers have drilled their way into various domains such as Healthcare, Finance, retail, etc., thus increasing the target spectrum. Data science and Cybersecurity serve as powerful weapons to dilute these losses. There are various Data Science courses online which can help us to gain a fundamental understanding of this state-of-the-art technology and apply it to strengthen cybersecurity. This article below will cover the in-depth relationship between data science and cyber security.
Data science is a branch of AI which involves studying and analyzing large volumes of data using various tools and techniques. It is used to find unseen patterns and draw meaningful insights from the data. A data scientist’s role involves preparing data for exploration, analysis, and visualization, along with developing models which will fruit outcomes for future inputs
Data Science finds its application in various aspects. Cybersecurity Data science is a discipline primarily focused on protecting systems and data from internal or external threats. The demand for Cybersecurity data scientists has increased tremendously with the rise in challenges related to security. Risk analysis should be one of the primary skills possessed by a data scientist cyber security expert.
There is a lot of data available on the internet, but data in its raw form doesn’t add much value, Hence it becomes very important to study the raw data and note its finding, and further use it to develop sophisticated systems which can predict desirable outcomes.
Applied Data Science has a broad scope of data science. It involves researching and deducing different machine learning algorithms to prevent the inlet of attackers. As the name suggests, applying data science techniques to real-time scenarios is what this discipline corresponds to. They help to design well-thought plans for increasing the security of the system.
Data Science for cyber security has been a game changer in resisting fraudulent activities. Data Science uses Machine Learning tools on past data to predict the likelihood of an intrusion or attack. It involves developing algorithms to deduce patterns from previous attacks and beforehand warning about the reliability of the system in use.
For example, Detecting unauthorized access in an institution. The AI model would grant access to only pre-registered users based on their credentials and analyze the activity of these users so that there is no activity beyond authorization. All these steps are used to prevent any sort of data breach or misuse of information.
Data Science professionals analyze large amounts of data using statistical and programmable skills. They develop solutions to cater to an organization’s needs. It involves interpreting raw data and extracting valuable information from it. This information is further used to interpret the underlying trend and derive a solution using machine learning algorithms.
Data science cyber security professionals are exposed to a large amount of data provided by institutions that thrive on collecting more and more data to leverage data science solutions. Data to be used must be managed. Handling large amounts of data without the help of data scientists is a very big challenge. Taking the predictive way tightens not only the security of the sensitive data but also blocks any sort of penetration.
Cybersecurity in the initial times was associated with Fear and uncertainty. This fear arose from the fact that all the security strategies made by the companies were purely based on assumptions. How the attack will take place, and which area is more prone to attack all these parameters were assumption based.
With data science coming into the picture, it changed the face of the entire Cyber industry. Since cybersecurity is mainly about technology decisions, the predictions from data science have helped a lot in minimizing the chances of making wrong decisions, as most of the judgments are facts based. These data-driven tools have made the jobs of cybersecurity analysts and experts a lot better by increasing their scope of resources, which in a way, helps them to carve out better security improvement plans.
It becomes extremely important that the security team is actively involved with the data science team right from the beginning. This collaboration from the beginning can facilitate both teams in numerous ways, the data science will become aware of the cybersecurity controls while the cyber security team will become well versed with the possible loopholes.
The pandemic has changed our lives in numerous ways. Our lives have moved to online platforms, be it anything purchasing, transferring money, or the shift of companies to online models. A system can be attacked through different mediums, as our usage is just not limited to one aspect. We use a variety of appliances every day, hence furthermore increasing the bandwidth for the attackers to cause data breaches.
Considering all of the above arguments, it is obvious why data science plays an important role in managing cybersecurity risk. This approach helps to reduce the percentage of attacks, it can’t stop the attack, but it helps in notifying the concerned stakeholder about the estimated risk involved. The security team then takes the necessary steps to stop the attack or minimize the damage due to the same. All this can be possible only if we have a risk assessment report by the data science team. In the wake of cybersecurity, data science is of extreme value.
Today, everyone is under the threat of an attack, and these attacks are not limited to just large organizations or governments. Hackers are always looking for the minutest opportunity to get sensitive information. These include personal information, bank account details, etc. Different frauds can be conducted using this information.
Anything which is put on digital platforms gets immortal. There is no way one can wash away their digital activities. With every round of surfing, we are leaving a huge amount of information that helps businesses to grow their trades by making user-oriented choices. Data science becomes fundamental in protecting our digital traces as they can be misused.
For example, My personal information can be used for identity theft. A person can claim my identity and thus create a lot of chaos by accessing private and confidential accounts, thus creating a lot of loss.
Technology is enhancing day by day. Thus, the potential risk of cybercrimes is also increasing. If you are still wondering about data science or cybersecurity which is better? The best possible answer to this question is data science for cyber security. The amount of sensitive data within an organization is increasing day by day, it becomes increasingly important for each one of them to include data science in their risk analysis plans.
There are various ways in which data science help to alleviate the threats, below are some mentioned evidence:
Data is extremely vital to any organization and it is extremely crucial that it is been protected at any cost, data science helps to create impermeable data channels for transferring the data using machine learning algorithms.
With improvements in technology, hackers do not use just one pathway to hack a system. Refined techniques have increased challenges for companies to recognize the paths for penetrating the system. Machine Learning models developed on current and past attack information provide a wholesome understanding to model different attacks. These models then predict the type of attack and the probability of breaking the system.
Prediction doesn’t just only mean detecting True positives. A data science cyber security model should also generate very few False positives, this will help to combat the problem of spam calls. These techniques help to create real-world hypotheses rather than old-school assumptions related to threats and Cyber risk.
Just understanding the type of attack or knowing the probability of it affecting the system is not enough, one must understand a hacker's behavioral pattern. This can serve great advantages as we will be in a position to predict his/her next move or next attack. This behavioral analysis is done by combining different datasets, studying the network logs, and finding correlations between systems help to draw a hacker’s behavioral pattern and take preventive measures accordingly.
Considering the need of the hour, there has been a rise in data science cyber security jobs. A person confused about which is best, data science or cyber security, to pursue as a career must explore their options as a data scientist in cyber security. In order to gain skills in this sector, one can take up any cyber security data science course and become an expert. Pursuing small cyber security data science projects provides practical understanding in addition to theoretical knowledge. Today in the field of cyber security data science salary spectrum varies from $100k- $150k. If you still lack a basic understanding of data science, KnowledgeHut's Data Science courses online can come to the rescue and help in forming the foundation for data science.
Data Science has one of the most promising futures. Hackers are constantly trying to find ways and loopholes to break into a system, with the advancement in approaches, more and more sophisticated attacks are surfacing, in order to prevent this, data science seems like a long-term solution. As already mentioned, the generation of data is not going to stop anytime soon, instead in the coming decades, we will see an exponential rise in the data this will, in turn, result in better-performing data science models as they will have more and more information to connect the dots.
Data Science is not just limited to developing models or algorithms. Analyzing and maintaining the existing data science model is also one of the important aspects involved in this branch. Analysis helps distinguish between what behavior is normal and what can be considered an anomaly. Large enterprises are facing huge losses due to data breaches. They are in dire need of finding ways to reduce these losses. Protecting data using data seems like an encouraging method. Every organization must take steps to strengthen its data science department, such as arranging Bootcamp Data Science workshops, which will help the employees to keep up with the current trends.
Data Science has left a massive impact on cybersecurity in a short span of time. The amount of data received by each organization is increasing day by day. With the increase in the volume of data, the predictive capabilities of a data science model will also increase.
It has become extensively important that the data science team and security team should work collectively at each stage of the process flow. No matter how small or big a company, data is essential to all of them, thus, protecting this data at any cost is key to every organization. The involvement of data science in cyber security has helped to reach a new level of security standards.
Yes, data science is used in cyber security, it's a modern-day technology that works by predicting the potential risk to a system. Data science uses the past history of the attacks based on which they alert the system about forthcoming attacks.
Both fields are in high demand. Considering that almost all companies are moving to digital platforms, professionals skilled in data science are required to manage the ever-increasing data, and people skilled in cyber security are needed to protect this data.
Data science jobs are in high demand. Hence, a data scientist has a high salary as compared to Cybersecurity professional. The average salary of a data scientist is $100,000 USD, while that of a Cybersecurity professional is around $85,000 USD.
No coding is not required for cybersecurity, but it is a great skill to have. It facilitates in gaining deeper knowledge of the system one is trying to protect, which in turn helps in deducing ways to prevent the system from going under attack.
| Name | Date | Fee | Know more |
|---|
