What is Data Security?

data security

Written by Ayesha

Data security implies keeping digital information safe from corruption, damage, and malicious parties. Data security procedures, tools, and policies focus on enhancing data protection, privacy, and safety. A robust data security management enables digital data protection against cyberattacks while also reducing the risk of insider threats and human error, which are major causes of data breaches and other similar threats.

Handling Data Safely

Whether it be protecting data due to legal regulations, personal information protections, or organizational resource requirements, handling data safely is a great practice to ensure privacy, confidentiality, and accessibility. Data security is crucial to preventing the reputational risk that accompanies a data breach. A cyberattack or loss of data can result in the loss of an organization’s reputation, an individual’s personal identity, or sensitive research data. 

Unauthorized access, cyber-attacks, and corruption and modification of data are among the major threats to consider when handling data, as these can be difficult to defend against without proper measures. Causing catastrophic damage to the data.

Neglecting safe data handling measures can also have major financial impacts in loss of personal credentials, user data, and lawsuits and fines that result from poor data handling. When handling data safely, there are many factors that come into play that must actively be considered to improve data security posture.

Threats

When handling data of any kind, whether it is corporate or personal, many threats must be considered to devise proper protective actions against them. Some threats that put digital data at risk are:

Accidental Data Exposure

Negligence in data handling can be a major threat to data security. Personal negligence, such as sharing devices that contain your sensitive data, accidentally exposing the data to third parties, losing data devices to theft, or due to mishandling, can all result in data corruption, loss, or theft. In a corporate or research environment, team members and employees who have access to the data can be the major source of causing this exposure and compromising sensitive information. 

Phishing Attacks

These manipulative attacks are caused by malicious third parties to trick authorized individuals with access to the data into providing the security or access details to them. These cybercriminals contact the victim as a trusted source to prevent raising any suspicion and deceiving them into sharing their private information or allowing them access to protected resources via malicious links or files sent to their inbox. 

Insider Threats

Insider threats result from people that have authorized access to the data, which intentionally or intentionally make it accessible to malicious third parties. Such authorized users may be unaware that their credentials have been compromised and are being used by malicious attackers to access sensitive data. On the other hand, these users may be intentionally trying to damage or steal the data for personal gain, just causing threats to the data due to negligence of proper security measures.

Cyber Threats

Cyber threats are focused attacks performed by malicious third parties on databases to gain access to the stored data. These utilize vulnerabilities in networks, codes, or applications found in the system to infiltrate the database. Some of the major cyber threats include:

  • Malware: Malicious software attackers use it to infect computers and corporate networks to cause data security threats like theft, damage, and extortion.
  • Ransomware: Ransomware attackers use variabilities to infiltrate systems and encrypt the data on them. These are caused to demand ransom for data safety.
  • SQLi: SQL injection attackers gain access to databases by injecting malicious code into the system to get third parties administrative access and steal or damage the data.

Security Measures

When handling data safely, proper measures must be taken to ensure safety from a wide range of threats posed to the sensitive information at hand. These measures include:

Data Access Controls and Management

Applying proper access controls and management frameworks enables proper authorization and authentication of all users that access data. Each user is allowed to access specific parts of the data while restricted from other unauthorized parts. Proper management of identities using techniques like multi-factor authentication and access privileges allow control over sensitive information within the database.

Data Encryption

Data encryption codes the data before storing it to make it unreadable even if a malicious user tries to access it. 

Data Loss Prevention

Data loss prevention enforces data protection policies to detect and notify if a potential data breach is taking place. It detects exfiltration and unauthorized sharing of information outside the organization.

Cloud Security

Data handling through the cloud means using cloud services to protect and store all sensitive data giving access to only authorized users who can access the data from anywhere via a network connection. 

Email Security

Email security prevents malicious attacks such as phishing attacks caused by malicious attachments or links. These ensure end-to-end email encryption and inbox controls to ensure secure data handling,

Handling Data Safely for Programmers

Using secure programming practices to ensure that the source code of an application is clear of any vulnerabilities is crucial to ensure that these are not exploited by malicious third parties to gain access to the system. Some of these practices are:

Authenticate Input

Authentication of user input is a great safety measure to secure data. Validate all inputs from untrusted data sources to remove software vulnerabilities.

Utilize Safety and Analysis Tools

Using the best compilers to compile the source code is also a great way to highlight loopholes or errors in the program. Furthermore, static analysis or dynamic analysis tools can also help in finding code errors and safety vulnerabilities. 

Security Policies and Access Control 

Dividing the system into subsystems based on privileges, access controls, and restrictions can help in keeping unauthorized users from accessing sensitive data. Denying access until conditions are met and providing users with the least amount of privilege necessary to undertake their tasks are great security policies to implement into your system. 

Server-side input validation is a good security measure and can be implemented in Microsoft ASP.NET using C#:

namespace ServerValidation.Models

{  

    public class User  

    {  

        public string Name { get; set; }  

        public string Email { get; set; }          

    }  

}

 

Validating Name and Email, and displaying error message:

using System.Text.RegularExpressions;  

using System.Web.Mvc;   

namespace ServerValidation.Controllers  

{  

    public class UserController : Controller  

    {          

        public ActionResult Index()  

        {              

            return View();  

        }  

        [HttpPost]  

        public ActionResult Index(ServerValidation.Models.User model)  

        {  

            if (string.IsNullOrEmpty(model.Name))  

            {  

                ModelState.AddModelError("Name", "Name is required");  

            }  

            if (!string.IsNullOrEmpty(model.Email))  

            {  

                string emailRegex = @"^([a-zA-Z0-9_\-\.]+)@((\[[0-9]{1,3}" +  

                                         @"\.[0-9]{1,3}\.[0-9]{1,3}\.)|(([a-zA-Z0-9\-]+\" +  

                                            @".)+))([a-zA-Z]{2,4}|[0-9]{1,3})(\]?)$";  

                Regex re = new Regex(emailRegex);  

                if (!re.IsMatch(model.Email))  

                {  

                    ModelState.AddModelError("Email", "Email is not valid");  

                }  

            }  

            else  

            {  

                ModelState.AddModelError("Email", "Email is required");  

            }  

            if (ModelState.IsValid)  

            {  

                ViewBag.Name = model.Name;  

                ViewBag.Email = model.Email;  

            }  

            return View(model);  

        }  

    }  

}

 

Using “index.cshtml” to support user input:

 

@model ServerValidation.Models.User  

@{  

    ViewBag.Title = "Index";  

}   

@using (Html.BeginForm()) {   

    if (@ViewData.ModelState.IsValid)  

    {  

        if(@ViewBag.Name != null)  

        {  

            <b>  

                Name : @ViewBag.Name<br />  

                Email : @ViewBag.Email  

            </b>  

        }  

    }        

    <fieldset>  

        <legend>User</legend>   

        <div class="editor-label">  

            @Html.LabelFor(model => model.Name)  

        </div>  

        <div class="editor-field">  

            @Html.EditorFor(model => model.Name)    

            @if(!ViewData.ModelState.IsValid)   

            {          

                <span class="field-validation-error">@ViewData.ModelState["Name"].Errors[0].ErrorMessage</span>   

            }               

        </div>   

        <div class="editor-label">  

            @Html.LabelFor(model => model.Email)  

        </div>  

        <div class="editor-field">  

            @Html.EditorFor(model => model.Email)   

            @if (!ViewData.ModelState.IsValid)   

            {          

                 <span class="field-validation-error">@ViewData.ModelState["Email"].Errors[0].ErrorMessage</span>   

            }            

        </div>  

        <p>  

            <input type="submit" value="Create" />  

        </p>  

    </fieldset> 

 

Analyze Data Sent and Received From Other Systems

SQL injection and other such attacks utilize this data exchange aspect to make the system process malicious code that creates vulnerabilities. Creating a subsystem to analyze the context under which data is requested or received to ensure system and data safety.

It is necessary to ensure that all valid data is accepted and does not include dangerous code. A whitelisting approach can help in achieving this: 

Instead of a direct approach such as:

sprintf(buffer, "/bin/mail %s < /tmp/email", addr);

system(buffer);

 

It is better to validate the data:

 

static char ok_chars[] = "abcdefghijklmnopqrstuvwxyz"

                         "ABCDEFGHIJKLMNOPQRSTUVWXYZ"

                         "1234567890_-.@";

char user_data[] = "Bad char 1:} Bad char 2:{";

char *cp = user_data; /* Cursor into string */

const char *end = user_data + strlen( user_data);

for (cp += strspn(cp, ok_chars); cp != end; cp += strspn(cp, ok_chars)) {

  *cp = '_';

}

Conclusion

In order to help in developing threat mitigation strategies and ensuring that data is handled securely, adding multiple layers of security to your code to prevent security flaws and vulnerabilities, combining secure coding practices with secure runtime environments, performing penetration testing, source code audits and threat modeling practices are steps that need to be taken. Visit our other articles on safe programming and software development to help you go above and beyond to secure your digital design processes.

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