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Unlock the Power Of Hadoop for Cybersecurity

By Tom Seest

How Can Hadoop Enhance Cybersecurity?

At BestCybersecurityNews, we help entrepreneurs, solopreneurs, young learners, and seniors learn more about cybersecurity.

Faced with increasingly sophisticated cybercriminal attacks, security experts are turning to more advanced analytics. That is where Apache Hadoop and machine learning models come into play.
By combining big data tools, security professionals are better able to detect, identify, and deter threats. This allows them to better protect their organizations’ data as well as sensitive information.

How Can Hadoop Enhance Cybersecurity?

How Can Hadoop Enhance Cybersecurity?

How Does Encryption Help Hadoop in Cybersecurity?

Encryption is a technique that scrambles plain text into an encrypted form that hackers, cybercriminals, and other online snoops cannot decipher. This safeguard helps safeguard sensitive information from online attacks like those that compromise personal data or banking information.
Many businesses rely on encryption to meet compliance regulations, such as the Payment Card Industry Data Security Standard (PCI DSS). This practice ensures data is only accessible by authorized parties and cannot be altered by malicious actors.
Cloudera offers multiple methods for encrypting your data. For instance, you can encrypt data while it is being transmitted to the cloud or on-premises. Furthermore, HDFS data at rest encryption helps keep sensitive information private.
You can also utilize a third-party encryption service to encrypt and decrypt your data. However, make sure the encryption key is stored safely or backed up another way in order to prevent unauthorized access.
One of the most essential steps you can take to enhance data security is enabling encryption. This feature is especially important for companies handling credit cards and other sensitive information.
Another critical element of data security is authentication. This involves verifying that the person sending out a request really makes it. To do this, they use Kerberos, an open network authentication protocol.
This method, originally introduced in the MIT ecosystem, utilizes “tickets” to enable users to identify themselves. It has since spread throughout most Hadoop clusters as a secure way for individuals to authenticate their credentials securely.
For instance, if you want to access your files on the HDFS filesystem, then you must provide valid credentials. This can be accomplished either through Kerberos or by logging into an account specifically created for that purpose on your computer.
The encryption process is a three-step process that involves the client, authentication server, and data transfer server. This ensures that clients communicate with the correct person, and any data sent to a data node will be encrypted by said node. Once verified that the client is who they say they are, the data node will grant access to the file in question.

How Does Encryption Help Hadoop in Cybersecurity?

How Does Encryption Help Hadoop in Cybersecurity?

How Does Impersonation Impact Cybersecurity with Hadoop?

Impersonation attacks have become a serious problem for cybersecurity teams, costing businesses billions of dollars each year in losses. These malicious attacks use social engineering tactics to manipulate employees into providing sensitive information like credit card numbers and passwords.
In the past, attackers used malware or bots to launch attacks; however, today, a new breed of cybercriminals employ impersonation tactics. These bad actors target legitimate users through email and other communication channels and attempt to assume their identity.
This type of attack may be difficult to detect, but companies can protect themselves by providing cyber security awareness training to their employees. This education helps employees recognize fraudulent emails and other types of scams so that they are better able to stay protected.
The attack is typically carried out through an email message that urges the recipient to act quickly and provide certain information. In some cases, the message may even contain links leading to a fake website where malicious software can be installed.
There are various types of impersonation attacks, each targeting a different kind of organization. Hackers may target large global enterprises with valuable assets and data or smaller businesses with weak IT security infrastructure.

Research and Victim Targeting

Hackers employ various techniques to identify potential targets for impersonation attacks. They may consult business directories, news sites, or social media networks in order to learn about organizations that could be vulnerable to an attack.
Once a cybercriminal has identified their target, they usually conduct extensive research into them to gain knowledge about their background and career. Furthermore, cybercriminals use data from social media networks to craft an authentic appearance for their victim.
The final step in an impersonation attack is gaining unauthorized access to the organization’s network or systems. Unauthorized hackers may use password resets, stolen credentials, or other methods to break into the system and steal sensitive information.
To prevent impersonation attacks from gaining unauthorized access, organizations must implement strong encryption techniques and other cybersecurity measures. These protections can shield companies from impersonation attempts as well as other security risks that could damage their brand, reputation, and customers.

How Does Impersonation Impact Cybersecurity with Hadoop?

How Does Impersonation Impact Cybersecurity with Hadoop?

Can Hadoop Protect Against Flood Attacks?

The most prevalent DDoS attack type is a flood attack, which employs various techniques to overwhelm a targeted network. Often using botnets, these DDoS attempts aim to exhaust resources on the target system and prevent legitimate traffic from reaching it.
Flooding attacks come in three main varieties: HTTP flood, SYN flood, and RREQ flood. All these methods involve multiple computers sending an enormous number of requests at once.
HTTP floods occur when criminals use bots that support Trojan Horse malware to generate a large volume of GET and POST requests that appear like normal web page URLs, making them virtually undetectable by traditional rate-based detection tools.
Another type of flooding attack involves sending an excessive number of SYN packets to an infected server, overloading its resources and causing it to respond slowly or not at all to legitimate traffic. This requires less bandwidth than volumetric attacks and is, therefore, less likely to overwhelm networks and servers.
SYN flood attacks, also referred to as half-open attacks, require a size greater than the available backlog on a server’s operating system to cause it to time out. This distinction should be taken seriously since it allows malicious actors to cause denial-of-service at the device level rather than at the network level.
These attacks are much more efficient than traditional volumetric floods. A recent research study by Radware revealed that a botnet infected with Hadoop clusters in the US was capable of generating 5 million DDoS attacks utilizing both UDP and TCP floods as of April 2015.
These techniques are not only dangerous, but they can be costly for organizations. Since DDoS attacks can cause downtime, revenue loss, and reputation damage to companies, they must have an effective DDoS protection strategy covering all layers of the network. As with all DDoS threats, the best solution is applying a mitigation approach that includes protection for all layers of both network and application protection.

Can Hadoop Protect Against Flood Attacks?

Can Hadoop Protect Against Flood Attacks?

How Does Hadoop Help With Authentication?

Authentication is the initial security step that determines whether an individual or system can access information or data. It involves using usernames and passwords for user access to resources without exposing sensitive information to unauthorized individuals. Authentication is vital for any organization as it allows users to gain access to resources without exposing sensitive data to unauthorized individuals.
Authentication typically involves using the credentials of an existing user to log into an online system, application, or database. This process involves comparing those entered by a user with those stored on either their local operating system server or in a database of authorized users. If they match, the system will grant them access to that resource or database.
This process is often employed to restrict who has access to an organization’s network or systems, using a strategy known as least privilege access. This prevents users from gaining full control over everything and only grants them the necessary data or systems for their job tasks.
Authentication not only helps limit access to a system, but it also protects it from malicious actors by preventing credential stuffing, brute force attacks, and password resets. It reduces the surface area for such attacks.
Hadoop’s authentication mechanism utilizes Kerberos to identify users and services, syncing them from Active Directory or other user management systems to a key distribution center (KDC). Each user has its own principal in Kerberos that represents that individual; each service has a distinct principal unique to that particular service, which is stored in a key tab file on each node.
Once a user authenticates with Kerberos, a token is generated and distributed to each worker process. These worker processes then utilize these tokens for authentication on behalf of the user.
Authentication is paramount for Hadoop, as it ensures that only authorized users can access the system. This guards against phishing attacks, credential stuffing, and other forms of fraud. Furthermore, authentication prevents hackers from impersonating legitimate users or servers to gain an advantage in stealing confidential information.

How Does Hadoop Help With Authentication?

How Does Hadoop Help With Authentication?

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