Proactive Efforts to Decrease Risk and Improve Security

Proactive Efforts to Decrease Risk and Improve Security

Cyber security is one of the biggest challenges in the current society due to the

sophisticated tools that cybercriminals use daily to commit crimes. Organizations and firms

ought to implement both proactive and reactive measures to limit the spread of this vice and

protect themselves from the risk that is caused by cyber-attacks. Several proactive efforts can be

used to decrease risk and improve security, including creating employee awareness and training

them, MFA, regular software patching and updates, encryption and network segmentation.

Employee training and awareness are among the best proactive measures that firms

converting human-readable text to cipher text. Encryption enhances security by converting

sensitive data like passwords to cipher text. Many companies have employed encryption to

protect their sensitive data and information being shared online. Network segmentation is also

one of the best proactive methods to secure a network from cyber security-related attacks.

Network segmentation entails dividing the network into smaller segments to reduce the risk of

data breaches that could compromise the whole network. Regular updates are also key in

ensuring that systems are up to date and thus minimizing cyber-attack vulnerabilities.

Reactive Threats Detection Efforts

Reactive threat detection efforts are measures employed to detect and respond to cyber

attacks immediately after they have occurred. Their main objective is to contain and identify

security breaches, reduce the damages caused by cyber-attacks and recover them as quickly as

possible. Examples of reactive threat detection efforts include IDS, SIEM, EDR, vulnerability

scanning and IRP (Wong et al., 2022). Vulnerability scanning entails scanning applications and

systems for security and vulnerability weaknesses. A tool like Nmap is used to scan the

vulnerability and thus create awareness of the gaps that attackers can use to perform cyber

attacks and thus give recommendations that can be used to remediate the attacks.

plan with steps to respond to a security incident. IRP consists of steps included in detection,

investigation, containment and recovery. A properly defined IRP enables organizations to

respond effectively and quickly to security incidents. Proper use of Security Information and

Event Management is also an example of a reactive technique used in cyber security. SIEM is a

centralized system that analyzes and aggregates security events from sources like applications,

servers and network devices. SIEM plays an important role in identifying anomalies and patterns

in event data and thus enables the security team to respond quickly to security incidents. IDS

plays a significant role in monitoring systems and network traffic, thus detecting intrusion and

Several ways are used to analyze intrusion, including identifying the type of intrusion, the

timeline of attacks, scope, impact, and the cause of attacks. Identifying the type of attack, be it

phishing, ransomware, or malware, plays an important role in enabling one to understand the

scope of the attack and the data and information that are compromised. The timeline of the attack

is also used in analyzing intrusion. Timeline entails the time that an attack has occurred and the

time it has lasted. This helps identify and determine data and information that could have been

affected and how the attack was performed. The main cause of an attack also plays an important

such as tarnishing reputation and financial loss, determines how urgent response efforts need to

be employed. The extent of damages caused by the intrusion, like systems downtime, corrupted

files and compromise, can be used in the remediation efforts.

Summary Of Other Aspects of Intrusion Detection and Analysis That Were Not Covered

Several aspects are also used in intrusion detection and analysis, including threat

intelligence, machine learning, behavioural analysis, incident management and Extended

Detection and Response. Machine learning is one of the best intrusion detection and analysis

techniques. They can analyze big data and identify patterns and anomalies. Machine learning

improves the speed and accuracy of IDR. Behaviour analysis is another key aspect used in

to identify irregular patterns and anomalies. The monitoring includes the assessment of unusual

network traffic and access to file patterns.

Reference

Park, S. H., Yun, S. W., Jeon, S. E., Park, N. E., Shim, H. Y., Lee, Y. R., ... & Lee, I. G. (2022).