Cyber Security Solutions

Securing Your Digital Frontier: Empowering Cyber Security Solutions

Our Security Solutions are a testament to our commitment to fortified data security across organizations. We bring together an array of robust tools encompassing Mobile Device Management (MDM), Data Loss Prevention (DLP), and User and Entity Behaviour Analytics (UEBA). Our MDM solutions ensure rigorous management and security of an array of mobile devices and end-user computing devices like laptops, desktops, et. by establishing a secure corporate digital infrastructure. The DLP solutions we offer are up-to-date and adept at thwarting any unauthorized exposure of data, solidifying the confidentiality of sensitive information. Our UEBA services adeptly identify anomalous user or entity behaviour, effectively curtailing insider threats and other security risks. We also have a detailed cyber-human intent-indexing solution. Together, our services form an all-encompassing shield around your data, ensuring the integrity and confidentiality of your digital assets while you focus on your core business operations.
Cyber Security Solutions

What is Mobile Device Management

A comprehensive solution used by organizations to manage, secure, and monitor mobile devices such as smartphones, tablets, and laptops.

Why use MDM?

It enables organizations to protect sensitive data by implementing features like device encryption, passcode enforcement, and remote data wipe. MDM also allows for the configuration and management of security settings, such as disabling certain features or restricting app installations.

MDM enables organizations to remotely configure and manage a large number of devices efficiently. It allows IT administrators to remotely set up devices, apply standardized configurations, and push apps, software updates or patches. It helps organizations comply with regulatory requirements and enforce internal policies.

Mobile Device Management

It enables administrators to define and enforce policies related to data access, usage, and sharing e.g., restricting access to certain websites or apps, block data transfer to unauthorized locations, and monitor compliance in real-time.

MDM simplifies troubleshooting and support for mobile devices allowing IT administrators to remotely diagnose device issues, track device location, and even provide remote assistance to users.

It helps with asset management, budgeting, and planning for device upgrades or replacements.

Many organizations implement MDM to separate personal and work-related data on employee-owned devices (BYOD – Bring Your Own Device). MDM enables organizations to create secure containers or profiles on devices, segregating work apps and data from personal ones. This separation ensures privacy for personal data while allowing organizations to protect and manage corporate data.

What is Data Loss Prevention (DLP)

DLP refers to a set of strategies, policies, and technologies designed to prevent sensitive data from being lost, stolen, or unintentionally disclosed. It is an important aspect of information security and privacy management. DLP aims to identify, monitor, and protect sensitive data to prevent its unauthorized access, use, or dissemination.

Why use DLP?

DLP helps prevent data breaches by identifying, monitoring, and protecting sensitive data from unauthorized access or transmission.

Many industries have strict data protection and privacy regulations that organizations must comply with. Failure to comply can result in legal consequences, financial penalties, and damage to reputation. DLP solutions assist in meeting regulatory requirements by implementing appropriate controls and ensuring the security and confidentiality of sensitive data.

Organizations face the risk of data loss or leakage due to insider threats, whether intentional or unintentional.

Data Loss Prevention
Employees may accidentally send sensitive data to the wrong recipients or deliberately attempt to exfiltrate valuable information. DLP helps detect and prevent such incidents by monitoring data flows, enforcing access controls, and identifying suspicious behaviours.

DLP solutions provide automated data discovery and classification capabilities, assisting organizations in locating and categorizing sensitive data across various systems and repositories be helping organisations identify and classify sensitive data accurately, especially as data volumes increase.

Implementing DLP measures may introduce restrictions and controls on data handling and transfer. While necessary for security, these measures can sometimes impact employee productivity and workflows. Balancing security requirements with business needs is a crucial consideration when deploying DLP solutions.

Fine-tuning DLP policies and rules to minimize false positives is important to maintain the system’s effectiveness. DLP systems generate alerts based on policy violations or suspicious activities but, if the system produces an excessive number of false positives or irrelevant alerts, it leads to alert fatigue and hinders effective incident response.

Seamless integration and coordination with existing systems are essential for effective deployment and operation of DLP solutions. Compatibility issues, data mapping, and interoperability with other security tools or data management systems may pose challenges.

End User Education plays a critical role in the overall success of any tool deployment. Employees may be unaware of the importance of data security or may lack knowledge about best practices for handling sensitive information. Educating and raising awareness among users about data protection policies and the role they play in preventing data loss is critical for successful DLP implementation.

What is User and Entity Behaviour Analytics

User and Entity Behaviour Analytics (UEBA) is a security analytics approach that focuses on detecting and analyzing patterns of behaviour exhibited by users and entities within an organization’s network environment. It leverages machine learning, data analysis, and statistical modelling techniques to identify anomalies, detect threats, and mitigate security risks. UEBA primarily monitors and analyses the behaviour of users (employees, contractors, administrators) and entities (such as devices, servers, applications) to establish a baseline of normal behaviour and detect deviations or unusual activities that may indicate security incidents or insider threats. By analysing a wide range of data sources, including log files, network traffic, system events, and user activity logs, UEBA helps identify patterns, trends, and anomalies that traditional security solutions may overlook.

Why use UEBA?

Organizations may be concerned about insider threats posed by employees or trusted entities with privileged access. Detecting malicious or anomalous behaviour from insiders can be challenging using traditional security measures. UEBA helps identify unusual activities, deviations from normal behaviour, and potential insider threats.

By leveraging advanced analytics, machine learning, and behaviour-based algorithms, UEBA identifies subtle indicators of compromise and abnormal patterns that may indicate advanced threats.

User and Entity Behaviour Analytics
It helps detect and respond to potential breaches by monitoring user and entity behaviour, identifying abnormal data access patterns, unauthorized data transfers, or data exfiltration attempts.

UEBA solutions aim to reduce false positives by employing advanced analytics and contextual information to provide more accurate alerts, enabling security teams to focus on genuine threats thus reducing alert fatigue and allows the InfoSec teams to focus on the actual alerts that may get hidden in the vast number of false positives.

UEBA helps organizations meet compliance obligations by providing enhanced threat detection and incident response capabilities by helping organisations meet regulatory compliance requirements, such as those set by data protection laws which often require organizations to demonstrate effective monitoring and detection of security incidents..

Integrating UEBA with existing security infrastructure and systems can be complex. Ensuring compatibility, data ingestion, and integration with security information and event management (SIEM) systems or other security solutions can pose integration challenges.

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FAQs for Security Solutions

How do you manage threats?

Threat management involves identifying potential threats, assessing the damage they could cause, and implementing measures to prevent, eliminate, or minimize the damage. A comprehensive threat management program includes activities such as risk assessment, vulnerability scanning, penetration testing, incident response planning, and continuous monitoring.

What are the four different types of insider attacks?

Four types of insider attacks are:
1. Malicious Insiders: Employees who intentionally harm the organization.
2. Accidental Insiders: Employees who unknowingly cause a security breach, often through careless behaviour.
3. Exploited Insiders: Individuals whose credentials or access rights are misused by external attackers.
4. Third-party Insiders: These can be vendors, suppliers, or partners who have access to your systems and unintentionally or intentionally cause a breach.

What is the insider threat detection process?

The insider threat detection process involves a four-step cycle: Data collection from various sources, analysis of the collected data to look for patterns and anomalies, generating alerts for suspicious activities that need further investigation, and responding appropriately once a threat is identified.

What is the solution to counter insider threats?

The solution to insider threats lies in a combination of technology, people, and processes. Technological solutions like User and Entity Behaviour Analytics (UEBA), Data Loss Prevention (DLP), and Security Information and Event Management (SIEM) can help identify and neutralize threats. Alongside these, fostering a robust cybersecurity culture and implementing stringent access control policies are vital.

The insider threat detection process involves a four-step cycle: Data collection from various sources, analysis of the collected data to look for patterns and anomalies, generating alerts for suspicious activities that need further investigation, and responding appropriately once a threat is identified.

How can companies prevent insider attacks?

Companies can prevent insider attacks by implementing strict access control, continuous monitoring of user activity, conducting regular cybersecurity awareness training and fostering a strong security-centric culture.

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