MDM (Mobile Device Management)

Mobile device management (MDM) is a proven methodology and toolset used to provide a workforce mobile productivity tools and applications while keeping corporate data secure.

Mobile device management (MDM) is the administration of mobile devices, such as smartphones, tablet computers, and laptops. MDM is usually implemented with the use of a third-party product that has management features for particular vendors of mobile devices. Though closely related to Enterprise Mobility Management and Unified Endpoint Management, MDM differs slightly from both: unlike MDM, EMM includes mobile information management, BYOD, mobile application management and mobile content management, whereas UEM provides device management for endpoints like desktops, printers, IoT devices, and wearables as well.

What is mobile device management (MDM)? | IBM

Mobile device management - Wikipedia

Tools

• The Modern Apple MDM Built by Apple IT | Kandji
  • Apple MDM Solutions: MDM for Mac, iPhone, iPad | Kandji
• Unified Endpoint Management solution | Cloud-based UEM from Hexnode
  • Unified Device Management | Hexnode UEM
• Jumpcloud
• Jamf Apple Device Management. Mac iPad iPhone TV Apple MDM
• Zero Trust Network Access (ZTNA) | Zero Trust | Cloudflare

Open Source Tools

1. Scalefusion MDM
2. Flyve MDM (discontinued for active development)
3. OneMDM
4. Miradore
5. ManageEngine
6. Relution
7. Headwind MDM - Open Source Platform to Manage Android Devices
8. WipeDrive

Trending Open Source Mobile Device Management (MDM) Tools

5 Efficient MDM Solutions for You- Dr.Fone

Data Loss Prevention (DLP)

Data loss prevention is a security solution that identifies and helps prevent unsafe or inappropriate sharing, transfer, or use of sensitive data. It can help your organization monitor and protect sensitive information across on-premises systems, cloud-based locations, and endpoint devices. It also helps you achieve compliance with regulations such as the Health Insurance Portability and Accountability Act (HIPAA) and General Data Protection Regulation (GDPR).

When it comes to security data, following information protection and governance best practices is critical Information protection places controls (for example, encryption) around sensitive data, while information governance determines its lifecycle (how long an organization retains the data). Together, they help your organization understand, safeguard, and govern its data.

Know your data. Understand your data landscape; identify and classify important data across your hybrid environment.

Protect your data. Apply protective actions like encryption, access restrictions, and visual markings.

Prevent data loss. Help people in your organization to avoid accidental oversharing of sensitive information.

Govern your data. Retain, delete, and store data and records in a compliant manner.

How does DLP work?

Data loss prevention is a combination of people, processes, and technology that works to detect and prevent the leakage of sensitive data. A DLP solution uses things like antivirus software, AI, and machine learning to detect suspicious activities by comparing content to your organization’s DLP policy, which defines how your organization labels, shares, and protects data without exposing it to unauthorized users.

Types of data threats

• Cyberattack
• Malware
• Insider risks
• Unintentional exposure
• Phishing
• Ransomware

Benefits of a DLP solution

• Classify and monitor sensitive data
• Detect and block suspicious activity
• Automate data classification
• Maintain regulatory compliance
• Monitor data access and usage
• Improve visibility and control

DLP best practices

• Identify and classify sensitive data. To protect your data, you need to know what you’ve got. Use your DLP policy to identify sensitive data and label it accordingly.
• Use data encryption. Encrypt data that is at rest or in transit so unauthorized users won’t be able to view file content even if they gain access to its location.
• Secure your systems. A network is only as secure as its weakest entry point. Limit access to employees who need it to do their jobs.
• Implement DLP in phases. Know your business priorities and establish a pilot test. Allow your organization to grow into the solution and all it has to offer.
• Implement a patch management strategy. Test all patches for your infrastructure to ensure there are no vulnerabilities being introduced into your organization.
• Allocate roles. Establish roles and responsibilities to clarify who is accountable for data security.
• Automate. Manual DLP processes are limited in scope and can’t scale to meet the future needs of your organization.
• Use anomaly detection. Machine learning and behavioral analytics can be used to identify abnormal behavior that could result in a data leak.
• Educate stakeholders. A DLP policy isn’t enough to prevent intentional or accidental incidents; stakeholders and users must know their role in protecting your organization’s data.
• Establish metrics. Tracking metrics—like the number of incidents and time-to-response—will help determine the effectiveness of your DLP strategy.

What is data loss prevention (DLP)? | Microsoft Security

What is DLP (Data Loss Prevention)? | Fortinet

What is Data Loss Prevention (DLP) | Data Leakage Mitigation | Imperva

What Is Data Loss Prevention (DLP)? [Guide] - CrowdStrike