Modern DLP has evolved to protect organizations’ data against today’s changing digital landscape. Find out how along with use cases here in our breakdown.
Traditionally, data loss prevention (DLP) solutions relied on rigid rules, evaluating outbound communications and activity for specific signatures and indicators. This legacy approach could be summarized as “building bigger walls” to prevent data breaches and exfiltration. But data is no longer sequestered away – it can’t be. Cloud migrations and remote work have significantly changed how modern DLP technology must operate and organizations must adapt to today’s workforces and structures.
A late-pandemic survey reported:
- 74% of businesses attribute remote work to a rise in cyberattacks
- 80% believe they’re more exposed
- Over 50% of remote employees utilize personal devices
- 71% claim they lack sufficient visibility
Per the World Economic Forum’s Global Risks Report 2022, “growing cyberthreats are outpacing society’s ability to effectively prevent and manage them.” Legacy DLP is no exception, and companies require evolved solutions.
As our co-founder and CPO, Anand Raghavan, has stated, modern DLP focuses on “points of interaction,” such as email and cloud integrations. These points incorporate cloud security brokers and posture management solutions, alongside more behavioral analytics like natural language understanding (NLU).
Modern Email DLP: Learning to be Better
Like all cybersecurity measures, email data loss prevention (DLP) must adapt continuously as malicious actors invent methods for evading newly developed protections and capabilities. Beyond cybercriminals, negligent and inadvertent behavior also lead to data loss.
Both concerns have been exacerbated by new network connections to cloud environments and an overall lengthening of the software supply chain.
Today, most businesses are reliant on some cloud capabilities. However, cloud service providers have their own clients and outsource some of their IT needs to other software-as-a-service (SaaS) providers, leaving few self-contained digital ecosystems remaining.
The connections better resemble ever-expanding spiderwebs that link hundreds or thousands of organizations and digital entities—if not more.
Incorporating machine learning and artificial intelligence (AI) enables modern email DLP to better recognize context, sensitive data, and potential threats or negligence. This is partly achieved by:
- Establishing normal user activity baselines
- Scanning for deviant occurrences
- Enabling thorough monitoring across cloud email platforms, storage environments, databases, and other applications.
Cloud Security Brokers and Posture Management
Cloud security brokers and cloud posture management tools are two essential capabilities for modern DLP solutions.
The former layers between cloud environments and the networks and devices connected to them. The latter identifies potential issues before malicious actors or inadvertent user activity can exploit them to a company’s detriment.
DLP Use Case Examples
In essence, modern DLP solutions live up to the promises and expectations of data security solutions, unlike their legacy counterparts.
With greater adaptability through AI and broader cloud coverage, these solutions implement holistic monitoring well beyond overly restrictive policies and excessive false-positive alerts.
1. Sensitive Data Management and Exfiltration Protection
Sensitive data consists of any information that an organization deems mission-critical or that must be protected according to applicable compliance regulations. Categories include:
- Social security numbers
- Credit card data
- Source code
- Intellectual property
- Proprietary information
Before mass cloud migrations, sensitive data was stored on-premise. To facilitate today’s “perimeter-less” operations, modern DLP solutions extend to cloud-based environments.
This substantially mitigates the chances of sensitive data exfiltration (i.e., unauthorized data transfers) from email accounts or through unsecure cloud storage.
While traditional DLP was often used to identify risks and losses of certain data types (like social security numbers and credit card numbers), newer platforms provide more robust and customizable data protection capabilities via NLU to reduce false positives.
2. Detecting (and Preventing) BEC
Business Email Compromise (BEC) is a scam in which cybercriminals trick executives and employees into sending sensitive data or making payments to fraudulent accounts. According to the FBI’s 2021 Internet Crime Report, their Internet Crime Complaint Center (IC3) received nearly 20,000 BEC complaints, adding up to an estimated $2.4 billion in losses.
By incorporating NLU, modern email DLP solutions identify unauthorized accidental or malicious email data exposure beyond pattern matching known regular expressions (i.e., “regex”). Modern email DLP solutions extend beyond these regex limitations via machine learning to recognize communication patterns and protect sensitive data specific to each organization.
3. Mobile Device Protection
Most remote or hybrid work employees rely on mobile devices linked to cloud environments to perform work tasks, opening new attack vectors for cybercriminals. These devices can be the target of malware attacks (particularly ransomware, which encrypts all stored files and resources) that can spread across and compromise an entire IT environment.
"Bring-your-own-device" (BYOD) policies complicate cybersecurity further. Visibility is often scarce and the odds of a successful attack increase, with the blurred lines between professional and private device usage.
With modern DLP, the stratum provided by cloud security brokers protects both devices and accessed cloud integrations. Incoming attacks are prevented, and users are restricted from saving sensitive information to personal devices or sending to unauthorized parties.
4. Risk Management and Compliance Assurance
Beyond preventing the immediate damages caused by breaches, risk management and periodic assessments are obligatory for many regulatory compliance frameworks.
Examples include:
- HIPAA for healthcare information
- The EU’s GDPR and California’s CCPA for personally identifiable information (PII)
- The PCI DSS for credit card data
With modern data security, compliance becomes easier to maintain. Any unauthorized disclosures or unsecure storage of regulation-covered data is restricted, and user activity is monitored to preserve integrity.
For example, consider HIPAA and its stipulation that any unauthorized use or disclosure of covered health information constitutes a data breach. In addition, modern DLP solutions are able to implement customized policies, understanding the content and context of communications and identifying potential breach incidents, preventing willful or negligent compliance violations.
Modern DLP provides organizations with proactive measures for catching near-violations for sensitive data, helping organizations avoid steep fines and penalties that can cause both financial and reputational harm.
Combat Data Loss With Armorblox Advanced DLP Solution
Modern DLP solutions are critical for any business given the rise in cybercrime facilitated by remote work. Unfortunately, legacy DLP solutions don’t provide the sophisticated data protection capabilities that organizations need to ensure data remains secure in today’s ever-evolving threat landscape.
Armorblox Advanced DLP solution prevents data loss over email communications while reducing false positives. Armorblox intelligently protects the data organizations deem proprietary through the use of NLU.
See how Armorblox can help you reduce false positives, prevent accidental or malicious data exposure, and automate security responses for safer email communication.
