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Data Security Knowledge Base

Data Forensics

What is Data Forensics?

Data forensics, also know as computer forensics, refers to the study or investigation of digital data and how it is created and used. Data forensics is a broad term, as data forensics encompasses identifying, preserving, recovering, analyzing, and presenting attributes of digital information. In regards to data recovery, data forensics can be conducted on mobile devices, computers, servers, and any other storage device. Data forensics can also be used in instances involving the tracking of phone calls, texts, or emails traveling through a network. Digital forensics professionals may use decryption, reverse engineering, advanced system searches, and other high-level analysis in their data forensics process.

Two types of data are typically collected in data forensics. This first type of data collected in data forensics is called persistent data. Persistent data is data that is permanently stored on a drive, making it easier to find. The other type of data collected in data forensics is called volatile data. Volatile data is impermanent elusive data, which makes this type of data more difficult to recover and analyze.

The History of Data Forensics

As personal computers became increasingly accessible throughout the 1980s and cybercrime emerged as an issue, data forensics was developed as a way to recover and investigate digital evidence to be used in court. Today, investigators use data forensics for crimes including fraud, espionage, cyberstalking, data theft, violent crimes, and more. Computer forensic evidence is held to the same standards as physical evidence in court. This means that data forensics must produce evidence that is authentic, admissible, and reliably obtained.

The Data Forensics Process

The data forensics process has 4 stages: acquisition, examination, analysis, and reporting. There are also various techniques used in data forensic investigations. One of these techniques is cross-drive analysis, which links information discovered on multiple hard drives. A second technique used in data forensic investigations is called live analysis. Live analysis examines computers’ operating systems using custom forensics to extract evidence in real time. Recovery of deleted files is a third technique common to data forensic investigations.

Data Forensics Tools and Software

There are many different types of data forensics software available that provide their own data forensics tools for recovering or extracting deleted data. There are also many open source and commercial data forensics tools for data forensic investigations. Security software such as endpoint detection and response and data loss prevention software typically provide monitoring and logging tools for data forensics as part of a broader data security solution.

Challenges Facing Data Forensics

There are technical, legal, and administrative challenges facing data forensics. Technical factors impacting data forensics include difficulty with encryption, consumption of device storage space, and anti-forensics methods. Anti-forensics refers to efforts to circumvent data forensics tools, whether by process or software.

Legal challenges can also arise in data forensics and can confuse or mislead an investigation. An example of this would be attribution issues stemming from a malicious program such as a trojan. Trojans are malware that disguise themselves as a harmless file or application. Since trojans and other malware are capable of executing malicious activities without the user’s knowledge, it can be difficult to pinpoint whether cybercrimes were deliberately committed by a user or if they were executed by malware.

From an administrative standpoint, the main challenge facing data forensics involves accepted standards and governance of data forensic practices. Although there are a wide variety of accepted standards for data forensics, there is a lack of standardization. In regards to data forensics governance, there is currently no regulatory body that overlooks data forensic professionals to ensure they are competent and qualified.

Data Security Knowledge Base

Data Protection 101

Learn more about the fundamentals of data and information security in our Data Protection 101 Series

Welcome to Data Protection 101, our series on the fundamentals of data security. In this series you will find information on a wide array of topics that any security professional should be familiar with. This series is created to expand your knowledge, providing you with definitions, background information, examples, and best practices for the most important subject matter regarding data security.

Here are the links to all of the topics we have covered in this series:

Data Security Knowledge Base

Incident Response

What is Incident Response?

Incident response can be defined as a method for responding to a security breach or attack. The intended outcome of incident response is to minimize damage while also reducing recovery time and costs. An incident response plan is a step-by-step process that is carried out after a security incident occurs. As a result, an incident response plan must specifically define the terms of what the organization considers to be a security incident – this definition will vary from organization to organization. Examples of security incidents that can require incident response include attempts at gaining unauthorized access to data or systems, disruption or denial of service attacks, malware infections, and unauthorized use of systems to manipulate data. In addition, unauthorized changes to a system’s hardware, firmware, or software can also be considered a security incident requiring response.


What is a Computer Security Incident Response Team (CSIRT)?

Computer security incident response teams are groups that analyze reports of security breaches and manage the incident response process. Computer security incident response teams can be formally established or can be put together when an incident arises. Of course, the more organized an incident response team is prior to an incident, the more efficient their response can be; the same goes for incident response plans themselves.


There are many different types of computer security incident response teams. Internal computer security incident response teams are composed to serve a parent organization such as the government or a corporation. National computer security incident response teams provide incident response services to an entire country. External computer security incident response teams provide paid incident response services when needed. Other types of computer security incident response teams include coordination centers, analysis centers, vendor teams, and incident response providers. Aside from computer security incident response teams, there are also various cyber incident response and data incident response software/tools available for organizations to use.


Benefits of Incident Response Plans

An effective incident response plan improves the decision making of the organization. Having standardized procedures for incident response allows for decisions to be made quickly and effectively, which is critical following an attack or compromise. Effective incident response plans also improve internal and external coordination. Internal coordination is improved because incident response planning aligns all of an organization’s business functions around critical security issues. Externally, incident response plans help to maintain relationships with third parties, which can be critical to the organization’s success in addressing a security incident.


Incident response plans establish distinct roles and responsibilities across the organization. This makes the organization’s internal response activities flow much more fluently and efficiently. Moreover, incident response plans enable organizations to act immediately after an incident is noticed and limit the damage from incidents that occur.


Shortcomings of Incident Response Plans

Although incident response plans bring the benefits of strategic and coordinated threat response, if not properly designed or implemented, incident response plans can be ineffective. Additionally, incident response plans that are outdated or too generic will not serve companies well when a security incident occurs. Another shortfall organizations can face in incident response planning is when a plan is developed following a siloed approach – that is, the incident response plan is too concentrated within a small portion of the company, leaving other business units in the dark. Exclusive incident response plans may be an option to defend against highly targeted attacks, but they also leave organizations susceptible to incidents that affect other business units. Finally, incident response plans can easily become ineffective when organizations fail to allocate human resources effectively to align stakeholders with their appropriate roles in security incident response.


Ultimately, in order to be effective, incident response must be well-planned and updated continuously to address new threats and risks facing the organization as well as new laws regarding cyber security. When developed and executed properly, cyber security incident response brings countless benefits to the victim organization – including damage control, reduced mitigation costs, improved response times, and minimized brand damage.

Data Security Knowledge Base

Intrusion Prevention System

What is an Intrusion Prevention System?

An intrusion prevention system (IPS) is a tool that is used to sniff out malicious activity occurring over a network and/or system. Intrusion prevention systems can also be referred to as intrusion detection and prevention systems (IDPS). Intrusion prevention systems function by finding malicious activity, recording and reporting information about the malicious activity, and trying to block/stop the activity from occurring.

Intrusion prevention systems expand on the capabilities of intrusion detection systems (IDS), which serve the fundamental purpose of monitoring network and system traffic. What makes intrusion prevention systems more advanced than intrusion detection systems is that IPS are located in-line (directly in the path in which the source and destination communicate) and have the capability to prevent or block the malicious activity that is occurring.

How do Intrusion Prevention Systems Work?

Intrusion prevention systems are usually located behind a firewall to function as another filter for malicious activity. Since intrusion prevention systems are located in-line, IPS are capable of analyzing and taking automated actions on all network traffic flows. Those actions can include alerting administrators, dropping dangerous packets, halting traffic coming from the source address(es) of malicious activity, and restarting connections. It is important to note that an effective intrusion prevention system must be efficient to avoid hindering network performance. In addition, intrusion prevention systems must work quickly and accurately in order to catch malicious activity in real time and avoid false positives.

How do Intrusion Prevention Systems Detect Malicious Activity?

Intrusion prevention systems have various ways of detecting malicious activity, however the two predominant methods are signature-based detection and statistical anomaly-based detection. The signature-based detection method used by intrusion prevention systems involves a dictionary of uniquely identifiable signatures located in the code of each exploit. There are two types of signature-based detection methods for intrusion prevention systems as well: exploit-facing and vulnerability-facing. Exploit-facing methods detect malicious activity based on common attack patterns, whereas vulnerability-facing methods attempt to detect malicious activity by identifying specific vulnerabilities. On the other hand, intrusion prevention systems that rely on statistical anomaly-based detection randomly sample network traffic and then compare the samples to a predetermined baseline performance level.

Intrusion Prevention System Comparison

There are four common types of intrusion prevention systems. The first type of intrusion prevention system is called a network-based intrusion prevention system (NIPS). This type of intrusion prevention system has the ability to monitor the whole network and look for suspicious traffic by reviewing protocol activity. In contrast, wireless intrusion prevention systems (WIPS) only monitor wireless networks for suspicious activity by reviewing wireless networking protocols. A third type of intrusion prevention system is called network behavior analysis (NBA). Network behavior analysis looks at network traffic in an effort to locate threats that cause unusual traffic flows, including distributed denial of service (DDoS) attacks and policy violations. The last common type of intrusion prevention system is host-based intrusion prevention systems (HIPS). A host-based intrusion prevention systems is an installed software package that looks into suspicious activity that occurs within a single host.

Best Intrusion Prevention System

The intrusion prevention system market has a very wide product offering. This makes choosing the best intrusion prevention system a quite difficult task. In an effort to reduce the complexity of choosing the best intrusion prevention system for you, it essential to set a budget, define the requirements that your new system will need to fulfill, and do your research on the different intrusion prevention systems on the market. Keep in mind that an intrusion prevention system is a standalone technology and not a comprehensive security solution. While an IPS can be a valuable technology for detecting malicious activity on networks, an effective security program should leverage additional technologies and resources for data protection, endpoint security, incident response, and more.

Data Security Knowledge Base

Data Encryption

What is Data Encryption?

Encryption is a data security technique that converts electronic data in to ciphertext so that it can only be understood after being decoded (decrypted) by authorized parties. The goal of encryption is to provide protection to sensitive digital data that is stored on a computer or transmitted across networks. Today, encryption algorithms are widely used as a key component of data security for IT systems and communications.

Data encryption can be used to secure data that is located on media, in storage, or in transit. Data encryption is a popular approach to protecting data that resides on any type of digital media storage device such as USB devices and hard drives. Data encryption temporarily decrypts the data when it is being used and then encrypts it again when the user is finished.

Data encryption is used to inhibit outsiders from reading, modifying, or duplicating encrypted data. Encrypted data can still be viewed in a file listing, but prohibits unauthorized persons from reading file contents. Even if stolen, encrypted data remains unreadable unless it can be decrypted. An important aspect of data encryption to keep in mind is that data encryption doesn’t protect files from being deleted. Therefore, it is recommended that all encrypted data is backed up, and that data encryption be employed as one facet of a defense-in-depth security strategy.

Email Encryption

Without email encryption, employees can accidently or purposely leak sensitive information by sharing it via email. When dealing with regulatory compliance, a remote workforce, and project outsourcing, email encryption allows for a secure way to share information. Email encryption usually uses public-key cryptography. This is where the user has a public key that other anyone canuse to encrypt email messages, but only a unique private key can be used to decrypt the messages they receive. Symmetric key encryption, also known as private key encryption, is a less popularmethod that uses the same, unique key for both encryption and decryption.

Encryption Software

Encryption software encodes computer data so that it only can be retrieved using a specific key. There are various types of encryption software for both business and personal use. There are many encryption tools for personal use that are open source and free to use, while enterprise-grade encryption software is typically sold by software security vendors. Additionally, most encryption software programs provide different versions and features in an effort to better fit the encryption needs of the user.

With all the different choices available, choosing the right encryption software can be difficult. When deciding on what encryption software is right for you or your company there are some things to consider. For personal use, free open source encryption software is usually enough to take care of the user’s encryption needs. However, for businesses, especially those with employees or third parties that communicate frequently from multiple locations, enterpsie-grade encryption software choices might be necessary. It is important to do your research when comparing data encryption software tools. There are many online sources for encryption software reviews that break down the software product, compare price points, and provide customer testimonials.

Encryption Security Threats

The main issue with encryption is the threat of an attack by a hacker. The most basic method hackers use to gain access to encrypted information is brute force, or simply trying every possible key until the right one is entered. Since the length of the key reflects the number of possible keys, the longer the key, the more difficult it is for the hacker to discover the right decryption key. A second method of breaching encrypted information is called a side-channel attack, where the attacker finds an error in the encryption system’s design or execution. There are also many decryption or cracking technologies available that can help hackers decrypt sensitive information much more efficiently.

Data Security Knowledge Base

Advanced Persistent Threat

What is an Advanced Persistent Threat (APT)?

An advanced persistent threat (APT) refers to a continuous computer hacking process in which a cybercriminal carries out a prolonged attack against a specific target. Since advanced persistent threats occur over an extended period of time, the advanced persistent threat must be stealthy and well-coordinated. Advanced persistent threats usually victimize organizations and/or governments, and typically have financial or political motives.

Advanced persistent threats are used to steal data without causing damage to the network or organization. In addition, advanced persistent threat attacks are most often carried out against organizations with valuable information, including financial institutions, healthcare organizations, manufacturing companies, and national defense organizations. The main difference between advanced persistent threats and other hacking methods is that in order to be successful, advanced persistent threats must be undetectable throughout the entire duration of the attack.

Advanced Persistent Threat Life Cycle

The initial step an attacker takes when beginning an advanced persistent threat attack is acquiring information to learn more about their target. Next, the advanced persistent threat proceeds with the attacker penetrating the target’s network through hacking or social engineering methods and distributing malware to the desired destinations. Once the network is compromised, the advanced persistent threat attacker keeps a low profile while they develop a plan to access and/or steal the information that is being targeted. Once the advanced persistent threat attack is in full swing, the attacker will capture information over an extended duration of time. The last step in an advanced persistent threat attack involves the attacker exfiltrating that data, covering their tracks, and using the stolen information based on their motives.

Advanced Persistent Threat Detection

Advanced persistent threats can be very difficult to detect due to the covertness of the attacker. An advanced persistent threat attack can go on for months with no visible signs to the target. Additionally, often times when a target realizes they are under attack they only discover a fraction of the attack as a whole. However, there are various warning signs that could signal that your business is under attack.

One of the most obvious warning signs of an advanced persistent threat attack is suspicious emails, as email phishing techniques are a popular way for attackers to gain entry into targeted networks. Another indication of compromise to look for is abnormal traffic and/or suspicious connections within your company’s network. Furthermore, advanced persistent threat attackers may try to issue commands to your company’s key applications. The last major warning sign of an advanced persistent threat attack is unauthorized attempts to access your company’s sensitive data or unusual data transfers.

Advanced Persistent Threat Protection

Despite the stealthy nature of advanced persistent threat attacks, there are preventative measures companies can take to protect themselves against the loss of critical information. One of the most important steps in protecting against advanced persistent threats is to have layered data security protections in place and know what data you are trying to protect. This will not only help to prevent advanced persistent threats, but will also ensure that your most sensitive data would remain protected if an advanced persistent threat attack were to happen.

Another critical safeguard in protecting against an advanced persistent attack is having continuous security awareness training for all employees. This ensures that all employees are aware of what to look out for when online and using email. Other technological safeguards against advanced persistent attacks include but are not limited to application whitelisting, encryption, data classification, security analytics, and managed security services.

Data Security Knowledge Base

Phishing Attacks

What is a Phishing Attack?

A phishing attack is a tool used by cybercriminals to gain sensitive information including passwords, usernames, and credit card information. Phishing attacks occur through mediums such as social web sites, auction sites, banks, and email, where the attacker reaches out to unsuspecting victims asking them for the information they are seeking. To carry out a phishing attack, attackers disguise themselves as valid electronic communication entities in an effort to gain the victims’ trust.


Phishing attacks are an example of social engineering, which can be defined as the psychological manipulation of an individual that leads them to perform certain actions or provide confidential information. With the continued popularity of social media sites and email services, the threat for phishing attacks continues to grow. Attackers use the messaging and email capabilities of theses mediums to execute their phishing attacks.


Phishing Attack Examples

Phishing attacks first began occurring in 1996 and since then have impacted millions people from all over the world. A notable phishing attack took place in 2013, where the credit card information of 110 million Target customers was stolen via a phished subcontractor account. Another large scale phishing attack seemed eminent in 2014 when the home improvement chain, Home Depot, was stripped of the personal and credit card data of over 100 million customers. The exposed data, including email addresses and other personal information, was put up online for sale on hacking websites – leaving millions of Home Depot customers vulnerable to targeted phishing attacks.


Phishing Attack Detection and Prevention for Users

Phishing attacks are usually carried out through email spoofing and instant messaging. Email spoofing is the act of creating email messages that contain a forged or spoofed sender address. These emails and messages will either prompt the victim to confirm confidential information or link them to a fraudulent website that attempts to make the victim leak sensitive information. People can also become a victim of a phishing attack by clicking on a pop-up window and being redirected to a fake website where they provide personal information.


There are various ways to detect and prevent against email phishing attacks. First off, to avoid a phishing attack you should be sure to use caution when checking your email. Phishing attacks that use emails to lure victims are often from an unrecognized sender or are impersonalized. In addition, phishing emails sometimes use scare tactics or a sense of urgency in an attempt to get the person to act on impulse. Another safeguard against phishing attacks is to set spam filters to high. Even though might catch some legitimate emails, the more spam emails you are able to catch, the safer you are from phishing attacks. Furthermore, anti-virus software will assist in detecting and removing common malware from your computer.


To avoid a phishing attack when sharing information over the internet, the most important thing to do is to make sure you are on a legitimate website. Phishing attacks can involve victims being directed to a site that looks very similar to their intended destination, but are in fact fake. The best way to tell if a website is legitimate is by looking at the URL. When on the internet, make sure URL reads “https,” where the “s” at the end stands for secure. Moreover, when clicking on links or browsing the web, check the URL text carefully to ensure that you’re not viewing spoofed version of the website with a similar URL.


A last measure for avoiding phishing attacks is to configure privacy settings social media and watch who you talk to on social networking sites. Attackers often use social media sites to gain information that they can use in phishing attacks, such as where people work, their habits, and their family members and friends. Additionally, attackers can use this information to start a conversation with you, pretending they know who you are. Lastly, make sure to configure privacy settings to limit the amount of personal information you provide on social media.


Phishing Attack Detection and Prevention for Businesses

Detecting and preventing phishing attacks can be challenging for businesses. Organizations’ success in defending against phishing attacks requires a combination of employee education, coordinated policies for data security and incident response, and selecting the right data security technologies to detect and stop phishing attacks – such as endpoint detection and response solutions, data loss prevention software, and anti-virus/anti-malware technology, among others.

Data Security Knowledge Base

Application Control

Application Control: Eliminate Application Risk While Conducting Business

Each new application your organization or employees install puts your company’s data at greater risk. That data holds tremendous value today – not only to your organization, but also to cyber criminals and malicious hackers. Applications can introduce exploitable security vulnerabilities to your environment, giving malicious parties additional attack vectors and potential ingress points. In addition to the risk of adding new security vulnerabilities, applications can also produce high volumes of data – some of which will require additional protection. As a result, many organizations today rely on application control solutions to manage application activity and control application risk by blocking unauthorized applications.

The Evolving Approach to Application Control: From Application Whitelisting and Blacklisting to Integrated Application Control Solutions

Application control techniques have changed significantly over the years. Traditionally, organizations handled application control through standalone security solutions such as application whitelisting, blacklisting, and greylisting software. This approach is simple - when an application attempts to run, it is checked against a list of approved or blocked applications and allowed to execute only if the list permits. However, many standalone application control solutions have developed a bad reputation for blocking legitimate application usage and hindering business processes as a result. Furthermore, point application control solutions too often fail to integrate with other security solutions, robbing security teams of valuable analytics and the ability to correlate threat intelligence across tools, technology layers, or attack vectors.

In recent years, many security teams have shifted from viewing application control as a standalone technology or to treating it as an integrated security process. More advanced solutions to application control leverage activity monitoring and context awareness to dynamically manage application risks, not simply with a list-based "block or allow" approach, but instead with flexible, automated controls that account for contextual factors such as the types of applications, users, and data involved in an attempted action. Other features of advanced application control tools include:

  • Application Monitoring & Visibility: Monitoring of all application activity is a critical component of application control technology, as it provides object-level visibility into all of the applications running in your business environment as well as how those applications are putting data at risk.
  • Context-Based Application Controls: Contextual awareness can allow or block application activity based on a variety of factors, including application vendor, process, MD5, data class, and user type.
  • To-and-from Data Flow Control: Data flow control goes beyond traditional "block or allow" application control methods to allow applications to run while restricting their access only to the data they require to run securely. In doing so, to-and-from data flow control bolsters application control capabilities by preventing the unauthorized transfer of sensitive data by authorized applications or users.

Extending Application Control to Web and Cloud Applications

Your organization and employees depend on web and cloud applications for communication, collaboration, storage, and more. While these applications can make your business more efficient and productive, they also open your networks to data loss, malware infections, and increased application risk. As a result, many advanced application control solutions offer extended capabilities to secure web application usage and protect sensitive data in the cloud.

Web and cloud application control solutions serve two main purposes: ensuring that only authorized data can be accessed by or uploaded to web/cloud applications and preventing infected files from being downloaded by web/cloud applications. In order to meet these requirements, web and cloud application control solutions:

  • Provide continuous monitoring and visibility for all data interactions with web and cloud storage applications
  • Enable granular file movement control based on browser and OS events involving web applications such as SharePoint, Dropbox, Gmail, and more
  • Automatically classify and protect data extracted from web applications
  • Deliver forensic application event logs for more effective alerting, reporting, and policy creation
  • Automatically encrypt sensitive data prior to egress
Data Security Knowledge Base

Big Data Security

Big Data Has Big Potential, But Also Data Security Concerns

Enterprises are embracing big data like never before, using powerful analytics to drive decision-making, identify opportunities, and boost performance. But with the massive increase in data usage and consumption comes a whole set of big data security concerns. Ultimately, big data adoption comes down to one question for many enterprises: how can you leverage big data’s potential while effectively mitigating big data security risks?


Regulated Enterprises Face Additional Big Data Security Issues

Concerns surrounding the storage, management, transmission, mining, and analyzing of data are an even bigger issue when regulations come into play. A key example is the HIPAA privacy guidelines for healthcare providers, contractors, and other business associates who may come into contact with, use, or even be responsible for storing sensitive healthcare data.

One of the biggest challenges facing enterprises is the sense of loss of control over data that comes with utilizing cloud storage providers and third-party data management and analytics solutions. The impact of this is significant, as many regulations hold enterprises accountable for the security of data that may not be in their direct control.


Trends like BYOD Further Complicate Big Data Security

Add in trends like Bring-Your-Own Device (BYOD) and the rise in the use of third-party applications, and big data security issues quickly move to the forefront of top enterprise concerns. A December 2013 article from CSO Online states that many of the big data capabilities that exist today emerged unintentionally, eventually finding their place in the enterprise environment.


“Because security is not inherent, enterprises and vendors have to retrofit these systems with security,” notes CSO Online. But retrofitting big data security solutions on a system-by-system basis is not only not cost-effective, it makes the enterprise security process as a whole inefficient and unnecessarily complicated.


Big Data Security Risks Include Applications, Users, Devices, and More

Big data relies heavily on the cloud, but it’s not the cloud alone that creates big data security risks. Applications, particularly third-party applications of unknown pedigree, can easily introduce risks into enterprise networks when their security measures aren’t up to the same standards as established enterprise protocols and data governance policies.


Devices introduce yet another layer of big data security concerns, with workers embracing mobility and taking advantage of the cloud to work anywhere, at any time. With BYOD, a multitude of devices may be used to connect to the enterprise network and handle data at any time, so effective big data security for business must address endpoint security with this in mind.


Additionally there’s the issue of users. Particularly in regulated industries, securing privileged user access must be a top priority for enterprises. Certain users must be permitted access to highly sensitive data in certain business processes, but avoiding potential misuse of data can be tricky. Securing privileged user access requires well-defined security policies and controls that permit access to data and systems required by specific employee roles while preventing privileged user access to sensitive data where access isn’t necessary – a practice commonly referred to as the “principle of least privilege.”


These are just a few of the many facets of big data security that come into play in the modern enterprise climate.


A Multi-Faceted Approach to Big Data Security

Big data security requires a multi-faceted approach. When it comes to enterprises handling vast amounts of data, both proprietary and obtained via third-party sources, big data security risks become a real concern. A comprehensive, multi-faceted approach to big data security encompasses:


  • Visibility into all data access and interactions
  • Data classification
  • Data event correlation
  • Application control
  • Device control and encryption
  • Web application and cloud storage control
  • Trusted network awareness
  • Access and privileged user control

Many enterprises have slowly – sometimes rapidly – accumulated a series of point solutions, each addressing a single component of the full big data security picture. While this approach can address standalone security concerns, the best approach to big data security integrates these capabilities into a unified system capable of sharing and correlating security alerts, threat intelligence, and other activity in real time – an approach not unlike the concept of big data itself.

Data Security Knowledge Base

Insider Threat

Insider Threat: Protect your Data with Digital Guardian

According to the 2013 U.S. State of Cybercrime Survey, 53% of respondents say damage caused by insider attacks is more severe than damage from outsider attacks. Insider threats include theft of proprietary information, unauthorized access to or use of information/systems/networks, theft of intellectual property, unintentional exposure of private sensitive data such as customer and financial records, and other data breaches and theft. Digital Guardian is the only company that protects data from insider and outsider threats with a single platform.

Insider Threats Are Not Limited to Corporations and Enterprises

Insider threats are a serious concern at the government level, particularly for the U.S. government. In October 2011, President Obama issued Executive Order 13587, establishing the National Insider Threat Task Force (NITTF), under joint leadership of the Attorney General and the Director of National Intelligence to “…prevent, deter and detect compromises of classified information by malicious insiders.” Furthermore, the President’s memo on insider threats, called “National Insider Threat Policy and Minimum Standards for Executive Branch Insider Threat Programs,” was released in November 2012. Whistleblowers, information leakers, and fraud and abuse exposers all fall under the U.S. government’s insider threat umbrella. The NITTF assists government agencies in developing and implementing their insider threat programs, but protecting against insider threats is still a challenge for businesses.

Digital Guardian Classifies and Protects Data At Every Level

Digital Guardian works to prevent data loss and protect your data from insider threats, even at the government level. From the moment it is deployed, Digital Guardian starts identifying and protecting your most sensitive data. The platform automatically tags and classifies your sensitive data to stop anything proprietary from leaving your company or agency. It’s sophisticated enough to block and control only the behaviors that pose threats to your organization based on the user, event, and data type. Its unique contextual awareness and noninvasive approach minimize risk while your employees go about their business as usual.

The Need to Protect Company Data from Insider Threats

Chances are, your data is distributed to a wide network of employees, partners, and contractors. All of those users create, manipulate, and share data at rates never seen before. Your data moves on and off the corporate network, on corporate and personal devices, and now in the cloud. Independent contractors and freelancers work outside the office – and off your corporate network – meaning your network defenses are left behind and your data is put at risk every moment of the day. So, how are you protecting sensitive data from insider threats?

Digital Guardian Data Loss Prevention: Insider Threat Protection Implementation

Reduce insider threat risks and maximize your data protection capabilities with Digital Guardian Data Loss Prevention. Digital Guardian DLP was built to defend against insider threats, delivering full visibility into all data access and usage while applying controls to enforce data protection policies and prevent sensitive data loss. Its data protection capabilities include automatic data classification, device and email encryption, privileged user control, application control, malware protection, and more.

In order to defend against today’s insider threats Digital Guardian delivers:

  • Comprehensive data discovery, classification, and monitoring to identify where sensitive data is located, how it moves through the organization, and where risks lie
  • Security policy implementation and enforcement to prevent risky activity without disrupting business practices
  • Advanced analystics and correlation to identify potential risks in real time
  • Forensic-grade reporting to log all data activity and facilitate incident response

Digital Guardian Is Your Best Defense Against Insider and Outsider Threats

Digital Guardian offers the most advanced data protection platform. It is the only single platform to secure against both insider and outsider threats, safeguarding millions of endpoints against malicious or inadvertent data loss by insiders as well as cyber attacks and advanced threats. Proven to run silently for the world’s top IP holders, Digital Guardian has zero impact on even the most performance-sensitive devices. Get unprecedented data visibility and control at the endpoint with Digital Guardian, your best defense against insider threats.

Data Security Knowledge Base

Endpoint Detection and Response (EDR)

Comprehensive Endpoint Detection and Response with a Single Endpoint Solution from Digital Guardian

Endpoint Detection and Response (EDR) is an emerging technology. The term defines a category of tools and solutions that focus on detecting, investigating, and mitigating suspicious activities and issues on hosts and endpoints. Originally dubbed Endpoint Threat Detection and Response (ETDR), the term is now more commonly referred to as Endpoint Detection and Response (EDR).

A rapidly growing field, there are numerous software tools focused on endpoint detection and response as well as tools and solutions with broader offerings that include endpoint detection and response as a core or supplemental capability. Digital Guardian is recognized by industry analysts as a leading provider of endpoint detection and response solutions.

Why Endpoint Detection and Response Matters

Advanced persistent threats and customized targeted malware attack toolkits are intentionally bypassing traditional signature-based antivirus solutions. Endpoint detection and response solutions supplement traditional signature-based technologies for richer behavior-based anomaly detection and visibility across endpoints.

Endpoint detection and response tools offer greater visibility into endpoint data that’s relevant for detecting and mitigating advanced threats, limiting sensitive data loss, and reducing the risk of devastating data breaches occurring on endpoints. Endpoint detection and response tools are complimentary to a variety of other security measures and solutions as well, including data loss prevention (DLP) solutions, security information and event management (SIEM), network forensics tools (NFT), and advanced threat defense (ATD) appliances.

An Exploding Sector in Enterprise Security

Digital Guardian’s kernel-level security technology provides deep endpoint visibility to enable real-time detection and response of endpoint threats. Thanks to its heritage in data loss prevention, Digital Guardian's EDR solution can be supplemented with DLP capabilities including device control, data classification, and encryption, as well as the ability to block known malicious applications and unknown applications from copying, accessing, or transmitting sensitive data. Additionally, Digital Guardian’s endpoint security technology provides visibility into a variety of events, including:

  • Application access and activity
  • Operating system activity
  • All data interactions (creation, modification, transmission, duplication, etc.)
  • User access to sensitive data Memory usage

But Digital Guardian’s endpoint protection capabilities don’t end there. Digital Guardian’s endpoint detection and response functionality is also capable of malware discovery, correlation, and IOC detection. Digital Guardian can be configured to perform policy-based prevention and containment activities on individual hosts and it also supports both static and dynamic malware investigations and reporting.

Why Digital Guardian Endpoint Protection is the Ideal Solution for Endpoint Detection and Response

Digital Guardian’s widespread capabilities both for endpoint detection and response as well as broader data protection make the platform a far-reaching solution for modern enterprises. A single endpoint platform protects laptops, desktops, servers, and virtual environments, with support for a variety of operating systems. With multiple deployment options (on-premise, managed services, or hybrid msp), Digital Guardian’s versatile and comprehensive platform is an ideal solution for protecting enterprises’ sensitive data from an ever-expanding threat landscape.

Digital Guardian is the only endpoint security solution offering complete visibility into both insider and outsider threats across all endpoint devices. This data can be correlated with other security event streams via HP ArcSight in order to detect today’s most advanced attacks in real-time.

Endpoints Are Frequent Entry Points for Advanced Persistent Threats and Targeted Attacks

Endpoints are often entry points for advanced persistent threats (APT) and targeted attacks. In fact, 40 percent of security professionals say their endpoints have been an entry point for an APT or targeted attack within the past 12 months, making endpoint visibility critical in the modern threat landscape.

Only Digital Guardian offers comprehensive endpoint detection and response with a single solution that protects against both insider and outsider threats. A data-centric approach combining deep data visibility and knowledge of process-level malicious behaviors, Digital Guardian provides comprehensive protection against the loss of sensitive data.

As enterprise networks are changing in terms of where employees are located, where data is located, and from which locations it can be accessed, detecting threats at endpoints is an essential component of information security. By detecting, understanding, and stopping threats before sensitive data is compromised, Digital Guardian provides the most advanced endpoint detection and response solution available. Digital Guardian’s autonomous agent protects your endpoints wherever they may be, whether on a corporate network, third-party network, or not connected to a network at all.

Data Security Knowledge Base

Data Classification

Better Data Classification for Better Data Security

Modern businesses are handling vast amounts of data, with the volume of data managed, controlled, or used by any business growing exponentially in just a short time. As enterprises struggle to keep the pace of business that consumers or competitors demand, they continuously strive to better manage and protect their data, making it more readily accessible and available without compromising security. Digital Guardian data classification provides a solution to these challenges and is a foundational element to your entire data security program.

Why Data Classification is Foundational in the Modern Business Climate

In order to make sense of the ever-increasing volume of data, businesses must gain an understanding of what data requires protection and the appropriate level of protection. The data classification process involves first discovering data, regardless of where it resides, then determining appropriate categories, identifying various levels of sensitivity, and outlining policies and procedures that allow employees and others who come in contact with the organization’s data to operate within the framework of compliance.

Historically regarded as a challenging process, data discovery and classification provides insights on the types of data within your organization, data sensitivity, where data is stored, and how it’s accessed and protected. However, modern approaches to data classification have made the process scalable and achievable for all organizations.

Data classification is increasingly important for enterprises that must maintain strict compliance with regulatory requirements, such as the ability to retrieve data within specified timeframes to document compliance. Data classification is not merely a security solution (although it’s a critically important one), but it also makes an organization’s data more organized and streamlines the process for employees and other users to quickly find the correct information. In the event of a breach, classification can also guide incident response efforts by providing detail on what level of information was externally exposed.

Data Classification Puts the Focus Where It Matters

Data classification ensures that your focus is always on the data that matters most. Coupled with other security measures such as data loss prevention and endpoint detection and response, data classification enables you to prioritize threat alerts and identified risks based on those targeting your most sensitive and valuable information.

Digital Guardian Streamlines Data Classification

Digital Guardian automatically identifies, classifies, and tracks sensitive data from the moment it is created, modified, or transmitted. Instead of waiting to complete a lengthy, data classification project, Digital Guardian enables enterprises to achieve meaningful and scalable data protection immediately.

Traditional data classification processes can’t keep pace with the lightning speed at which enterprise data is growing today. Classification simply must occur as rapidly as data is being created, accessed, and shared within an organization. Otherwise, the process is for naught, as sensitive data can be easily missed.

Digital Guardian discovers and classifies data on endpoints, databases, file shares, and in the cloud to reflect today’s diverse data storage reality. Digital Guardian is the only data classification solution that’s both automatic and persistent, triggered at the endpoint the moment an action is taken on a file (e.g. creation, modification, duplication). Scheduled scans of file shares, cloud, and databases provide the enterprise-wide visibility to document compliance.

It’s also both content- and context-aware, so you’re not left with a partial picture of your data. Digital Guardian’s deep visibility to all data interactions enables you to know precisely who created what data, where it came from, how they created it, and why. Digital Guardian protects all of your data, regardless of whether it lives within or outside of your corporate network. What’s more, it can be configured for automatic classification and/or classification by user control, giving you complete and total control over your enterprise data classification process from the start.

Digital Guardian’s Data Classification Solution is Deployed Across Your User Base with Full Visibility and Control

Unlike other traditional classification solutions, Digital Guardian’s data classification solution is easily deployed across your entire user base. It’s the only endpoint security agent that’s compatible with Windows, Linux, and Mac; our appliances deploy quickly for the network, cloud, and database classification needed.

Data discovery and classification goes far beyond organization; it provides visibility into where your most sensitive data is located, as well as who has access to it, how it’s utilized, in what circumstances it is at risk, and potential ways it can be protected.

Digital Guardian’s comprehensive data classification solution meets requirements for regulatory compliance by identifying sensitive data such as electronic health records (as required by HIPAA), cardholder data (as required by PCI), confidential or proprietary design documents (as required by ITAR), and other structured and unstructured data. With automated data discovery and classification, you can support complete compliance efforts by never missing sensitive data or inadvertently allowing it to escape your control.

Digital Guardian doesn’t stop with data classification. An integrated security platform, Digital Guardian not only handles data discovery and classification, but protects the enterprise from every angle, defending against both insider and outsider threats. No other solution is capable of meeting the vast array of security requirements for modern enterprises from a single platform.

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