Article | March 17, 2022
In today's enterprise contexts, the cyber-attack area is vast, posing a serious threat to businesses. As a result, reviewing and upgrading a company's cybersecurity posture isn’t just about human involvement.
According to TechRepublic, a midsized company receives notifications for about 200,000 cyber events every day. This level of attack is overwhelming for a typical company's security team. Furthermore, as these threats go unnoticed, they will cause severe network damage.
Artificial intelligence in cybersecurity is becoming increasingly crucial as it can swiftly scan millions of data sets and find a variety of cyber threats, from malware to misconduct, that could lead to a phishing attack. In addition, AI and machine learning are constantly evolving and improving, and they will be able to identify new types of attacks that might happen today or tomorrow.
There are various advantages to using AI in cybersecurity. With today's fast-evolving assaults and rapidly proliferating devices, AI and machine learning in information security can help stay one step ahead of cybercriminals, automate threat detection, and respond more quickly than traditional software-driven or manual operations.
Artificial intelligence in Cybersecurity
As cyberattacks expand in volume and complexity, artificial intelligence (AI) in cybersecurity helps stay ahead of such cyberattacks. Cutting-edge AI technologies, such as NLP and machine learning, curate threat intelligence from millions of research papers, blogs, and news stories, providing instant insights to cut through the noise of daily alerts and substantially lower response time.
AI attempts to mimic human intelligence. It has enormous potential in the field of cybersecurity. If used correctly, artificial intelligence (AI) in cybersecurity can be trained to provide threat warnings, identify new types of malware, and protect critical data for businesses.
AI Provides Better Endpoint Protection
The number of devices used by remote workers is continuously increasing, and AI in cybersecurity will be important in protecting those endpoints.
Virtual private networks (VPNs) and antivirus software can protect against remote malware and ransomware assaults, but it typically relies on signatures. This means that if you want to stay safe from the threats that are currently present, you need to stay up-to-date on signature definitions.
This can be a serious issue if virus definitions lag, either owing to a failure in updating the antivirus solution or a lack of awareness by the software maker. As a result, if there is a new type of malware attack, signature protection may not work.
“AI-driven endpoint protection takes a different tack, by establishing a baseline of behavior for the endpoint through a repeated training process. If something out of the ordinary occurs, AI can flag it and take action — whether that’s sending a notification to a technician or even reverting to a safe state after a ransomware attack. This provides proactive protection against threats, rather than waiting for signature updates.”
Tim Brown, VP of Security Architecture, SolarWinds.
Artificial Intelligence Predicts Breach Risk
AI systems can help figure out the IT asset inventory, which is a complete and accurate list of all devices, users, and applications with different levels of access to various systems.
AI cyber security-based cybersecurity solutions can now calculate how and where you're most likely to be hacked based on your asset inventory and threat exposure (as described above), allowing you to prepare and allocate resources to the most susceptible regions.
Using AI-based cybersecurity analysis insights, you can set and modify policies and procedures to reinforce your cyber resilience.
AI Battles with Dangerous Bots
Bots account for a large amount of today's internet traffic, which is potentially harmful. Bots may pose some serious threats, ranging from account takeovers via stolen passwords to account creation fraud and data theft.
You can't defend against automated threats by relying just on manual answers. AI and machine learning in cybersecurity help identify good bots (like search engine crawlers), bad bots, and people. They also help get a complete picture of how people use a website.
AI in cybersecurity allows for the examination of large volumes of data and enables cybersecurity teams to adapt their strategy to a changing environment.
AI Helps in Detecting New Threats
Using artificial intelligence (AI), cyber security can identify threats and possibly unsafe actions. In addition, artificial intelligence can help because traditional software systems can't keep up with the massive number of new viruses released every week.
AI cybersecurity systems are trained to identify malware, perform pattern recognition, and detect even the slightest features of malware or ransomware assaults before they reach the system. This is done by using complex algorithms.
Predictive intelligence from AI in cybersecurity can be better because it can scrap articles, news, research and other information about cyber threats and curate content on its own by using natural language processing.
Opinion of the Experts on AI in Cybersecurity
Capgemini Research Institute investigated the importance of AI in cybersecurity. Their paper, Reinventing Cybersecurity with Artificial Intelligence, strongly indicates that modern organizations need to strengthen their cybersecurity defenses with AI.
Because cyberpunks are already using AI technology to perform cyberattacks, the survey's respondents (850 executives from cybersecurity, IT information security, and IT operations from 10 countries) believe that AI-enabled reaction is vital.
Below are some of the report's primary takeaways:
Three out of four executives believe AI helps their company respond more quickly to security incidents.
69% of businesses believe AI is required to respond to cyberattacks.
Three out of five companies say that AI helps cyber analysts be more accurate and efficient.
AI in cybersecurity gives better answers to an organization's cybersecurity demands as networks get more extensive and data becomes more complicated. Simply put, humans can’t keep up with the growing complexity on their own, so AI in cybersecurity will be used sooner or later.
In recent years, artificial intelligence (AI) has emerged as a critical tool for strengthening the work of information security teams. Cybersecurity professionals can utilize AI to deliver much-needed analysis and threat detection to decrease breaches and enhance security posture since humans can no longer adequately guard the dynamic corporate attack surface. In the field of security, AI can identify and prioritize risks, detect malware on a network quickly, lead incident response, and detect intrusions before they occur.
AI enables cybersecurity teams can establish powerful human-machine collaborations that expand knowledge, enrich lives, and drive cybersecurity in a far better way.
Frequently Asked Questions
How can AI be used in cybersecurity?
Artificial intelligence systems can help with the detection of zero-day malware, threat prioritization, and automated removal of malware.
What are some of the advantages of artificial intelligence in cybersecurity?
Some of the advantages of artificial intelligence in cybersecurity are:
Offers complete, real-time cybersecurity solutions
It can process massive amounts of data
Can AI be considered the future of cybersecurity?
Artificial intelligence (AI) is slowly but surely becoming a critical component of cybersecurity, supporting businesses of all sizes and sectors in enhancing their security effectiveness. Unfortunately, information technology and telecommunications have the quickest and most complex AI adoption procedures.
Article | March 16, 2022
Data exchanges happen between organizations and their partners, customers, distant employees, other legitimate users, and occasionally unauthorized individuals. Keeping track of all the information is difficult for many firms that lack adequate data loss prevention best practices. One cause is that employees transfer data across many communication routes, both permitted and illicit. They communicate using email, instant messaging, shared online folders, collaborative software, texting, social media, and other platforms. Employees also store data in various locations, such as desktops, laptops, notebooks, smartphones, file servers, legacy databases, the cloud, and other devices, as well as in the cloud.
A lack of awareness about what information goes out of the company makes data loss prevention more difficult. However, using data loss protection best practices can prevent the misuse of personal information.
The average cost of a data breach is $3.86 million in the United States. However, the price may be higher for large corporations. Home Depot, for example, spent more than $260 million in 2014 after hackers stole credit card information from more than 50 million consumers. As a result, Home Depot had to pay back banks, credit card companies, and customers and make court-ordered security changes.
Common Challenges of Businesses Not Having DLP Strategies
When weighing the advantages of a well-implemented DLP approach, you must equally examine the hazards of the alternative. For example, data breaches are costly to a company's bottom line. According to PurpleSec, $3.86 million is the average cost of a data breach to firms worldwide. Of course, this impact includes quantifiable cash losses, but it also consists of the irreparable harm to its reputation if a successful breach occurs. A solid data loss prevention strategy can help you escape the consequences of a disaster like this.
Essential DLP Strategies
Regardless of the size or industry, every organization requires a data loss prevention (DLP) strategy to prevent data loss. Medical records, financial data, and intellectual property are examples of important, sensitive, or regulated data that should be protected. In most cases, DLP entails both technologies and policy. Personal USB devices, for example, can't be used on workstations. This is a common practice, just like having clear rules for emailing confidential information.
Read on to learn some of the essential data loss prevention best practices.
Define the Roles and Responsibilities of Everyone
First and foremost, make sure everyone in the organization involved in data loss prevention understands their roles and responsibilities.
"DLP strategies encompass several things. Some of the best practices include identifying those in the organization hierarchy and their obligations or tasks under the DLP standards. You must determine who creates the policy, who revises it, and who puts it into action."
Baruch Labunski, CEO of Rank Secure
This distinction will help you keep a close grip on who has access to your data. Using the principle of least privilege, where individual users have access only to the information they need to accomplish their work—nothing more and nothing less—is one of the best methods to avoid a data breach. In addition, it will be easier to determine how much data is in danger if a user's account is hacked or otherwise compromised.
In the worst-case situation, clear user roles keep things going smoothly. It's customary to allocate roles to individuals in other types of emergencies, such as fires or floods, so that everyone understands what to do and can respond quickly. The breach of data is no exception. By defining their roles and responsibilities, you can avoid situations where misunderstandings lead to confusion and, eventually, inaction.
Get Rid of Unnecessary Data
The rising importance of artificial intelligence and automation could lead you to believe that all data is good and that having more information is always better. However, data is only helpful if it has a clear purpose. Excessive data can slow down production and efficiency and put a lot of data at risk.
As a result, it's critical to remove any data that doesn't serve any purpose. If unwanted data is collected and stored, it is more likely to cause harm than good. It not only clogs up your data landscape but also draws attention away from the most critical information and increases the risk of data loss.
Eliminate unwanted data to reduce your risk. So, a key DLP strategy is to get rid of any data that doesn't make a big difference in the growth of the company.
Have a Data Classification Framework
It's also critical to segregate your data precisely. As businesses become more data-driven, specific data will inevitably be more sensitive and valuable than others. There are many ways to make your risk management processes more effective by separating sensitive information from non-sensitive information.
It's worth mentioning that this should include all data that has anything to do with your company. Pay close attention to the information you share with your vendors, partners, and other third-party platforms, as well as the information you receive from them. This is because all the data flowing in and out of your systems is at risk of being lost. A bird's-eye perspective is necessary to ensure you don't miss any blind spots. All the data you find should be sorted according to its relative importance after you've scanned each of them.
Regularly Update Policies and Procedures
When developing a DLP strategy, one of the most crucial best practices to remember is that there will never be a moment when you can dust your hands off and consider the job done. The responsibility to keep it safe is an ongoing process that will continue as long as valuable information exists.
Similarly, the implementation of your DLP strategy should correspond to and represent each stage of your company's growth. Your data loss protection plan should be updated as your company keeps growing and expanding. The rules and processes that are in place now may not be able to meet your company's future demands and requirements.
Educate Your Employees
DLP best practices rely heavily on employee understanding and acceptance of security policies and procedures. Employees’ data security understanding and their ability to follow recommended DLP best practices can be improved by education and training activities like classes, online training, monthly emails, and posters. Penalties for data security breaches may also enhance compliance, mainly if they are well-defined.
Data loss prevention (DLP) and auditing tools should be used to ensure that data usage restrictions are consistently enforced. The purpose is to determine how data is being utilized, where it is going, and whether or not it complies with compliance policies such as GDPR. Administrators should receive real-time notifications to investigate when a suspicious activity is noticed. In addition, violators should be held accountable for the data security policy's implications.
Frequently Asked Questions
Which is the best data loss prevention strategy?
Backing up all your data is the most crucial preventative best practice against data loss. Keep a backup of your information on a different server.
How can network data loss be prevented?
The best way is to prevent sensitive data from being lost over the network. Look for sensitive information in email subjects, messages, and attachments. Enforce policy-based web application monitoring and blocking. To ensure secure communication and regulatory compliance, encrypt email information.
What are the ways to protect data storage?
Some of the ways to protect data storage are:
Encrypt your data
Backup your data
Anti-malware protection is a must
Article | March 4, 2022
Virtualization has gained popularity in recent years because of its ability to improve efficiency and scalability at lower costs. Server virtualization is used by over 90% of businesses, and many companies are looking into other virtualization alternatives, such as application, desktop, network, and storage virtualization.
With the increasing popularity of virtualization, security has become one of the most significant concerns. As a result, there is a need to pay close attention to virtualization security risks. When compared to traditional server infrastructure, virtualization provides certain obvious security advantages. Virtual machines (VMs) have a lot of benefits, including increased availability, isolation from the operating systems and actual hardware they run on, and enhanced security measures that come standard with most virtualization solutions.
Because so many firms use this technology, it's an attractive target for hackers and other cybercriminals. However, virtualization is no more or less of a security risk than any other component of your IT infrastructure. Its use necessitates a greater understanding of the problems that IT managers problems.
Virtualization security is an essential component of a larger security strategy. Virtualization security must be applied to all physical, virtual, and cloud layers in today's settings, where more than 80% of them are virtualized.
“Virtualization allows organizations to cut costs, improve efficiency and increase essential infrastructure agility, but it also brings complexities – including scale and management concerns that impact the surrounding IT infrastructure. We support HP’s cloud initiative of delivering highly scalable and adaptable global-class services to ensure optimized application delivery to users and continue to collaborate with HP to help enterprises maximize the value of their virtualization investments.”
- Karl Triebes, senior vice president, Development, and chief technology officer, HP
Read on to know more about the risks of virtualization and how to mitigate them efficiently.
Top Virtualization Security Risks
Virtualization security risks are known to affect businesses adversely. So, it is better to be aware of these potential risks and find ways to mitigate them. Some of the top virtualization security issues can be:
• Keeping snapshots on VMs
• External attacks
• Network configuration
• File sharing between VM and host
• Offline virtual machine security
• Viruses, ransomware, and other malware
• VM sprawl
Ways to Mitigate Virtualization Security Risks
Now that we've covered the potential risks associated with virtualization, let’s look at reducing these risks. Here are some things you may do to lessen the effects of security issues mentioned above:
Protect Your Data Centre by Securing Management Interface
Virtualization systems may improve data center efficiency and cost-effectiveness, but they also add complexity with a different administration interface to protect. As a result, agencies must ensure that their management interface is safe. Even if an attacker gains administrative access to a system, they cannot take over a large part of the data center and alter hardware resources.
The best defense is to restrict access to a minimum. In addition to needing a strong multifactor authentication, cybersecurity teams should guarantee that the interface is only available from a virtual local area network devoted to that purpose. For administrators to get access, they first need to connect to the dedicated VLAN by VPN or jump box. This significantly reduces the risk of a breach because it prevents attackers from accidentally coming across the interface during routine network scans.
Find Out Warning Signs, Carefully Monitoring Networks
Even the most meticulously constructed security safeguards can fail at times. Therefore, monitoring networks and systems for signs of compromise is one of the most critical tasks for agency cybersecurity teams. This necessitates a robust set of technologies and processes, such as intrusion detection and prevention systems, thorough logging and security data, and event management systems that correlate collected data. While developing monitoring techniques, another thing to keep in mind is to pay extra attention to monitoring virtualization platforms for signs of compromise, like unusual inter-VM network activity or administrative connections from unknown sources.
Protect Your Environment with Strong Virtualization Security Tools
Companies can deploy robust virtualization security tools to protect businesses from virtualization security risks. This will help safeguard against any potential threats and breaches. Some of the practical tools can be:
Antivirus and anti-malware software
Change auditing software
Backup and replication software
Have a Well-Designed Disaster Recovery (DR) Plan and Strong Backup
Whether you experience a cyberattack or a hurricane bringing down your production data center, a proper disaster recovery plan and backup are critical to guaranteeing business continuity. In addition, having a disaster recovery site in a remote data center or the cloud can help reduce the virtualization issues of extended downtime. You can consider three steps as you put together your disaster recovery plan:
Back up VMs and physical servers
Use the 3-2-1 backup rule
Modern businesses must protect their virtual environments from various virtualization security attacks. Keeping all software up to date, utilizing antivirus software, following configuration best practices, and providing frequent user training are essential tactics. However, some threats will get through even the finest defenses, so it's critical to invest in virtualization security solutions that can track changes and logons to help you maintain security at all levels, all the time.
Frequently Asked Questions
Does virtualization improve security?
Virtualization increases physical security by lowering physical hardware elements. In a virtualized environment, less hardware means fewer data centers. In addition, server virtualization allows servers to revert to their default state in an incursion.
What are the basics of virtualization security?
The basics of virtualization security are:
Secure all the parts of the infrastructure
Reduce the open ESXi firewall ports numbers
Have a robust backup and disaster recovery (DR) plan
What are some of the types of virtualization?
Some of the types of virtualization are:
Article | March 1, 2022
Database security is critical because it contains a vast volume of highly sensitive data. These features of the database make it prone to cyber-attacks. However, what measures can be taken to safeguard data against such threats? In addition, some catastrophes, such as system outages, unauthorized access, and data loss, can occur if you do not have best practices for database security.
According to the Q3 report of Risk Based Security 2020, 36 billion data were compromised between January and September 2020. The report also emphasizes the importance of adequate database security best practices to prevent data loss.
According to IBM, data breach costs increased from USD 3.86 million to USD 4.24 million in 2021. In the 17-year history, this is the highest average total cost.
“We believe that data is the phenomenon of our time. It is the world’s new natural resource. It is the new basis of competitive advantage, transforming every profession and industry. If all of this is true – even inevitable – then cybercrime, by definition, is the greatest threat to every profession, every industry, and every company in the world."
Database security practices differ from website security practices. Software solutions, physical actions, and even employee education are part of the former. Therefore, it’s crucial to secure your site to limit the attack routes that cybercriminals might use.
Database Security Challenges
With the evolution of the internet and the growing dependence, numerous services based on internet-based databases have emerged. Therefore, the threats and challenges that databases face have increased manifolds.This provides online foul players increased chances to turn things into their benefits.
Online fraudsters are looking for a chance to get into database accounts and make use of them in their favour. So, there should be a well-planned strtategy to mitigate risks, and understand all the potential breaches.
Some of the challenges and threats faced by database security are:
Intellectual property rights
Physical location security
Database Security Best Practices
The term refers to a set of procedures used to prevent security breaches in a database management system. As a result, the database's reliability can be kept up by following certain rules on a regular basis.
Read on to learn about database management best practices and the steps your company should take to secure them.
Respond to Potential Attacks by Actively Scanning Your Database for Breach Attempts
The more often you check your database for possible data breaches, the more secure you are and the faster you can react to any problems.
You can use monitoring software, such as SolarWinds Database Performance Analyzer, SolarWinds Database Performance Monitor, Paessler PRTG Network Monitor, and SQL Power Tools, to keep track of all actions on the database server and receive alerts if there are any breaches. Set up escalation measures in the event of a potential attack to keep your critical information secure.
Another database security best practice is conducting frequent security audits and cybersecurity penetration tests. These allow you to identify potential security flaws and fix them before a breach occurs.
Create Backups for Database to Mitigate Losing Sensitive Information
While it is common to have a back-up of your website, it is critical to back up your database also. This significantly reduces the chances of losing sensitive data because of malicious attacks or data corruption.
Also, to boost database security, ensure that the backup is stored and encrypted on a different server. This ensures that your data is recoverable and secure even if the primary database server is compromised or unavailable.
Regular Updates and Monitoring Can Save you from Hackers and Breaches
Always use the latest database management software, such as MySQL, Microsoft Access, Oracle, PostgreSQL, and dBASE, as an adequate database security best practice. In addition, keep your operating system up to date to stay protected from the latest security threats.
Any program connecting to the database from a third party can pose a security risk. To avoid external flaws, keep all plug-ins up-to-date. Ensure that all database security settings are turned on by default, especially when connected to multiple third-party apps.
Understand the Various Types of Data and How to Categorize to Protect it Effectively
To secure data successfully, you must first understand what types of data you have. Then, your data repositories will be scanned, and the results will be reported using data discovery technologies. Using a data classification technique, you can organize the data into categories. Data discovery engines commonly use regular expressions for their searches, which are highly flexible but challenging to create.
Data detection and classification technology allow you to limit user access to vital data and avoid storing it in insecure locations, lowering the risk of data loss and inappropriate data exposure. All essential or sensitive data should be tagged with a digital signature that indicates its categorization to safeguard it according to its importance to the company.
Database security best practices encompass a wide range of security concerns and activities. However, the most effective security measures discussed in this article help keep your database secure.
Keeping your database safe from unwanted attacks is a multi-faceted task that includes everything from the physical location of the servers to limiting the possibility of human mistakes.
Even though data breaches are becoming rampant, following sound database security best practices reduces the chances of being targeted and helps prevent breaches.
Frequently Asked Questions
What is database security?
Businesses take steps to protect their databases from both internal and external threats. Database security protects the database, the data it holds, the database management system, and the numerous applications that access it.
What are the types of database security threats?
There are many types of database security threats. Some of them are:
Exploitation of Database Software Vulnerabilities
SQL/NoSQL Injection Attacks
Buffer Overflow Attacks
Denial of Service (DoS/DDoS) Attacks
An Evolving IT Environment
What are the different types of databases?
Databases can be relational databases, NoSQL databases, cloud databases, columnar databases, wide column databases, object-oriented databases, key-value databases, and hierarchical databases.