How Does AI Help Prevent Cyber Attacks in the e-Commerce Sector?
Cyber attacks are not uncommon in any industry, but they are especially prevalent in the banking sector. Banks typically hold a large amount of sensitive data related to clients and businesses that have accounts within the bank. As a result, wealth managers and bankers must spend more money than other sectors to resolve issues caused by cyberattacks.
Cyber threats have the potential to destabilize large business networks and gain access to confidential and private data that is otherwise protected by robust cybersecurity systems and protocols. Relying solely on cybersecurity experts may not provide a failsafe solution to preventing major cyber attacks. Due to the necessity for better security systems, banks have invested heavily in artificial intelligence and the aspects it provides.
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More companies are using AI to prevent cyberattacks and fraud than other vendor-related services. Given this, it is critical to examine the connection between artificial intelligence implementation and e-commerce security measures in order to define a comprehensive approach in the event of a malicious cyberattack.
Here are five ways AI can help prevent various types of cyber attacks.
AI fighting spam and phishing
Phishing, a form of cyber attack in which the perpetrator attempts to impersonate a person or company in order to deceive the victim, is a major threat to businesses. Companies can create a system that can identify unusual behavior and anomalies by basing algorithms on understanding and recognizing patterns in massive amounts of data. Using data analysis and this algorithm, AI can detect spam and phishing emails by looking for anomalies and warning signals in the message content and context.
Protecting DNS data with AI
Many cyber criminals use the domain name system (DNS) to gain access to sensitive customer and business data. Machine learning (ML) and AI can protect businesses from these types of attacks by analyzing trillions of DNS queries to better understand where bad actors hide. DNS poisoning occurs when an attacker intercepts a DNS request and sends the client a forged (poisoned) response. This is a critical issue for businesses because there are over 30,000 DNS poisoning attacks per day and the DNS layer is involved in 70% of all cyber attacks.
Using artificial intelligence to detect advanced malware
Malware is a constantly evolving, serious risk to cybersecurity, but AI enables company defense strategies to keep up. The AI improves with each sample of malware that passes through the model. Deep learning AI has enabled businesses to improve their malware protection strategies by increasing the volume and accuracy of the data it analyzes.
AI in authenticity protection
Authentication is critical in cybersecurity, and the evolution to multi-factor authentication (MFA) has improved access security. As cyber criminal tactics evolve, AI plays a critical role in improving authentication processes. Traditional authentication processes only protect against threats during the login stage, whereas AI systems can detect and respond to threats throughout a user’s session. For example, if the user abruptly switches to a new location and device, or tries to access financial information that isn’t related to their job, they’ll be prompted to verify their identity.
AI and breach risk prediction
AI systems can predict how and where organizations are most likely to be breached, allowing organizations to allocate resources and tools to areas of weakness. AI-derived prescriptive insights can assist organizations in configuring and improving controls and processes to most effectively improve their cyber resilience.
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Benefits of using AI in cybersecurity
Artificial intelligence attempts to mimic human intelligence. It holds tremendous promise in the field of cybersecurity. Artificial Intelligence (AI) systems, when used correctly, can be trained to generate threat alerts, identify new types of malware, and protect sensitive data for organizations.
Every day, a midsized company receives alerts for over 200,000 cyber events, according to TechRepublic. An average company’s security team cannot handle this volume of threats. As a result, some of these threats will go unnoticed and cause significant damage to networks.
AI is an excellent cybersecurity solution for today’s businesses that want to thrive online. To work successfully and protect their organizations from cyber attacks, security professionals require strong support from intelligent machines and advanced technologies such as AI. This article investigates the advantages of combining AI and cybersecurity.
Let’s take a look at them:
AI acquires more knowledge over time
AI is perceptive enough to learn on its own, which can be useful in developing network security over time. AI recognizes and clusters patterns on the network using machine learning and deep learning. It then detects deviations or security incidents from the norm before responding to them. These patterns may aid in the future improvement of security. Similar potential threats can be identified and mitigated if they are detected early enough. Continuous learning makes it difficult for hackers to outwit them.
Artificial Intelligence identifies unknown threats
A human may or may not be able to recognize all of the threats that an e-Commerce company faces. Hackers can carry out multiple attacks for a variety of reasons. These unknown threats have the potential to cause massive network damage. AI is more effective at mapping and preventing unknown threats from wreaking havoc on a company.
AI can handle massive amounts of data.
Even with a large amount of data, AI can detect potential threats. There is a lot of internal and external communication and data exchange in an e-Commerce company. This information must be shielded against malicious people and software. Cybersecurity personnel, on the other hand, cannot investigate all traffic for potential attacks. In this case, AI is the best possible solution because it can detect any threat hidden in this traffic.
Enhanced vulnerability management
Vulnerability management is critical to network security. As explained previously, the average e-commerce faces a plethora of threats on a regular basis. It must detect, identify, and prevent them in order to be safe. AI research can aid in vulnerability management by analyzing and assessing existing security measures. Companies can analyze threats much more easily when they use a vulnerability management tool.
AI allows you to evaluate systems faster than cybersecurity personnel, greatly improving your problem-solving abilities. It detects vulnerabilities in computer systems and business networks and helps businesses prioritize critical security tasks. This enables timely vulnerability management and business system security.
Improved overall security
The threats that e-Commerce face change on a regular basis. Every day, hackers change their tactics. This makes it difficult for an e-Commerce company to prioritize security tasks. You might have to deal with a phishing attack as well as a denial-of-service attack or ransomware at the same time.
These threats have the same possibility, but you must first understand what you’re up against. Human error and negligence are more serious threats that can make security difficult. The solution is to deploy Artificial Intelligence (AI) on your network to detect all types of attacks and assist you in prioritizing and preventing them. AI’s self-learning capabilities make it well-equipped to combat these multiple threats simultaneously.
Duplicative processes are eliminated.
As previously stated, attackers frequently change their tactics. The fundamental security best practices, however, remain constant. If you hire someone to handle these responsibilities, they may become bored along the way. Or they may become tired and complacent and overlook an important security task, exposing your network.
While AI mimics the best of human qualities while leaving out the flaws, it handles redundant cyber security processes that could bore your cyber security personnel. It aids in the regular detection and prevention of basic security threats. It also thoroughly examines your system for any security holes that could be detrimental to your network.
Detection and response times are expedited.
When your e-Commerce company’s network is compromised, it’s critical to act quickly and take the necessary precautions. “Prevention is preferable to cure.” It is safer to block a threat than to try to counter it after it has already caused significant damage. AI can detect these threats early on and stop them before they cause harm.
Most websites have a user account feature that enables users to log in to access services or purchase products. Some websites require visitors to fill out contact forms with classified information. Because such a site involves personal data and sensitive information, your company requires an additional security layer. The additional security layer will keep your visitors safe while they browse your network.
When a user attempts to access their account, AI ensures authentication. AI uses a variety of tools for identification, including facial recognition, CAPTCHA, and fingerprint scanners, among others. These features’ information can help determine whether or not a login attempt is genuine.
Best AI-enabled tools for cyber security available in the market
Darktrace, a leading AI cyber company, can help prevent spam and phishing attacks with its Darktrace for an Email solution. This solution examines links and attachments in all email communications across the organization. When phishing attacks occur, the Antigena solution detects that neither the recipient nor anyone in their peer group has ever visited the suspect domain.
DNSFilter provides DNS security powered by AI. Its DNS Filtering solution protects users against online threats and inappropriate content. The solution categorizes and then blocks or allows access to various websites using DNS. DNS filtering is considered edge-layer protection because it provides security at the internet’s most vulnerable security layer.
Netskope, a leader in secure access service edge (SASE), has created a comprehensive, multi-layered threat protection system to scan its customers’ network traffic. To help identify malware, AI/ML is used to power multiple engines in the inline fast scan as well as static and dynamic analysis-based deep scans.
OneLogin, a risk-based authentication company, offers AI-Powered SmartFactor Authentication, which streamlines real-time visibility into login attempts, allowing users to act quickly and address high-risk activities, easily define risk thresholds, and automatically adjust authentication requirements.
SentinelOne, a pioneer in autonomous security, expands on risk prediction with its WatchTower solution. With intelligence-driven, cross-platform threat hunting, this service provides visibility and actionability for novel attacker techniques, global APT campaigns, and emerging cybercrime. As SentinelOne’s threat researchers track threat actors in the wild, WatchTower curates, contextualizes, and prioritizes its intelligence sources to deliver user-relevant and timely insights.
Artificial intelligence (AI) is rapidly becoming a must-have technology for boosting the effectiveness of IT security teams. Humans can no longer scale to adequately secure an enterprise-level attack surface, and AI provides much-needed analysis and threat identification that security professionals can use to reduce breach risk and improve security posture.
Furthermore, AI can help discover and prioritize risks, direct incident response, and detect malware attacks before they occur.
So, despite the potential drawbacks, AI will serve to propel cyber security forward and assist organizations in developing a more robust security posture.
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