From email correspondence and financial transactions to professional networking, technology plays a critical role in business operations. Unfortunately, our adoption of technology is subject to overcoming security challenges. An increasing number of cyber-attacks indicate that several businesses lack adequate protection against online threats. According to IBM, the average cost of a cybersecurity breach has been increasing and is now at $3,860,000. The company also estimates that the cost of each stolen record that has sensitive information in 2018 was $148. It is a rise of 4.8% compared to their estimate for the year 2017.
Several global organizations are using tech-driven techniques to safeguard their systems and protect them against cyberattacks. Recently, artificial intelligence has emerged as an effective way to strengthen business security and thwart attacks. Next-gen cybersecurity products are emerging that use AI and Machine Learning (ML) algorithms to detect and eliminate the possibility of cyberattacks. ML and AI neural networks can accurately identify new attack vectors and anticipate the next steps of cybercriminals.
Automated Network Analysis: Most malware and cyber-attacks occur over computer networks. Monitoring network communications is, therefore, essential to detect attempted installations of malware and command-and-control (C2) communications of successful intrusions. Malware creators exploit common C2 protocols to merge with the rest of the traffic on the network. Placing malicious data in HTTP header values or embedding it in DNS requests achieves firewall beaches. ML-based detection algorithms use techniques like keyword matching, statistics monitoring, and anomaly detection to accurately identify the inbound/outbound data packets.
Email Scanning: AI-based algorithms are effective at detecting phishing emails that steal a user’s sensitive information such as passwords and bank account details. Several anti-phishing programs perform deep link inspection and simulate clicks on all the email links. It examines the resulting pages for signs of phishing. Natural language processing (NLP) techniques ensure that the email incorporates appropriate word choice and grammar. Finally, anomaly detection is applied to determine if any feature of the email sender, recipient, body, or attachment contains malware, adware or other suspicious programs. ML and AI algorithms provide protection against phishing attacks and detect suspicious emails that may contain malicious programs.
ML for Anti-malware: With the increasing number of computers, smartphones, and digital devices, protecting them from viruses and malware is critical. An AI-based antivirus program can detect unusual software behavior to identify signs of potential virus threats. A typical example of an AI-based Antivirus program is Microsoft Windows Defender. It monitors system performance and flags unusual activity, such as Microsoft Word using a lot of memory.
We develop AI-powered solutions that protect organizational data against malicious attempts and data breaches. Our AI team is skilled at using multiple technologies to establish security mechanisms that detect threats and strengthen information systems.
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