Due to the emergence of new digital and modern technologies cyber criminals can easily manipulate any data or information with ease. Emerging technologies kept cyber security at risk. On account of never ending innovations and technologies, the volume and complexity of cyber crimes have increased drastically.
Data security is so critical that the attacks from malware and hackers are greater than it ever has been in the past. Even though advancement of technology improved the daily operations of businesses, hackers have changed the way they attack data as well. Upgrading existing cyber security solutions and implementing every possible applicable security layer doesn’t promise that your data is tamper-proof.
Artificial Intelligence (AI) and Machine Learning (ML) are playing a major role in cyber security, with security devices studying data from millions of cyber incidents, and using it to identify malware and potential threats.
AI can quickly and effectively analyze human behaviors, work out a pattern, and recognize all sorts of deformities or irregularities in the network. Cyber vulnerabilities can be quickly identified with such data.
Cyber Threat Detection through Machine Learning
Machine learning can eliminate cyber threats and support security infrastructure through real-time cyber crime mapping, pattern detection and thorough penetration testing which can help to prevent similar attacks and respond to changing behavior. Machine learning is about evolving patterns and handling those patterns with algorithms. In order to develop these patterns, a lot of quality data is needed. The data must be relevant, complete and it should be extracted from potential sources.
AI in Biometric Authentication and Face Recognition
Since passwords can be easily hacked by cybercriminals, developers are using AI to strengthen biometric authentication and remove its faults to make it a reliable system. Through facial recognition systems human faces can be matched from an electronic image or a video frame against a database of available faces. It makes use of biometrics for mapping facial features and detects identity through key or unique features of the face. Researchers are evolving various methods in which facial recognition systems work. The most advanced face recognition method, which is also employed to authenticate users through ID verification services, works by pinpointing and measuring facial features from a given image.
AI ML in Malware Detection
Phishing is a kind of social attack frequently used to steal user data, credit card numbers, login passwords etc. It happens when an attacker, pretending to be a trusted entity, deceives a victim into opening an email, instant message, or text message. AI-ML can detect and track active phishing sources, react and can give solutions much quicker than humans can. The difference between a fake website and a legal one can be quickly identified through AI.
AI ML in Vulnerability Management
AI can be employed in this part of the vulnerability management process to help reduce the number of false positives, essentially detecting the miss-detections. Vulnerabilities are increasing day by day . It is extremely difficult to manage them through human resources. This can be more easily tackled through AI. AI-based systems actively inspect potential vulnerabilities in organizational information systems, through combining multiple factors, such as hackers’ discussions on the dark web, reputation of the hacker, patterns used, etc. AI can analyze these elements and use the information to detect when and how the threat might make its way to vulnerable targets.
AI in Network Security
Network security involves two important parts which is security policy and working out network topography of an organization. But both of these activities take a very long period for the process. AI can efficiently analyze user behaviors, deduce a pattern, and identify all sorts of abnormalities or irregularities in the network. It's much simpler to identify cyber vulnerabilities quickly through such data. AI can expedite these processes, which it does by observing and learning network traffic patterns as well as suggesting security policies. That does not only save time but also a lot of effort and resources which we can instead apply to areas of technological development and advancement.