CYBERSECURITY INFRASTRUCTURE AND SECURITY AUTOMATION

International Journal of Science and Research (IJSR), 2024

Artificial intelligence will redefine the concept and operation of data security by infusing increased advanced threat detection, response, and prevention mechanisms. This paper will specifically discuss the critical role that AI-based systems play in the area of fortification of data security and also introduce innovative approaches underpinned by AI in cybersecurity. In the digitization age, connectivity and data exchange levels have touched unscaled heights, and in the process, data systems have never been so susceptible to the stroke of cyber threat. The increasing sophistication of data breaches, ransomware attacks, and other forms of attack, including sophisticated phishing schemes, makes it imperative for security measures to be similarly modern and innovative, responsive, and even predictive of quick real-time detection and response. In this respect, AI holds the promise of learning from experience. Building on this and a firm review of the current literature, this paper aims to evaluate the potential of AI to match modern security threats and the means through which it can be further integrated into the realm of cybersecurity. The study provides quantitative illustrations of cases where AI has been effectively adapted to dynamic security challenges, drastically reducing response times and improving detection accuracy. The study also presents some difficulties and limitations associated with integrating AI into cybersecurity infrastructures, ethical issues, personal data privacy, and never-ending algorithm updates. The results showed lots of promise for the achievements that AI could bring in cybersecurity by transforming the threat detection and response capability by a 30% reduction in the false positive rate. Threat identification became sure, and the false alerts were lessened. This reduced the time spent in responding to the identified threats by half, compared to traditional ways, and improved the ability of AI to process data and recognize patterns in real time. Also, AI integration has significantly reduced operational costs in the long term by automating routine tasks, thus assigning human resources to more strategic functions. However, among this multitude of benefits, the study also identifies the major challenges that need to be countered for successful implementation in AI: huge technological investment, the need for a workforce skilled in AI and data science, and data privacy and ethical issues. Transparent decisions with sufficient AI accountability are the factors that help avoid biases and maintain trust. The organizations, therefore, have strong data governance frameworks that must be developed to safeguard sensitive data, ensuring regulations around the globe. What can be gathered from this is that AI has great promise to revolutionize cybersecurity, but careful and strategic planning, ethical consideration, and ongoing monitoring are needed in the AI implementation process. In order to achieve balanced support, technological innovation and effective strategic management, by way of ethics and continuous education and training, are fundamental; these will help in utilizing the full potential of AI at work in cybersecurity. More research should focus on the long-term effects, the ethical consequences, and the interdisciplinary integration of AI into cybersecurity to benefit at the highest level while not being risky.

International Journal for Research in Applied Science & Engineering Technology (IJRASET), 2022

The cyber security industry's financial resources and human abilities to assess and battle every new type of cyber danger have been overwhelmed by the surge in cyber assaults. With the rise of the digital world, there is a rising quantity of personal and financial data that has to be secured against cyber-attacks. In reality, cyber assaults may devastate an organization's reputation or cause it to fail totally. This study investigates the use of artificial intelligence (AI) to improve cyber security. Artificial intelligence has advanced to the point that it has surpassed human capability in activities like data analytics. The analysis indicated that using AI to regulate cyber attacks has both benefits and drawbacks the benefits exceed the drawbacks. This study discovers that AI systems are likely to increase the safety of customers and enterprises in cyberspace due to the fast and efficient technology necessary to operate them [2] .

Cyber-attackers unit investment automation technology to launch strikes, whereas many organisations unit still victimisation manual efforts to mixture internal security findings and contextualising them with external threat data. Victimisation these ancient ways that, it'll take weeks or months to sight intrusions, throughout that amount attackers can exploit vulnerabilities to compromise systems and extract info. To wear down these challenges, progressive organisations unit exploring the employment of AI (AI) in their regular cyber risk management operations. The speed of processes and conjointly the amount of data to be used in defensive the cyberspace can't be handled by humans whereas not sizeable automation. However, it's hard to develop code with customarily mounted algorithms (hard-wired logic on deciding level) for effectively defensive against the dynamically evolving attacks in networks. this instance is also handled by applying methods of computing that supply...

2024

As cyber threats continue to evolve and become more sophisticated, traditional security measures are no longer sufficient to protect networks and sensitive data. Artificial intelligence (AI) and machine learning (ML) techniques offer powerful tools to enhance cyber security by enabling more effective and efficient threat detection and response. This paper provides an overview of the current state of AI and ML in cyber security, discussing key techniques, applications, challenges, and future directions. We review ML algorithms used for tasks such as anomaly detection, malware classification, and network intrusion detection. Case studies are presented showing the successful implementation of AI/ML in real-world cyber security systems. Limitations and challenges are also discussed, including the need for large labelled datasets, adversarial attacks on ML models, and the difficulty of interpreting black-box ML models. Finally, we highlight promising research directions, such as explainable AI for cyber security, unsupervised learning approaches, and the integration of ML with other security tools and frameworks. AI and ML will play an increasingly crucial role in cyber security going forward, and ongoing research will help unlock their full potential for safeguarding our digital infrastructure.

International Journal of Software Engineering & Applications

Internet usage has increased quickly, particularly in the previous decade. With the widespread use of the internet, cybercrime is growing at an alarming rate in our daily lives. However, with the growth of artificial intelligence (AI), businesses are concentrating more on preventing cybercrime. AI is becoming an essential component of every business, affecting individuals worldwide. Cybercrime is one of the most prominent domains where AI has begun demonstrating valuable inputs. As a result, AI is being deployed as the first line of defense in most firms' systems. Because AI can detect new assaults faster than humans, it is the best alternative for constructing better protection against cybercrime. AI technologies also offer more significant potential in the development of such technology. This paper discusses recent cyber intrusions and how the AI-enabled industry is preparing to defend itself in the long run.

Artificial intelligence has become a crucial element of cyber security because of its capacity to assess security threats instantly and respond appropriately. Nowadays, AI plays a more significant role in identifying and thwarting attacks that keep companies innovative. The primary goals of artificial intelligence in cybersecurity are threat identification and mitigation. Artificial intelligence uses machine learning algorithms and sophisticated data analysis to identify patterns and abnormalities in user behavior and network traffic that can point to a possible cyberattack. Artificial Intelligence can help stop attacks by using predictive modeling. AI is also capable of anticipating dangers and preventing them by analyzing historical attacks and finding patterns. Automated incident response system creation is just another crucial cybersecurity use of artificial intelligence. These systems can assess data, spot possible threats, and then take action to lessen the impact of the attack by containing it or mitigating its effects. Artificial intelligence must be used by businesses in cybersecurity to safeguard their networks and sensitive data against ever-evolving online threats. Artificial intelligence (AI) is quickly emerging as a crucial tool for effective cybersecurity in today's digital environment due to its capacity to evaluate massive volumes of data in real-time and automate incident response. The importance of artificial intelligence (AI) in cybersecurity, particularly its applications in threat identification and defense.

2019

In the age of digital transformation with adoption of Cloud and mobile computing and ever-increasing Internet of Things(IoT) devices, the cybersecurity risks and threat levels are increasing at a rapid pace. The data is spread across systems, devices and cloud leading to growing attack surface and increased frequency of the security attacks. IoT is extended to drones, driver-less cars, industrial equipment, smart buildings, consumer goods, home appliances leaving us with more vulnerable attack points. Organizations needs to have effective information security management system (ISMS) in place to proactively detect, react to security threats with reduced time to discover any potential breach. This paper highlights how Artificial Intelligence(AI) and Machine Learning(ML) can redefine cybersecurity to detect, prevent organizations from security threats and data breaches.

With excessive exposure and use of internet, every system is prone to wide range of attacks. With this perspective, Network security is gathering every ones' concern. Network attackers are getting more and more innovative with designs. Exponential growth in attacker's intelligence require mitigation mechanism to be updated with same speed and level of innovation. This pans avenues for advanced technologies and methods to be employed for handling network security issues. Trending ones are artificial intelligence(AI), machine learning (ML) and deep learning(DL). AI is an umbrella covering ML and DL under it. Main features of AI making it big deal for network security are capacity to handle big data, faster detection, quick response, ability of unsupervised processing. Considering mentioned aspects, comprehensive study of AI approaches in handling network security issues is been carried out.

2025

Artificial Intelligence (AI) is transforming the cybersecurity landscape, providing unprecedented capabilities in threat detection, incident response, and adaptive defense. This paper explores the intersection of AI and cybersecurity by assessing the dual role AI plays as both a defensive asset and a potential vulnerability. The study outlines how machine learning models enhance detection accuracy, automate responses, and identify sophisticated attack patterns in real time. At the same tiame, it acknowledges the dangers posed by adversarial AI, automation errors, and the lack of interpretability in current AI systems. The paper also evaluates leading AI-driven security platforms, compares their implementations, and discusses future developments in context-aware defense, federated learning, and explainable AI. The goal is to provide security professionals, researchers, and policymakers with a comprehensive overview of opportunities and challenges in AI-powered cybersecurity.

IJCSMC, 2019

In today's digital era, the emerge of IOT and linked devices, cyber security experts come across a lot of encounters. The specialists require all the aid to overcome attacks, security cracks, its affects and respond to the attacks. A lot of linked workplaces lead to heavy traffic, high security attack vectors, security breaches and many more that the cyber environment cannot be handled by humans without sizeable automation. It is not easy to create software managed system with standard working algorithms (hard-wired logic on deciding level) for successfully cautious against the prominently growing attacks in networks. It is a evident fact that number of cyber security problems are now settled as an add on with progress only procedures of Artificial Intelligence techniques unit acquiring utilized. Cyber Security applications and analyses can now be moulded with AI applications and its existing methods.