By: Dadapeer Agraharam Shaik, Department of Computer Science and Technology, Student of Computer Science and technology, Madanapalle Institute of Technology and Science, Angallu,517325, Andhra Pradesh.
Abstract:
Since the nature of cyber threats is constantly evolving, AI has thus risen as a force against the modern, complex threats. This paper aims at analysing and describing various aspects of AI and cyber threats focusing on an application of artificial intelligence as the tool used in identification and combating of cyber threats. This includes the ways of thinking and actions that are used by AI to mitigate the attacks, the benefits of AI in the field of cybersecurity, and what new prospects can be expected in this important domain in the future. By perusing this discussion, we should be able to draw attention to the constant struggle between the implementing of AI and the cyber attackers thus posing the question as to who reign supreme in the continuous fight that can be referred to as the digital war.
Keywords: Ai in Cybersecurity, Ai-powered Cyber Attacks, Ai-driven Cyber Threats , Ai and Cyber Defence
1.Introduction
This concept has become paramount to face in the digital world since almost every device is connected to the internet and many societies rely heavily on digital structures. These threats have evolved to become more complex, and they are increasingly common, affecting from individuals’ information to states’ security. The conventional approaches to cybersecurity are still paramount and are, at the same time, incapable of preventing cybercriminals’ activities. It is at this point that Artificial Intelligence (AI) comes as a solution to change the cybersecurity paradigm. AI is applied to cybersecurity because of its capacity to scan a sizable amount of data, interpret it, and subsequently make decision promptly and effectively. In contrast, the machine learning approach is rather different and does not require any prior knowledge of threats and their definitions as AI systems are able to learn from data, find out new threats and even predict possible weak spots, and therefore, AI is an extremely useful tool in the fight against cyber threats. AI in cybersecurity means the system can integrate threat detection and response; threat intelligence and automated response; and predictive security analytics, which all generally improve a network’s security against multiple types of attacks at levels that cannot be achieved through manual methods. The application of AI in cybersecurity also comes with these drawbacks; issues to do with data privacy, large data sets when training the systems as well as adversarial aspects of AI. It is essential to reach a certain level of balance in thoughts behind creation of the AI systems so that it is not overemphasizing on minimizing the false negatives while at the same time not going in the opposite extreme of having excessively high false positives. Thus, AI is a dynamic and a highly effective solution to improve cybersecurity as the threats are constantly emerging, but it demands active development and cooperation of the stakeholders. The future of cybersecurity is in getting the best of AI cooperating with other innovative technologies, thus making the best defence system that will put to shame the hackers and cybercriminals.
2.AI in Cyber Security
Samsung recently suffered a major data breach when confidential code was uploaded to ChatGPT to get a review by the company’s staff. While using OpenAI services, it seems that the corporation may utilize the received data for model improvement unless the user has configured it not to do so. Hence, following the leakage of sensitive information by the employees using ChatGPT, Samsung has put strict measures that regulate how the model can be used in the future. This state of affairs highlights why organizations need to focus on the protection of data more now than ever before when more sophisticated AI applications are on the increase. Reminding people to use the web’s private browsing mode is another elementary way of minimizing the leakage of data. This is according to Trend Micro that states that private browsing can shield the user from the dangers of interacting with unsafe websites as well as phishing attacks[1].
One way of data-security is by engaging the privacy mode especially when interacting with LLMs. Although this may be paid and needs a user subscription, such as ChatGPT Enterprise, it guarantees that user inputs and information do not train the models, conserving business information. Most organizations use internal measures to curb leakage of data to unauthorized personnel. For example, the employees of Amazon receive pop-up messages concerning the dangers for the enterprise in terms of security when visiting ChatGPT sites on the work PCs, which ultimately excludes the unregulated AI usage.
Lurking in other uncertainties of Artificial Intelligence is the capability of AI to improve on the phishing process. During the call, Better Business Bureau’s Celia Surridge drew attention to the daily rise of consumer scams, especially when the traffic is high, like Black Friday, or specific days of the week, such as Wednesdays and Thursdays, related to Amazon Prime days. Brian Schnese from Hub International explained how easily AI can be misused: a single request to ChatGPT can write convincing phishing emails like, ‘change of wiring instructions’ to the vendors. This capability increases the risk factors and heightens the call for solid cybersecurity undertakings when dealing with AI contrived scams or maintaining the privacy and authenticity of relevant information. In the contemporary world of technological advancements, it is crucial to combine the application of AI with advanced levels of cybersecurity to ensure the security of data and establish users’ confidence.[2]
3.How does AI help in Cyber Security
Large-scale projects have defined the area of cybersecurity, especially where AI has been applied. Duties like threat identification, threat seeking, and handling of incidents remain predominantly manual tasks today, and this consumes a lot of time hence slowing down remedy processes, extends exposure to threats and raises the likelihood of cyber-crimes. Benefits of applying AI in cybersecurity are significant since it assists the government and business leaders in safeguarding individual systems, organizations, and communities against today’s cybersecurity threats.
Today, easy to use, fast, biometric, fingerprint, retina, and palm vein scanning methods are the most popular login techniques. These techniques can be used individually and in conjunction with passwords and are now a standard on most of the new generation smart phones. However, security breaches in large companies have violated users’ email addresses, personal details, and passwords, thus calling for the stronger security measures[3].
In the field of cybersecurity, AI can help the work of professionals due to the possibility to automate many processes and let the machines examine large amounts of data, pointing interesting items or something suspicious the human should take a closer look at. This not only enhances productivity but also can respond in a more timely manner to emerging threats that affect a business’ security, augmenting their cybersecurity position.[4]
3.AI-powered vs classic cyberattacks
The usage of cyber operations can be performed against certain persons or organizations in some regions by employing various cyberattacks. They include DoS and DDoS attacks, MitM attacks, phishing, spear-phishing attacks, injection attacks which are SQLI and XSS, jamming and eavesdropping, and malware attacks. All these are regarded as examples of classical cyberattacks. This paper focuses on new types of AI-powered cyberattacks, mainly in three categories: misclassification of data information, generation of synthetic data and includes data analysis.
It should be noted that AI is fuelled by data, and our perspective is devoted to the point of attacks related to audio, visual, and textual data. However, concerning the technology of these attacks, it can be utilized in different other circumstances. The comparison between AI-powered and classic cyberattacks regarding the recognized STRIDE menace model is also evaluated.[5]
Table.1 Representing AI-powered classical cyberattacks
ASPECT | AI-POWERED CYBER ATTACKS | CLASSICAL CYBER ATTACKS |
Automation | Largely automated with minimal human intervention | Requires more manual control and intervention |
Attack methods | Can use different techniques like deepfakes, data poisoning, and polymorphic malware | Traditional methods like phishing, brute force, and malware |
Scalability | Highly scalable, capable of launching widespread attacks simultaneously | Limited scalability due to manual process |
Speed | Faster due to automation and AI decision-making | Slower as they often require manual adjustments |
In this research, they question and answer what refers to the general technical principles applied in weaponizing AI for cyberattacks and the kinds of attacks that are currently being conducted with such weaponised AI. [5].
Conclusion:
In the fast-changing landscape of cybersecurity, inclusion of artificial intelligence (AI) has become a very strong weapon in fighting sophisticated cyber threats. In addition, AI can now easily examine large amount of data quickly, identify any possible weakness and take prompt remedial measures when it comes to defensive actions against cyber insecurity. The application of AI in cybersecurity has changed how to detect threats, respond to them and be proactive for security predictions that goes beyond what manual methods can do.
Nevertheless, there are several challenges that AI poses to cybersecurity. Also, issues such as privacy constraints on data and the need for big training sets as well as the likelihood of misusing AI for negative purposes suggest the importance of balance and thoughtfulness while implementing this technology. The aim is to optimize these systems so that they will have low chances of false negatives but not too many false positives.
As shown by different instances like when there were massive data breaches in some notable companies or even where AI was used in designing complex phishing attacks, it is clear how double-edged sword AI is within the cyberspace. Vigilance must be maintained by organizations which ought to have strong internal controls against unauthorized access to data while enhancing their security through leveraging on what AI provides them with.
Reference:
- C.-Y. Lin, M. Rahaman, M. Moslehpour, S. Chattopadhyay, and V. Arya, “Web Semantic-Based MOOP Algorithm for Facilitating Allocation Problems in the Supply Chain Domain,” Int. J. Semantic Web Inf. Syst., vol. 19, pp. 1–23, Jan. 2023, doi: 10.4018/IJSWIS.330250.
- S. Ahmed, “Council Post: AI Vs. AI: How To Win The Corporate Cybersecurity Battle,” Forbes. Accessed: Jul. 28, 2024. [Online]. Available: https://www.forbes.com/sites/forbestechcouncil/2024/03/08/ai-vs-ai-how-to-win-the-corporate-cybersecurity-battle/
- K. T. Putra, A. Z. Arrayyan, R. Z. Syahputra, Y. A. Pamungkas, and M. Rahaman, “Design a Two-Axis Sensorless Solar Tracker Based on Real Time Clock Using MicroPython,” Emerg. Inf. Sci. Technol., vol. 4, no. 1, Art. no. 1, May 2023, doi: 10.18196/eist.v4i1.18697.
- D. Shamiulla, “Role of Artificial Intelligence in Cyber Security,” Int. J. Innov. Technol. Explor. Eng., vol. 9, pp. 4628–4630, Nov. 2019, doi: 10.35940/ijitee.A6115.119119.
- M. M. Yamin, M. Ullah, H. Ullah, and B. Katt, “Weaponized AI for cyber attacks,” J. Inf. Secur. Appl., vol. 57, p. 102722, Mar. 2021, doi: 10.1016/j.jisa.2020.102722.
- Rahaman, M., Lin, C. Y., Pappachan, P., Gupta, B. B., & Hsu, C. H. (2024). Privacy-Centric AI and IoT Solutions for Smart Rural Farm Monitoring and Control. Sensors, 24(13), 4157.
- Vajrobol, V., Gupta, B. B., Gaurav, A., & Chuang, H. M. (2024). Adversarial learning for Mirai botnet detection based on long short-term memory and XGBoost. International Journal of Cognitive Computing in Engineering, 5, 153-160.
Cite As
Shaik D.A. (2024) AI vs. Cyber Attacks: Who Wins, Insights2Techinfo, pp. 1