Combating Cyber Crimes Leveraging Artificial Intelligence

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The growth of the internet computing raises several concerns about the privacy and security information. Most of the cyber facilities are greatly susceptible to intervention and other dangerous threats. The use of sensors and various devices cannot check this challenge of cybercrime completely. That’s the reason why there is the necessity of utilising the modern, sophisticated IT. This It technology can be able to modify normal behaviours and also at the same time it can check or sense the abnormal behaviours too simultaneously. Cyber defence systems must be convenient, robust and also easy to adapt. Moreover, they should also be capable of detection of a broad range of threats and come up with an intelligent real-time decision. The rise of cyber attack is significantly increasing day in day out, and human beings alone are not adequate to analyse multiple attacks and at the same time create an immediate response. One of the essential things to note is that several network-centric cyber attacks are generated by different agents, who are very intelligent. For instance, the case of computer viruses. Therefore it is straightforward to track these criminal using smart semi-autonomous agents which are capable of detection, evaluation and creation of a quick response to cyber attacks. The use of computer-generated forces is very efficient and suitable for curbing the attacks and build immediate reply in time. This digital technology is capable of analysing the type of the attack caused, the targets, at the same time it gives an appropriate response, and it provides more information on how to block and prioritise various secondary attacks.

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There is no localisation regarding cyber attacks, and therefore it’s a global menace. It is universal meaning it causes threats to different computer systems worldwide. Initially, cybercrime could only be performed by educated specialist, but due to the internet spreading and expansion, nowadays cybercrime can be accomplished by anyone due to the adequate knowledge and equipment. Other conventional algorithms measures are utterly inefficient against inhibiting the drastically evolving cyber attacks. This is the reason why there is the need for an application of Artificial intelligence (AI). The Artificial intelligence is capable of offering a flexible capability to various computer software which will significantly help human beings to fight and prevent multiple cyber crimes. Artificial intelligence provides multiple solutions to several cyber crimes. The research carried out by Turing during the early age had some downs since there were no sufficient resources for computing.

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Therefore the person was so disadvantageous since he could not transform his bright ideas into the real act. Multiple successes have sprouted since then for instance in the case of heuristic search, first samples of machine learning, the processor of the natural language, systems involved in facial recognition, computer vision capable of focusing on character recognition as well as mobile robotics among others. Frank Rosenblatt's perceptron provided the background of artificial neural networks fields back in 1957. In the year 1980, the research concerning artificial intelligence showed some progress although very minute significant victories had been achieved. This smart combination can be seen clearly, and it is evolving from an artificial intelligence which is a pure software based to a neuromorphic computing hardware, for instance, IBM’s SYNAPSE as well as Google Tensor Flow Processing Unit.

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These two of them are permitting dramatic leaps; they can increase computational power or reduce the consumption of the electric power. Currently, many researchers are in the grand challenge since it is insufficient of the digitally federated environment. Therefore still there is no full sustenance of the artificial intelligence. Due to these problems, they have improvised different strategies, and they have come up with various shortcuts (for example the approaches of the heuristic) to build algorithms that have the representation of the specific management and localisation of views of intelligent logic. In the anti-virus technology of the new generations data mining, neural networks, heuristics and AISs also apply. Others such as IDSs, some of them employ the technique of intelligent agents, and it can also be used sometimes in conjunction with mobile agent technology.

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The mobile intelligent agents usually spread to various collection points and hence uncovering any cyber threat. According to Wang et al. the technology involved in future detecting of antivirus highly depends on the heuristic technology application. provided an IDS based on the artificial neural network which was highly detailed. This architecture boosted detection of intrusions in various networks. Itikhar et al. analysed the DoS attack using the neural network. Barman and Khataniar came up with studies on the creation of IDSs which also was involved in detection of intrusions. The artificial immune system is designed to maintain firmness in various environmental changes. This immune detection of multiple intrusions consist of the immunocytes evolution( clone, variation etc. it also detects antigens, and this works simultaneously. The immune system is involved in the release of the antibodies that creates resistance against pathogens.

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The measurement of the intensity of intrusion is by changes in the concentration of the antibody. Benaicha et al. designed an intrusion detection network basing on genetic algorithm. The system modification is high, with the selection operator and population which is initial to maximise the search for various attacks scenes. Other extensive artificial intelligence applications This area we give more examples of other hybrid applications. Pei and Song (2008) mainly put their concerns mostly on the adjustment of the performance of the detectors of the intrusions of the IDSs. Genetic algorithm maximises searching suitable fuzzy rules with the aim of obtaining the optimal solution. The experimental results displayed that it can detect network attacks within a reasonable time of about 2-3 seconds. Detection rate is above 97. SUCCESS RATE OF ARTIFICIAL INTELLIGENCE BASED CYBER SECURITY INITIATIVES Cybercrime is highly epidemic, the statistics done, and the results have shown that, up to the year 2019, the crime can lead to damage of above 2$ trillion annually, this is four times huge as compared to that of 2015.

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Some threats caused by cybercriminals can be restored within days, but some can prolong for weeks or even several months. Threats and malware are drastically occurring, and they are diverse. In future coming years we expect to see malware modification with adaptive and also learning to enhance the attack effectiveness. The new coming generation will be in a more significant position of awareness; this means that they will have more knowledge on the state of the environment and its upon them to come up with ideas and decide on what they are supposed to perform next. This generation may also choose to use codes which act as a progenitor to artificial intelligence and hence altering with the traditional strategies. CONCLUSION The fast growth and advancement of the information technology impacted positives and became convenient to lives of many individuals, although it has resulted to several matters that are so difficult to curb for instance the rise of cyber crimes.

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Applications of Artificial Intelligence Techniques to Combating Cyber Crimes: A Review. International Journal of Artificial Intelligence & Applications,6(1), 21-39. doi:10. ijaia. Vena, D. cicybs. Spector, L. Evolution of artificial intelligence. Artificial Intelligence,170(18), 1251-1253. doi:10. Wang, X. Yang, G. Li, Y. Liu, D. Review on the application of artificial intelligence in antivirus detection system. W. n. d. Victimology and Crime Prevention in Comic Books. Encyclopedia of Victimology and Crime Prevention. International Journal of Recent Trends in Engineering and Research,3(10), 240-246. doi:10. ijrter. jtu50 12. Qiang, H.

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