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The COVID-19 pandemic was a remarkable and unprecedented event that changed the lives of billions of citizens around the world and resulted in what is known as a new term in terms of social norms and lifestyles. In addition to the tremendous impact on society and business in general, the epidemic created a unique set of cybercrime circumstances that also affected society and business. Increased anxiety due to this epidemic increases the probability of success of cyber attacks by increasing the number and scope of cyber attacks. This article analyzes the COVID-19 epidemic from the perspective of cybercrime and highlights the wide range of cyberattacks experienced worldwide during the epidemic. Cyberattacks are analyzed in the context of major global events to reveal how cyberattacks work. This analysis shows how, following what appears to be a large gap between the outbreak in China and the first COVID-19-related cyberattack, attacks are steadily becoming more prevalent than in some on days, 3 or 4 unique cyber attacks were reported. This analysis uses surveys in the UK as a case study to show how cybercriminals use key events and government announcements to build and design cybercrime campaigns.

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Not all phishing attacks are always done in the form of website forgery and telephone phishing. Emails and messages that appear to be sent by the bank and receive information from the user can also be a phishing attack. Feature selection and sample selection are two very important issues in the data processing stage in detecting malicious emails. In particular, identifying spam without data reduction will not be nearly as accurate in the results. Most articles and research have focused on one of these issues, and there are few articles that have worked in combination to detect malicious emails. Therefore, the purpose of the present study is to provide a method to reduce the data in identifying emails by selecting features and samples simultaneously. In the proposed method in this paper, the forbidden search algorithm and the genetic algorithm are used in combination and simultaneously. For the suitability of this method, the evaluation vector machine evaluation function was used. The results showed that the detection rate of spam and e-mails in LineSpam and UCI datasets was 97.28, which was the highest possible value compared to other algorithms proposed in previous studies.

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In recent decades, video surveillance systems have an increasing development that are used to prevent crime and manage facilities with rapid diffusion of  (CCTV)cameras to prevent crime and manage facilities. The video stored in the video surveillance system should be managed comfortably, but sometimes the movies are leaking out to unauthorized people or by unauthorized people, thus violating individual boundaries . CCTV cameras and video surveillance systems are needed today because of the increasing number of crimes, These cameras and video surveillance systems. but because of unsafe storage and data sharing methods, access to movies saved by unauthorized people is possible. The use of existing protocols and security techniques has already been defeated several times by the attackers. It requires an alternative system that should not only be highly secure but not changeable. Video stream generated by surveillance cameras play a crucial role in preventing crime in smart cities. CCTV cameras are necessary for a range of public applications in a smart city; they can become smart sensors that help ensure safety and safety. in this paper, we review the methods and articles presented in the context of blockchain application in visual surveillance systems and compare them.

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Wireless sensor networks have many applications in the real world and have been developed in various environments. But the limitations of these networks, including the limitations on the energy and processing power of the sensors, have posed many challenges to researchers. One of the major challenges is the security of these networks, and in particular the issue of authentication in the wireless sensor network. An authentication scheme in a wireless sensor network must have the following security features: anonymity, Unlink sessions, session key agreement, session key security, and perfect forward secrecy and prevent attacker’s attacks. An important feature of the authentication scheme is that by capturing the sensor, the attacker will not be able to obtain the private values of the protocol parties. Chen et al propose an authentication scheme with key agreement using wireless sensor network for an agricultural monitoring system, which claims to have security features. This articcle proves that Chen et al’s scheme is vulnerable to sensor capture attacks that Obtain session key, sensor impersonation, User anonymity violation, forward and backward secrecy violation, and sessions link. In the rest of the article, the proposed solution to improve the design of Chen et al. will be presented and the improved design will be evaluated.

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