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Article Citation - WoS: 11Citation - Scopus: 24The Effect of Social Media User Behaviors on Security and Privacy Threats(Ieee-inst Electrical Electronics Engineers inc, 2022) Cengiz, Aslihan Banu; Kalem, Guler; Boluk, Pinar SarisarayThe number of online social network (OSN) users is increasing daily and attacks and threats against over the time spent on online networks has been increasing equally. Attacks against OSN users exploit not only system vulnerabilities but also user-induced vulnerabilities, which naturally affect the hacker's attack strategy as well. This study is designed to investigate the effect of social media user behaviors on their vulnerability level in terms of security and privacy. The study was conducted survey methods, which was applied to social media users in two countries - Turkey and Iraq. This study documents and analyzes the behaviors of 700 OSN users in two countries. This study examines the behaviors of social media users from two nationalities, investigating whether there is a relationship between social media users' behaviors and security and privacy threats. Research findings demonstrate that there is a significant relationship between OSN users' behaviors and their attitudes towards security and privacy. Additionally, Turkish social media users pay more attention to their behaviors in terms of privacy and security awareness than Iraq users.Review Citation - WoS: 245Citation - Scopus: 528A Comprehensive Review of Cyber Security Vulnerabilities, Threats, Attacks, and Solutions(Mdpi, 2023) Aslan, Omer; Aktug, Semih Serkant; Ozkan-Okay, Merve; Yilmaz, Abdullah Asim; Akin, ErdalInternet usage has grown exponentially, with individuals and companies performing multiple daily transactions in cyberspace rather than in the real world. The coronavirus (COVID-19) pandemic has accelerated this process. As a result of the widespread usage of the digital environment, traditional crimes have also shifted to the digital space. Emerging technologies such as cloud computing, the Internet of Things (IoT), social media, wireless communication, and cryptocurrencies are raising security concerns in cyberspace. Recently, cyber criminals have started to use cyber attacks as a service to automate attacks and leverage their impact. Attackers exploit vulnerabilities that exist in hardware, software, and communication layers. Various types of cyber attacks include distributed denial of service (DDoS), phishing, man-in-the-middle, password, remote, privilege escalation, and malware. Due to new-generation attacks and evasion techniques, traditional protection systems such as firewalls, intrusion detection systems, antivirus software, access control lists, etc., are no longer effective in detecting these sophisticated attacks. Therefore, there is an urgent need to find innovative and more feasible solutions to prevent cyber attacks. The paper first extensively explains the main reasons for cyber attacks. Then, it reviews the most recent attacks, attack patterns, and detection techniques. Thirdly, the article discusses contemporary technical and nontechnical solutions for recognizing attacks in advance. Using trending technologies such as machine learning, deep learning, cloud platforms, big data, and blockchain can be a promising solution for current and future cyber attacks. These technological solutions may assist in detecting malware, intrusion detection, spam identification, DNS attack classification, fraud detection, recognizing hidden channels, and distinguishing advanced persistent threats. However, some promising solutions, especially machine learning and deep learning, are not resistant to evasion techniques, which must be considered when proposing solutions against intelligent cyber attacks.
