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    A Comprehensive Review of Cyber Security Vulnerabilities, Threats, Attacks, and Solutions
    (Mdpi, 2023) Aslan, Omer; Aktug, Semih Serkant; Ozkan-Okay, Merve; Yilmaz, Abdullah Asim; Akin, Erdal
    Internet 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.
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    A Novel Blockchain-Based Scientific Publishing System
    (Mdpi, 2023) Bestas, Mansur; Tas, Ruhi; Akin, Erdal; Ozkan-Okay, Merve; Aslan, Omer; Aktug, Semih Serkant
    The scientific publishing industry is dominated by a few publishers that use centralized systems, which decrease the quality of studies and make the publication process longer. Traditional publication systems generally have high publication costs, slow and biased review processes, copyrights held by publishers, lack of rewards for contributors, lack of connection among researchers, etc. Accordingly, we propose a decentralized blockchain-based scientific publication platform to eliminate the traditional publication system deficiencies. The proposed system uses Ethereum smart contracts to accelerate the publication process and abate the biased evaluation process while reducing the publication cost. The proposed model also improves the quality of scientific studies by adding new features to the publication process. The proposed system increases the number of publishers, makes the publication process fully traceable, and makes scientific papers globally available to anyone with a small fee. In addition, the system provides journals with decentralized models and integrates scientific papers with related data or datasets. The editors, reviewers, and cited authors are also rewarded. The proposed system has been implemented using Ethereum Virtual Machine (EVM), which consists of a front-end, middleware, and back-end. When an author submits a manuscript for evaluation, the system automatically finds the most appropriate editors and reviewers for related fields. After the publication process finishes, editors, reviewers, cited authors, and other contributors are rewarded as a system token-based cryptocurrency.
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    EVALUATION OF FOREIGN DIRECT INVESTMENTS IN AGRICULTURAL SECTOR IN NORTHERN IRAQ
    (Mehmet Akif Ersoy Univ, 2019) Aktug, Semih Serkant; Dag, Mehmet; Hama, Mahir Rashid
    Foreign Direct Investment (FDI), considered as a significant source of economic growth in both developed and developing countries. In Northern Iraq, it is planned to make a friendly investment environment to attract FDI as much as possible toward its region to enhance development acceleration. This study evaluates the main obstacles or factors that deter foreign investors from investing in the region's agricultural sector. In the study, in addition to a general assessment of the investments in the agricultural sector of the region, the main reasons for the fact that FDI has not increased significantly in the last decade in the region in the 2006-2016 period is also evaluated.