Maikel Leon, Department of Business Technology, Miami Herbert Business School, University of Miami, Florida, USA
Innovations that combine the interpretability of symbolic AI with the learning capabilities of sub-symbolic AI can flourish in the nexus of symbolic and sub-symbolic AI. This research presents Fuzzy Cognitive Maps (FCMs). This hybrid model combines the best features of both paradigms as a workable answer to the problems of interpretability and explainability in artificial intelligence (AI) systems. FCMs have become a robust framework for logically and intuitively supporting decision-making processes and expressing causal information. A more organic and adaptable problem-solving approach is made possible by FCMs’ ability to manage the inherent ambiguity and uncertainty present in real-world situations. Because of their innate flexibility and ability to learn and adapt from sub-symbolic AI, FCMs are an excellent fit for applications requiring high interpretability and explainability.
Fuzzy Cognitive Maps, Symbolic AI, and Sub-symbolic AI.
KLODIAN LIPA
Protecting personal information privacy has become a controversial issue among online social network providers and users. Most social network providers have developed several techniques to decrease threats and risks to the users’ privacy. These risks include the misuse of personal information which may lead to illegal acts such as identity theft. This study aims to measure the awareness of users on protecting their personal information privacy, as well as the suitability of the privacy systems which they use to modify privacy settings. Survey results show high percentage of the use of smart phones for web services but the current privacy settings for online social networks need to be improved to support different type of mobile phones screens. Because most users use their mobile phones for Internet services, privacy settings that are compatible with mobile phones need to be developed. The method of selecting privacy settings should also be simplified to provide users with a clear picture of the data that will be shared with others.
Smart Mobile Phone, Social Networks, Mobile Network, Privacy, Personal Information.
Naga Satya Praveen Kumar Yadati
The dynamic field of cybersecurity has seen a surge in sophisticated cyber threats, necessitating advanced detection and mitigation strategies. This paper explores various advanced threat detection methodologies, including machine learning algorithms, behavioral analytics, threat intelligence feeds, and deception technologies. By adopting these cutting-edge techniques, organizations can significantly enhance their ability to detect and respond to complex cyber threats, thereby securing their digital assets more effectively.
cybersecurity, threat detection, machine learning, artificial intelligence, behavioral analytics, threat intelligence, deception technologies, endpoint detection, network traffic analysis, continuous monitoring..
Hemnath shreeharan D, Shri Vindhya A, Department of Computer Science Engineering, Saveetha School of Engineering, Chennai, Tamil Nadu, India
In a now more mature market for Small and Medium-sized Enterprises (SMEs), The objective of this study is to use cryptographic algorithms, namely (Message-Digest 5 (MD5) and El Gamal), for improving the operating performance in SMEs. In this research, the performance improvement and security robustness of ten heterogeneous systems over two cryptographic schemes are evaluated in respect to cost savings by comparing them with that of a recently published hashing technique. Compared with the simple and fast md5 elaboration, we find for example that of El Gamal whose construction involves a higher degree of security but which has greater computational / financial costs. This research highlighted that with MD5, SMEs could obtain certain immediate benefits in terms of improvements apart from lowering costs but as an entire data integrity and security is a must for long term; hence adopting El Gamal would serve them best dealing especially the places where devising useful information matters crucial. For SMEs it provides an informed choice on which crypto scheme to choose depending upon their requirements, efficiency and cost against security.
Small and Medium-sized Enterprises (SMEs), Cryptographic algorithms, Efficiency, Financial inclusion, Security, Computational cost, Performance gains, Operational agility.
