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Efficient Malware Detection in Cybersecurity: Leveraging Advanced Data Structures for Enhanced Threat Identification
Abstract: The cybersecurity landscape is constantly changing with more advanced malware creating major challenges for detection systems. To address these challenges effectively, advanced data structures have become essential in optimizing how data is managed, processed, and analyzed for malware detection. This review paper delves into the role of several cutting-edge data structures—bloom filters, tries, hash tables, graphs, decision trees, and suffix trees—in enhancing the efficiency and accuracy of malware detection mechanisms. …
Published in International Journal of Data Structure Studies · Vol. 2, Issue 2, 2024 · pp. 32–40 Read article
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Novel Perspectives in Quantum Safe Crypto algorithms for Enhanced Cyber Security
Abstract: This paper explores novel perspectives in quantum-safe cryptographic algorithms to bolster cybersecurity in the face of impending quantum computing advancements. Due to the efficient resolution of intricate mathematical problems by quantum computers, posing a substantial threat to existing cryptographic systems, there is a pressing requirement to create resilient alternatives. This study delves into innovative approaches, drawing from quantum-resistant cryptographic primitives, lattice-based cryptography, code-based cryptography, and hash-based cryptography. By examining the …
Published in International Journal of Computer Science Languages · Vol. 1, Issue 2, 2023 · pp. 18–22 Read article