Zobrazeno 1 - 10
of 669
pro vyhledávání: '"Shukla Sandeep"'
The rise in cybercrime and the complexity of multilingual and code-mixed complaints present significant challenges for law enforcement and cybersecurity agencies. These organizations need automated, scalable methods to identify crime types, enabling
Externí odkaz:
http://arxiv.org/abs/2412.16614
The current state of Advanced Persistent Threats (APT) attribution primarily relies on time-consuming manual processes. These include mapping incident artifacts onto threat attribution frameworks and employing expert reasoning to uncover the most lik
Externí odkaz:
http://arxiv.org/abs/2409.16400
The use of multi-threading and file prioritization methods has accelerated the speed at which ransomware encrypts files. To minimize file loss during the ransomware attack, detecting file modifications at the earliest execution stage is considered ve
Externí odkaz:
http://arxiv.org/abs/2409.11428
Advanced Persistent Threat (APT) attribution is a critical challenge in cybersecurity and implies the process of accurately identifying the perpetrators behind sophisticated cyber attacks. It can significantly enhance defense mechanisms and inform st
Externí odkaz:
http://arxiv.org/abs/2409.11415
Publikováno v:
Digital Threats: Research and Practice (2024)
Understanding the modus operandi of adversaries aids organizations in employing efficient defensive strategies and sharing intelligence in the community. This knowledge is often present in unstructured natural language text within threat analysis rep
Externí odkaz:
http://arxiv.org/abs/2403.03267
Land, being a scarce and valuable resource, is in high demand, especially in densely populated areas of older cities. Development authorities require land for infrastructure projects and other amenities, while landowners hold onto their land for both
Externí odkaz:
http://arxiv.org/abs/2308.05950
This research article critically examines the potential risks and implications arising from the malicious utilization of large language models(LLM), focusing specifically on ChatGPT and Google's Bard. Although these large language models have numerou
Externí odkaz:
http://arxiv.org/abs/2305.15336
The explosive growth of non-fungible tokens (NFTs) on Web3 has created a new frontier for digital art and collectibles, but also an emerging space for fraudulent activities. This study provides an in-depth analysis of NFT rug pulls, which are fraudul
Externí odkaz:
http://arxiv.org/abs/2304.07598
The metadata aspect of Domain Names (DNs) enables us to perform a behavioral study of DNs and detect if a DN is involved in in-browser cryptojacking. Thus, we are motivated to study different temporal and behavioral aspects of DNs involved in cryptoj
Externí odkaz:
http://arxiv.org/abs/2205.04685