Cite this DOI

Venkata Suryanarayana, P., & Surendra, K. (2017). Malware Propagation in Large-Scale Networks. *Journal of Science & Technology*, *02*(04), 46–48. https://doi.org/10.46243/jstj.2017.v2.i4.212

@article{venkatasuryanarayana2017malware,
  author    = {Venkata Suryanarayana, Palati and Surendra, Kalagara},
  title     = {{Malware Propagation in Large-Scale Networks}},
  journal   = {Journal of Science \& Technology},
  year      = {2017},
  month     = {jul},
  volume    = {02},
  number    = {04},
  pages     = {46--48},
  publisher = {Longman Publishers},
  issn      = {2456-5660},
  doi       = {10.46243/jstj.2017.v2.i4.212},
  url       = {https://doi.org/10.46243/jstj.2017.v2.i4.212},
  language  = {en},
  abstract  = {Malware is prevalent in networks, and creates a condemnatory warning to network safety. However, we have very little grasp of malware performance in networks till date. In this project, we scrutinize how malware spread in networks from a global viewpoint. We construct the problem, and organize an accurate two layer outbreak model for malware spreading from network to network. Based on the submitted model, our inspection specifies that the dispensation of a given malware follows exponential dispensation, power law dispensation with a short exponential tail, and power law dispensation at its primarily, late and last phases, . Large Scale tests have been executed between two real-world comprehensive malware data sets and the outcome confirm our conceptual detections.}
}

TY  - JOUR
TI  - Malware Propagation in Large-Scale Networks
AU  - Venkata Suryanarayana, Palati
AU  - Surendra, Kalagara
JO  - Journal of Science & Technology
PY  - 2017
DA  - 2017/07/14/
VL  - 02
IS  - 04
SP  - 46
EP  - 48
PB  - Longman Publishers
SN  - 2456-5660
LA  - en
AB  - Malware is prevalent in networks, and creates a condemnatory warning to network safety. However, we have very little grasp of malware performance in networks till date. In this project, we scrutinize how malware spread in networks from a global viewpoint. We construct the problem, and organize an accurate two layer outbreak model for malware spreading from network to network. Based on the submitted model, our inspection specifies that the dispensation of a given malware follows exponential dispensation, power law dispensation with a short exponential tail, and power law dispensation at its primarily, late and last phases, . Large Scale tests have been executed between two real-world comprehensive malware data sets and the outcome confirm our conceptual detections.
DO  - 10.46243/jstj.2017.v2.i4.212
UR  - https://doi.org/10.46243/jstj.2017.v2.i4.212
ER  -

{
    "type": "article-journal",
    "id": "10.46243/jstj.2017.v2.i4.212",
    "DOI": "10.46243/jstj.2017.v2.i4.212",
    "URL": "https://doi.org/10.46243/jstj.2017.v2.i4.212",
    "title": "Malware Propagation in Large-Scale Networks",
    "source": "Smart Scholars DOI Registry",
    "container-title": "Journal of Science & Technology",
    "author": [
        {
            "family": "Venkata Suryanarayana",
            "given": "Palati"
        },
        {
            "family": "Surendra",
            "given": "Kalagara"
        }
    ],
    "issued": {
        "date-parts": [
            [
                2017,
                7,
                14
            ]
        ]
    },
    "volume": "02",
    "issue": "04",
    "page": "46-48",
    "publisher": "Longman Publishers",
    "language": "en",
    "abstract": "Malware is prevalent in networks, and creates a condemnatory warning to network safety. However, we have very little grasp of malware performance in networks till date. In this project, we scrutinize how malware spread in networks from a global viewpoint. We construct the problem, and organize an accurate two layer outbreak model for malware spreading from network to network. Based on the submitted model, our inspection specifies that the dispensation of a given malware follows exponential dispensation, power law dispensation with a short exponential tail, and power law dispensation at its primarily, late and last phases, . Large Scale tests have been executed between two real-world comprehensive malware data sets and the outcome confirm our conceptual detections.",
    "ISSN": "2456-5660"
}

From the record as registered (version 2) — the record and its history. Programs: https://registry.smartscholars.in/api.php?action=cite&doi=10.46243%2Fjstj.2017.v2.i4.212 gives all four in one JSON answer.