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8. ANOMALY DETECTION ON FLOWS AND INCOMING PACKETS WITH GAUSSIAN MIXTURES

Author

Barton, Armon C., Singh, Gurminder, Computer Science (CS), Menon, Tarun, Barton, Armon C., Singh, Gurminder, Computer Science (CS), and Menon, Tarun

Abstract

Firewalls are key for maintaining a secure network, but it cannot be assumed that network traffic that manages to get through one is completely safe. Anomaly detection refers to methods that can be used to discover unique or uncommon occurrences within a particular dataset. Unsupervised machine learning techniques involve machine learning with unlabeled data, and can be utilized in order to perform anomaly detection by ingesting a given set of data and finding instances that diverge from the rest in meaningful ways that may not be obvious to the human eye. In this study we aim to analyze anomalies that are detected in incoming packet and flow network traffic data that successfully passed through a firewall and determine what significance there may be within such anomalies. Considering the vast amount of malicious traffic that exists and gets generated regularly, this study shows that Gaussian Mixtures can be used for discovery of anomalies within network traffic that passed through a firewall to discover potential undesirable or malicious traffic., Civilian, Approved for public release. Distribution is unlimited.

Published
2023

9. ANOMALY DETECTION ON FLOWS AND INCOMING PACKETS WITH GAUSSIAN MIXTURES

Author

Menon, Tarun, Barton, Armon C., Singh, Gurminder, and Computer Science (CS)

Subjects
network traffic analysis, Gaussian Mixtures, cyber, unsupervised learning, anomaly detection
Abstract

Firewalls are key for maintaining a secure network, but it cannot be assumed that network traffic that manages to get through one is completely safe. Anomaly detection refers to methods that can be used to discover unique or uncommon occurrences within a particular dataset. Unsupervised machine learning techniques involve machine learning with unlabeled data, and can be utilized in order to perform anomaly detection by ingesting a given set of data and finding instances that diverge from the rest in meaningful ways that may not be obvious to the human eye. In this study we aim to analyze anomalies that are detected in incoming packet and flow network traffic data that successfully passed through a firewall and determine what significance there may be within such anomalies. Considering the vast amount of malicious traffic that exists and gets generated regularly, this study shows that Gaussian Mixtures can be used for discovery of anomalies within network traffic that passed through a firewall to discover potential undesirable or malicious traffic. Civilian Approved for public release. Distribution is unlimited.

Published
2023

12. Kerala Bird Atlas 2015–20: features, outcomes and implications of a citizen-science project

Author

Praveen, J., primary, Nameer, P. O., additional, Jha, Ashish, additional, Aravind, Anish, additional, Dilip, K. G., additional, Karuthedathu, Dipu, additional, Tom, George, additional, Mavelikara, Hari, additional, Mannar, Harikumar, additional, Palot, Jafer, additional, Johnson, Jaichand, additional, Jishnu, R., additional, Rodrigues, K. Maxim, additional, Mujeeb, P. M., additional, Namassivayan, L., additional, Payyeri, Naveelal, additional, Nesrudheen, P. P., additional, Narayanan, S. Prasanth, additional, Prasanth, S. S., additional, Krishna, M. C. Prashantha, additional, Praveen, E. S., additional, Velayudhan, Praveen, additional, Reghuvaran, Premchand, additional, Kidoor, Raju, additional, Rathish, R. L., additional, Roshnath, R., additional, Sashikumar, C., additional, Meppayur, Satyan, additional, Sivakumar, A. K., additional, Sreedevi, A. K., additional, Sreekumar, B., additional, Sreekumar, E. R., additional, Sumesh, P. B., additional, Venugopal, R., additional, Venugopal, Vinod, additional, Vishnudas, C. K., additional, Kartha, Vishnupriyan, additional, Puliyeri, Vivek, additional, Quader, Suhel, additional, Reddy, Abinand, additional, Puthiyeri, Abdul Raheem, additional, Riyas, K. Abdul, additional, Abhijith, R. S., additional, Surendran, Abhijith, additional, Sunil, Abhin M., additional, Chandran, Abhinand, additional, Abhirami, C., additional, Jayakumar, Abhirami M., additional, Peter, Abhishek Sebastian, additional, Muhammed, N. V. Afreed, additional, Katakath, Afthab Faisal, additional, Ajai, P., additional, Raju, Aju K., additional, Akhil, P. M., additional, Akhil, U. S., additional, Amal, U. S., additional, Menon, Anamika, additional, Ansari, Anas Ibinu, additional, Aneesh, K. S., additional, Aneesh, S., additional, Hari, C. Anjana, additional, Anjitha, R., additional, Raj, P. N. Anoop, additional, John, Anu, additional, Varma, Anuradha, additional, Anushreedha, S. S., additional, Aravind, C. K., additional, Ramachandran, Arjun, additional, Arun, B., additional, George, Arun, additional, Gopi, Arun P., additional, Varghese, Arun, additional, Vinod, Arya, additional, Shaji, Ashley, additional, Raj, V. M. Ashok, additional, Viswanathan, Ashwin, additional, Mohammed, Aslam, additional, Aswin, A., additional, Aswin, K. S., additional, Ali, A. Azhar, additional, Balaji, P. B., additional, Paul, M. Bibin, additional, Shree, J. Chaithra, additional, Venkatraman, Chandrasekaran, additional, Charutha, K., additional, Jose, Clareena T., additional, Jose, Clince P., additional, Singh, Dalip, additional, Sanghamithra, Devika, additional, Sikarwar, Digvijay Singh, additional, Murukesh, Divin, additional, Divin, V., additional, Arief, Fauzia, additional, Mandal, Jaydev, additional, Sarlin, P. J., additional, Nafar, A. Adil, additional, Bachan, K. H. Amitha, additional, Rejitha, V., additional, Dev, R. S. Vishnu, additional, Rowther, B. Elias, additional, Raja, Firosh, additional, Iyer, Geetha, additional, George, Ginu, additional, Gireesan, T. U., additional, Mohan, P. K. Girish, additional, Dsouza, Glen Preetesh, additional, Govind, G., additional, Greeshma, P., additional, Prasad, P. M. Hari, additional, Hariharan, T. V., additional, Harith, A., additional, Harith, C., additional, Hemanth, B., additional, Mohamed, Ijaas, additional, David, J. Patrick, additional, Jain, P. K., additional, Jameela, P., additional, Jayakrishnan, G., additional, Jishnu, K., additional, Jismi, M. O., additional, Johnson, Jithin, additional, Soniya, C. Joel, additional, Babu, Jose Rani, additional, Roy, Joseph, additional, Nelson, Jyothish, additional, Krishnan, M. Jyothi, additional, Bhandary, K. Pranav, additional, Jamaludheen, K. M., additional, Ravi, Kavingal, additional, Thrikkadeeri, Karthik, additional, Nair, Kausthubh K., additional, Kiran, B. S., additional, Kumar, Kiran S., additional, Raj, D. Kishore, additional, Panaganti, Kishore Kumar, additional, Moorthy, M. Krishna, additional, Murthy, R. Krishna, additional, Krishnanunni, M. R., additional, Prabhakaran, Latha, additional, Lathika, K. K., additional, Abraham, Libin, additional, Narayanan, G. Hari, additional, Panigrahi, Madhumita, additional, Manav, S., additional, Karingamadathil, Manoj, additional, Manoj, T. R., additional, Thomas, Manu, additional, Manuel, P. P., additional, Varghese, Mebin George, additional, Chandran, P. Megha, additional, Sulaiman, M. Mohammad, additional, Madathil, Mohammed Ashif, additional, Hirash, V. K. Mohammed, additional, Ramees, K. Mohammed, additional, Thirunnavaya, M. Sadique, additional, Niyas, A. P. Muhammed, additional, Muhasin, C. T., additional, Kizhakkemadham, Mukundan, additional, Azeez, Naseerudheen Abdul, additional, Nikhil, P. V., additional, Niranjana, C., additional, Mundekad, Nisha, additional, Mohan, Nithin, additional, Pavithra, A., additional, Viswanathan, Poornima, additional, Pramod, P., additional, Prakash, G., additional, Prasath, S., additional, Prakash, Prasoon, additional, Preethi, N., additional, Rajeevan, Rahul, additional, Rajaguru, M., additional, Rajarajan, V., additional, Sankaran, Raju, additional, Ratheesh, K., additional, Crasta, Rayan Pradeep, additional, Mohan, Remya, additional, Renju, Anon, additional, Koshy, Robin C., additional, Rai, Rohan, additional, Tom, Roshin, additional, Chandran, Sachin, additional, Sachinkrishna, M. V., additional, Ali, M. V. Saeed Anvar, additional, Siril, Sajitha, additional, Bharadwaj, D. D. Samarth, additional, George, Samuel, additional, Morris, Sancia, additional, Augustine, Sandeep, additional, Das, Sandeep K., additional, Morris, Sandie, additional, Sandra, P. R., additional, Sanuraj, T. K., additional, Sawant, Saurabh, additional, Morris, Savio, additional, Selvaganesh, K., additional, Shahil, K., additional, Shahina, N. N., additional, Valasy, Shahul, additional, Siji, P. K., additional, Joseph, Siju, additional, Sivashankar, R., additional, Karim, Siyad A., additional, Mohan, Sreehari K., additional, Pillai, Sreehari M., additional, Sowmiya, M. Sri, additional, Srinila, K. T., additional, Subin, K. S., additional, Sujith, V. G., additional, Sukumaran, Suryamol, additional, Syamili, M. S., additional, Menon, Tarun, additional, Praveen, Tejas, additional, Thilak, S. A., additional, Antony, Tony, additional, Ullas, U. R, additional, Sivaji, Vinod Ooralath, additional, Narayanan, Vishnu, additional, Sreejith, M. Vishnu, additional, Chandran, A. Vivek, additional, Sudhakaran, Vivek, additional, Vridhi, R., additional, Humam, Wahiba Irshad, additional, Uchummal, Yadukrishna J., additional, and Yathumon, M. A., additional

Published
2022
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17. Q. leucotrichophora Forest as a Bird Habitat in the Western Himalayas .

Author

Shahabuddin, Ghazala and Menon, Tarun

Subjects
*OAK, *FOREST birds, *BIRD habitats, *HARDWOOD forests
Abstract

The Western Himalayas harbor high floral and faunal diversity due to diverse biogeographical influences and steep altitudinal gradients that nurture numerous forest types. Quercus leucotrichophora (banj oak) forests (1,500 m to 2,200 m.a.s.l.) form part of the moist, temperate, broadleaf forest biome located in the middle elevations of the Western Himalayas. Based on our research in Q. leucotrichophora forests from 2013 to 2019, we describe their avifauna with reference to taxonomic and functional diversity, seasonality, habitat specialization, and endemism. We then describe our recent findings on the influence of anthropogenic disturbances on oak forest birds in this human-dominated landscape. Over six years of observation we have recorded as many as 135 species of birds in this forest habitat, including year-round residents, summer migrants (breeders), winter migrants and passage migrants. An overwhelming proportion of forest birds (78.5%) are insectivores – both obligate and facultative. The abundance and diversity of insects and other invertebrates can be attributed to the complex branching pattern of oak, the lush canopy of oak forest, the moist duff layer and general plant diversity of these forests. Between 37% and 44% of the bird species recorded in oak forest are hardwood forest specialists in this elevational range and between 51% and 63% are forest generalists. There are a total of 17 Himalayan endemics and 4 narrow endemics that occur only in the Central-Western Himalayas. Bird abundance and diversity are adversely affected by Q. leucotrichophora forest degradation; insectivores and forest specialists were found to be most vulnerable. Reduction in canopy cover, landscape proportion of forest, vertical stratification and under story shrub density, as a result of forest degradation, most strongly affect forest birds. It is necessary to implement sustainable extraction measures and maintain old, protected oak stands if this diverse avifaunal assemblage is to be conserved. [ABSTRACT FROM AUTHOR]

Published
2021

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