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VMM-based hidden process detection and identification using Lycosid

Stephen T. Jones, Andrea C. Arpaci-Dusseau, Remzi H. Arpaci-Dusseau
2008 Proceedings of the fourth ACM SIGPLAN/SIGOPS international conference on Virtual execution environments - VEE '08  
In this paper, we describe, implement, and evaluate a novel VMM-based hidden process detection and identification service called Lycosid that is based on the cross-view validation principle.  ...  In contrast to previous VMM-based hidden process detectors, Lycosid obtains guest process information implicitly.  ...  Acknowledgments We would like to thank the anonymous reviewers for their thoughtful comments and suggestions.  ... 
doi:10.1145/1346256.1346269 dblp:conf/vee/JonesAA08 fatcat:3igcjjy6r5dcljjxxlvd624nwi

Hidden Costs and the Role of Modularity: A Study on Offshoring Process Performance

Marcus M. Larsen
2013 Academy of Management Proceedings  
We narrow our focus on four capabilities and six processes that drive growth in NIVs. Our study points to the important role of  ...  We suggest that employee gender role perceptions and global mindsets influence these attitudes, which we examine within a Recent research suggests that the capabilities needed for new ventures to survive  ...  (For more information, please contact: Carine Peeters, Universite libre de Bruxelles, Belgium: Hidden Costs and the Role of Modularity: A Study on Offshoring Process Performance  ... 
doi:10.5465/ambpp.2013.16390abstract fatcat:qgexsh5fkjawppojjmj744l7fu

Attack Prediction using Hidden Markov Model [article]

Shuvalaxmi Dass, Prerit Datta, Akbar Siami Namin
2021 arXiv   pre-print
We propose the use of Hidden Markov Model (HMM) to predict the family of related attacks.  ...  Our proposed model is based on the observations often agglomerated in the form of log files and from the target or the victim's perspective.  ...  HMMs have been widely used in combination with intrusion detection systems (IDS) as an early-warning system for attack detection or for detecting anomalies in the network.  ... 
arXiv:2106.02012v1 fatcat:4ocqimgrszfurpqhxhbygvs4ga

Detecting falls with X-Factor Hidden Markov Models

Shehroz S. Khan, Michelle E. Karg, Dana Kulić, Jesse Hoey
2017 Applied Soft Computing  
We tested the proposed XHMM approaches on two activity recognition datasets and show high detection rates for falls in the absence of fall-specific training data.  ...  We propose three 'X-Factor' Hidden Markov Model (XHMMs) approaches. The XHMMs model unseen falls using "inflated" output covariances (observation models).  ...  [14] present an adaptive sensor network intrusion detection approach by human activity profiling.  ... 
doi:10.1016/j.asoc.2017.01.034 fatcat:b7aple5vezhwjn2bqqhu7ku4qe

A Novel Hidden Markov Model for Credit Card Fraud Detection

A. Prakash, C. Chandrasekar
2012 International Journal of Computer Applications  
In existing research they modelled the sequence of operations in credit card transaction processing using a Hidden Markov Model (HMM) and shown how it can be used for the detection of frauds.  ...  between the processes monitored by credit card detection system and the perfect normal processes.  ...  We presented an algorithm of fraud detection based on SHMM, which calculates the distance between the processes monitored by intrusion detection system and the perfect normal processes.  ... 
doi:10.5120/9532-3960 fatcat:lyl7vpmfrjagxlrw7glet2mxdy

Unexpected Inferences from Sensor Data: A Hidden Privacy Threat in the Internet of Things [chapter]

Jacob Kröger
2019 Springer Series in Materials Science  
This paper reviews existing evidence from the literature and discusses potential implications for consumer privacy.  ...  The presented findings call into question the adequacy of current sensor access policies.  ...  In order to enable consumers to remain in control of their personal data and understand the complex privacy implications of IoT sensor technology, information on data collection and processing must be  ... 
doi:10.1007/978-3-030-15651-0_13 fatcat:btx2dcjlpraitnoqcws2gh27lu

The Hidden Dimensions of Marketing

Gabriele Morello
1993 Market Research Society Journal  
Morello thanked each speaker for the words of appreciation, and stated that he will always be proud to be Professor Emeritus of the Vrije Universiteit.  ...  Morello also thanked the staff of the Faculty, with specific mention of Muriel Brummel and Veronica Bruijns for their help at administrative level.  ...  In search for the less explicit factors which make up the hidden dimensions of marketing, I suggest having a fresh look at the following aspects: marketing as a system; needs and wants, and the process  ... 
doi:10.1177/147078539303500401 fatcat:6kxrfqq7yrdwreryg6irfmqly4

The dept. of hidden stories

Gavin Wood, Linda Anderson, Adam Clarke, Peter C. Wright, John Vines, Madeline Balaam, Nick Taylor, Thomas Smith, Clara Crivellaro, Juliana Mensah, Helen Limon, John Challis
2014 Proceedings of the 32nd annual ACM conference on Human factors in computing systems - CHI '14  
Through a process of iterative design in collaboration with library staff and children's writers we designed DoHS to support the potential for playful storytelling through interactions with books.  ...  We detail the design of the Department of Hidden Stories (DoHS), a mobile-based game to support playful digital storytelling among primary school children in public libraries.  ...  ACKNOWLEDGEMENTS This research was funded by the AHRC Creative Exchange Knowledge Exchange Hub and the TSB ALIP 3/4 project SALT (2377-25137).  ... 
doi:10.1145/2556288.2557034 dblp:conf/chi/WoodVB0SCMLCACW14 fatcat:dbvrtppywjbhzptkjskifatjae

Knowing who to watch: Identifying attackers whose actions are hidden within false alarms and background noise

Howard Chivers, John A. Clark, Philip Nobles, Siraj A. Shaikh, Hao Chen
2010 Information Systems Frontiers  
rates are a standard metric for intrusion detection sensors.  ...  The paper provides a theoretical account of the process, a worked example, and a discussion of its practical implications.  ...  He is currently working on an EPSRC-funded project on System-Smart Intrusion Detection.  ... 
doi:10.1007/s10796-010-9268-7 fatcat:lrubrnjom5gurobk7jgxhjxwh4

The Hidden Punitiveness of Fines

Julia Quilter, Russell Hogg
2018 International Journal for Crime, Justice and Social Democracy  
We show that fines enforcement produces very real, but often hidden, hardships for the most vulnerable.  ...  The latter are being used for an increasing range of offences. This progressive 'monetization of justice' (O'Malley) and its effects have passed largely unnoticed.  ...  These processes can be highly consequential for some people.  ... 
doi:10.5204/ijcjsd.v7i3.512 fatcat:rtrkrugui5dozdvz3u2ee2wggq

The Hidden Punitiveness of Fines

Julia Ann Quilter, Russell Hogg
2018 International Journal for Crime, Justice and Social Democracy  
We show that fines enforcement produces very real, but often hidden, hardships for the most vulnerable.  ...  The latter are being used for an increasing range of offences. This progressive 'monetization of justice' (O'Malley) and its effects have passed largely unnoticed.  ...  These processes can be highly consequential for some people.  ... 
doi:10.5204/ijcjsd.v7i1.512 fatcat:prhcmbf4mndxdku6jq6hjsm7ua

A Hidden Markov Model Based Unsupervised Algorithm for Sleep/Wake Identification Using Actigraphy [article]

Xinyue Li, Yunting Zhang, Fan Jiang, Hongyu Zhao
2020 arXiv   pre-print
HMM can help expand the application of actigraphy in large-scale studies and in cases where intrusive PSG is hard to acquire or unavailable.  ...  In addition, the estimated HMM parameters can characterize individual activity patterns that can be utilized for further analysis.  ...  In the Discussion section, we conclude with the implications of our results and future research directions.  ... 
arXiv:1812.00553v2 fatcat:ifcv6saqcjasznyopfj7do3tzy

Learning genetic algorithm parameters using hidden Markov models

Jackie Rees, Gary J. Koehler
2006 European Journal of Operational Research  
We examine the parameter estimation process using estimation procedures for learning hidden Markov models, with mathematical models that exactly capture expected GA behavior.  ...  A lesser known but growing group of applications of GAs is the modeling of so-called "evolutionary processes", for example, organizational learning and group decision-making.  ...  intrusion detection for network security (Cho and Park, 2003) among others.  ... 
doi:10.1016/j.ejor.2005.04.045 fatcat:wylijsitxfdxbgkx5nt5yaldfm


D. García-Senz, C. Badenes, N. Serichol
2011 Astrophysical Journal  
Our aim is to use supernova remnant observations to constrain the single degenerate scenario for Type Ia supernova progenitors.  ...  Close to the edge of the hole, the Rayleigh-Taylor instability grows faster, leading to plumes that approach the edge of the forward shock.  ...  We thank the anonymous referee for the constructive critical comments that much improved the presentation of the manuscript.  ... 
doi:10.1088/0004-637x/745/1/75 fatcat:2v66ex75rne7zbhiqjfdyg4c24

Anomaly Detection via Feature-Aided Tracking and Hidden Markov Models

Satnam Singh, William Donat, Krishna Pattipati, Peter Willett, Haiying Tu
2007 2007 IEEE Aerospace Conference  
In this paper, we illustrate the capabilities of hidden Markov models (HMMs), combined with feature-aided tracking, for the detection of asymmetric threats.  ...  A procedure analogous to Page's test is used for the quickest detection of abnormal events.  ...  Hidden Markov models (HMMs) constitute a principal method for modeling partially-observed stochastic processes.  ... 
doi:10.1109/aero.2007.352797 fatcat:lhpnten5yjdtzb4c4jv5auzwae
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