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Modeling and Detection of Camouflaging Worm

Wei Yu, Xun Wang, P Calyam, Dong Xuan, Wei Zhao
2011 IEEE Transactions on Dependable and Secure Computing  
In this paper, we investigate a new class of active worms, referred to as Camouflaging Worm (C-Worm in short).  ...  Thereby, the C-Worm camouflages its propagation from existing worm detection systems based on analyzing the propagation traffic generated by worms.  ...  MODELING OF THE C-WORM C-Worm The C-Worm camouflages its propagation by controlling scan traffic volume during its propagation.  ... 
doi:10.1109/tdsc.2010.13 fatcat:kio52jalsjfvlagjl6qxymvmya

A NOVEL APPROACH FOR MODELING AND DETECTION OF CAMOUFLAGING WORM

Vivek Dubale, Syed, Kulkarni
2015 unpublished
Thereby, the C-Worm camouflages its propagation from existing worm detection systems based on analyzing the propagation traffic generated by worms.  ...  We analyze characteristics of the C-Worm and conduct a comprehensive comparison between its traffic and non-worm traffic (background traffic).  ...  CONCLUSIONS This is how we can implement the system for Modeling and Detection of Camouflaging Worm and we can overcome the problems with the existing system like Existing detection schemes are based on  ... 
fatcat:q7zbcwtchzesbp2hiouy36wcjy

C-Worm Traffic Detection using Power Spectral Density and Spectral Flatness Measure

Sushma Mergu
2012 IOSR Journal of Computer Engineering  
The empirical results revealed that our schemes are effecting in detecting camouflaging worms effectively besides identifying normal worms.  ...  However, there is a new type of worm that can camouflage itself so as to prevent anti worm software from identifying it.  ...  In the process of modeling camouflaging worm, the following characteristics are followed.  The traffic of C-worm is similar to non-worm traffic in terms of time domain.  ... 
doi:10.9790/0661-0434651 fatcat:2olczjl4kjhf7htauownlqhvfa

On Detecting Camouflaging Worm

Wei Yu, Xun Wang, Prasad Calyam, Dong Xuan, Wei Zhao
2006 Proceedings of the Computer Security Applications Conference  
We analyze characteristics of the C-Worm and conduct a comprehensive comparison between its traffic and non-worm traffic.  ...  Active worms pose major security threats to the Internet. In this paper, we investigate a new class of active worms, i.e., Camouflaging Worm (C-Worm in short).  ...  ACI-0329155 and CCF-0546668.  ... 
doi:10.1109/acsac.2006.36 dblp:conf/acsac/YuWCXZ06 fatcat:lst4zidnhzhmrbblxvvzyxubti

A Tour of the Computer Worm Detection Space

Nelson Ochieng, Waweru Mwangi, Ismael Ateya
2014 International Journal of Computer Applications  
This is partly because of the difficulty of accurately modeling either the normal behavior of computer networks or the malicious actions of computer worms.  ...  This paper presents a literature review on the worm detection techniques, highlighting the worm characteristics leveraged for detection and the limitations of the various detection techniques.  ...  In both, the challenge is to build models that are simultaneously complete (that is, the model allows detection of all malicious activities) and accurate (that is, model detects only malicious activities  ... 
doi:10.5120/18169-9045 fatcat:cbddkayh7bfdtpcqdbjugu6iay

A malware propagation model considering software diversity and topology dynamics

Soodeh Hosseini, Mohammad Abdollahi Azgomi, Adel Torkaman Rahmani
2014 2014 11th International ISC Conference on Information Security and Cryptology  
Here we find a new class of active worms, called as Camouflaging Worm (C-Worm).  ...  Our scheme uses the Power Camouflaging Worm distribution of the scan traffic volume and its corresponding Spectral Flatness Measure (SFM) to distinguish the C-Worm traffic from background traffic Using  ...  Many active worms are used to infect a large detection and defense mechanisms against worms [2] . number of computers and change them as bots or A network based worm detection system plays a zombies,  ... 
doi:10.1109/iscisc.2014.6994025 dblp:conf/iscisc/HosseiniAR14 fatcat:wp6poajfsffz3hryyyggbb5a4e

Spam and denial of information attacks and defenses

Carlton Pu, John P. Imlay
2009 Proceedings of the 5th Annual Workshop on Cyber Security and Information Intelligence Research Cyber Security and Information Intelligence Challenges and Strategies - CSIIRW '09  
., misspellings of VIAGRA) that only appear in spam messages, whether they are camouflaged or not.  ...  Extended Abstract Introduction and Motivation Automated Denial of Information Attacks.  ...  Other recent examples of DOI attacks include the work on misleading worm signature generators [7] and intrusion techniques that attempt to remain below the detection threshold of Intrusion Detection  ... 
doi:10.1145/1558607.1558613 dblp:conf/csiirw/PuI09 fatcat:assxjd3azjgdjcej2rzicyo46e

Interactive Evolution of Camouflage

Craig Reynolds
2011 Artificial Life  
This paper presents an abstract computation model of the evolution of camouflage in nature.  ...  Nested expressions of generators and operators form a texture description language. Natural evolution is represented by genetic programming, a variant of the genetic algorithm.  ...  Some of the names are self-descriptive, for oth-ers, and for description of parameter types for each, see (Reynolds, 2009  ... 
doi:10.1162/artl_a_00023 pmid:21370960 fatcat:jgqhpwphjnho3blnxuh2p7alxu

Detecting and Classifying Morphed Malwares: A Survey

Sanjam Singla, Ekta Gandotra, Divya Bansal, Sanjeev Sofat
2015 International Journal of Computer Applications  
These obscure methods cannot completely impede analysis, but it prolongs the process of analysis and detection.  ...  In this era, most of the antivirus companies are facing immense difficulty in detecting morphed malwares as they conceal themselves from detection.  ...  A framework presented in [51] for polymorphic worm detection was worth mentioning, as it uses byte-pattern-based signatures and graph based classification framework of content based polymorphic worm  ... 
doi:10.5120/21738-4937 fatcat:ryuz3x62jncflnjppysikvyafa

Learning Entropy [chapter]

Lele Zhang, Darryl Veitch
2011 Lecture Notes in Computer Science  
To illustrate the potential pitfalls, we give an in-principle analysis of network attack detection, in which we design a camouflage technique and show analytically that it can perfectly mask attacks from  ...  entropy based detector with low costs in terms of the volume of traffic brought in for camouflage.  ...  In this vein, [3, 5] used entropy of source IP address distributions to capture DDoS attacks, and [10] focused on worm detection using distributions from packet headers.  ... 
doi:10.1007/978-3-642-20757-0_2 fatcat:tvcjz3foqffcpl5xmqqwxustti

Camouflage in predators

Matilda Q. R. Pembury Smith, Graeme D. Ruxton
2020 Biological Reviews  
Camouflage - adaptations that prevent detection and/or recognition - is a key example of evolution by natural selection, making it a primary focus in evolutionary ecology and animal behaviour.  ...  Although many of the same principles of camouflage studied in prey translate to predators, differences between the two groups (in motility, relative size, and control over the time and place of predation  ...  Such models may provide insights into other motion camouflage mechanisms, and perhaps facilitate the development of new military or security applications. IV.  ... 
doi:10.1111/brv.12612 pmid:32410297 fatcat:txbkgchirnhntp56qoglazyppy

Scada Malware, a Proof of Concept [chapter]

Andrea Carcano, Igor Nai Fovino, Marcelo Masera, Alberto Trombetta
2009 Lecture Notes in Computer Science  
(2) ModBUS COM Worm -Attack Scope -The scope of the Com Worm attack is to take the control of the slaves of the process control architecture by taking advantage of the lack of authentication and integrity  ...  : -SCADA Intrusion Detection System -Secure SCADA protocols Old Operating Systems: Need for new Models -Need for new Risk assessment methods -Need for new experimental -studies -Infection Triggers: Experimental  ... 
doi:10.1007/978-3-642-03552-4_19 fatcat:kv3wtoaw7zecza35qquj75mxvy

Utilization Data Mining to Detect Spyware

Parisa Bahraminikoo
2012 IOSR Journal of Computer Engineering  
With the development of malware detection systems and Artificial Intelligence, as a new technology for them, Artificial Intelligence has been applied in anti-virus engines.  ...  Malware can be a virus, worm, Trojan, adware, spyware, root kit, etc.Spyware is a type of malware (malicious software) installed on computers that collects information about users without their knowledge  ...  The detection and evasion of such black holes and wormholes in an ad-hoc network is still considered as future challenging task.  ... 
doi:10.9790/0661-0430104 fatcat:syohb2g2lzhznpjjvbsxqgwlca

Optimizing Computer Worm Detection Using Ensembles

Nelson Ochieng, Waweru Mwangi, Ismail Ateya
2019 Security and Communication Networks  
The scope of this research is computer worm detection. Computer worm has been defined as a process that can cause a possibly evolved copy of it to execute on a remote computer.  ...  Modern computer worm authors obfuscate the code to make it difficult to detect the computer worm. This research proposes to use machine learning methodology for the detection of computer worms.  ...  Defense against computer worm attacks may be through prevention of worm attacks, detection of worms, containment of worm spread and removal of worm infections.  ... 
doi:10.1155/2019/4656480 fatcat:cbgjtdd5lbexld37zpwawa4ayy

LEAPS: Detecting Camouflaged Attacks with Statistical Learning Guided by Program Analysis

Zhongshu Gu, Kexin Pei, Qifan Wang, Luo Si, Xiangyu Zhang, Dongyan Xu
2015 2015 45th Annual IEEE/IFIP International Conference on Dependable Systems and Networks  
Our extensive evaluation shows that, compared with pure statistical learning models, LEAPS achieves consistently higher accuracy when detecting real-world camouflaged attacks with benign program cover-up  ...  In light of these limitations, we have developed LEAPS, an attack detection system based on supervised statistical learning to classify benign and malicious system events.  ...  Any opinions, findings, and conclusions in this paper are those of the authors only and do not necessarily reflect the views of our sponsors.  ... 
doi:10.1109/dsn.2015.34 dblp:conf/dsn/GuPWSZX15 fatcat:tsehffrqgzfethfqwbsyxhzoki
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