A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2015; you can also visit the original URL.
The file type is application/pdf.
Filters
Research Methodology on Web Mining for Malware Detection
English
2014
International Journal of Computer Trends and Technology
English
Preserved Fulltext
The proposed web mining methodology uses web structure mining, using graph mining for malware detection with a case study proposed on cloud mining. ...
In this review paper we want to discuss Research Methodology on Web mining for Malware detection. ...
It proposes a novel soft-computing mechanism based on the ontology model for malware behavioral analysis: Malware Analysis Network in Taiwan (MAN in Taiwan, MiT). ...
doi:10.14445/22312803/ijctt-v12p131
fatcat:tt4nfblmhfb43a5a5j7hrew2pm
Comprehensive Analysis of IoT Malware Evasion Techniques
2021
Engineering, Technology & Applied Science Research
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
Malware detection in Internet of Things (IoT) devices is a great challenge, as these devices lack certain characteristics such as homogeneity and security. ...
Many security researchers have studied the IoT malware detection domain. Many studies proposed the static or dynamic analysis on IoT malware detection. ...
Malware detection can be performed on three bases: Behavior-based, specification -based, and signature-based ( Figure 1 ). ...
doi:10.48084/etasr.4296
fatcat:hyfkdspwizce3cyeu6erygpqai
Peer-to-Peer Architecture for Collaborative Intrusion and Malware Detection on a Large Scale
[chapter]
2009
Lecture Notes in Computer Science
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
The complexity of modern network architectures and the epidemic diffusion of malware require collaborative approaches for defense. ...
We present a novel distributed system where each component collaborates to the intrusion and malware detection and to the dissemination of the local analyses. ...
Moreover, it disseminates network activity reports on the basis of a behavioral analysis of the captured payload, thus being able to provide a description of the malware behavior. ...
doi:10.1007/978-3-642-04474-8_37
fatcat:2ytrbjpxsfehte25fevnarjkkq
SCREDENT: Scalable Real-time Anomalies Detection and Notification of Targeted Malware in Mobile Devices
2016
Procedia Computer Science
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
We propose SCREDENT: Scalable Real-time Anomalies Detection and Notification of Targeted Malware in Mobile Devices, to provide a scalable system to classify, detect, and predict targeted malware in real-time ...
SCREDENT uses adaptive, location-based notification principles to create a geographical fence which warn users of malicious attacks. ...
The logging component consists of a native Android application which logs replicable contextual and user behavioral data temporarily on the device until a Wi-Fi connection is established (see Table I ...
doi:10.1016/j.procs.2016.04.254
fatcat:4rugawxfqjaxdiazpg7brnjwhq
Triton: A Carrier-based Approach for Detecting and Mitigating Mobile Malware
2014
Journal of Cyber Security and Mobility
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf.
In this paper, we describe Triton, a new, network-based architecture, and a prototype implementation of it, for detecting and mitigating mobile malware. ...
Our implementation of Triton for both Android and Linux environments was built in our 3G UMTS lab network, and was found to efficiently detect and neutralize mobile malware when tested using real malware ...
Acknowledgements We thank Tufan Demir, Gerry Eisenhaur and Mike Gagnon for their help with mobile malware analysis. ...
doi:10.13052/jcsm2245-1439.324
fatcat:qt22obp6jndpfibojlf4dovcnq
Detection of Threats to IoT Devices using Scalable VPN-forwarded Honeypots
2019
Proceedings of the Ninth ACM Conference on Data and Application Security and Privacy - CODASPY '19
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
For detection and examination of potentially malicious traffic, we devise two analysis strategies: (1) given an outbound connection from honeypot, backtrack into network traffic to detect the corresponding ...
attack command that caused the malicious connection and use it to download malware, (2) perform live detection of unseen URLs from HTTP requests using adaptive clustering. ...
IMPLEMENTATION OF VPN-FORWARDED IOT HONEYPOT In this section, we describe the implementation of a high interaction IoT honeypot based on our proposed design. ...
doi:10.1145/3292006.3300024
dblp:conf/codaspy/TambeASOTSE19
fatcat:cnkc6mqnxrdj7oowy7cmk6pmxy
Scalable and Secure Architecture for Distributed IoT Systems
[article]
2020
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
We propose a novel architecture based on permissioned blockchain technology in order to build a scalable and decentralized end-to-end secure IoT system. ...
Internet-of-things (IoT) is perpetually revolutionizing our daily life and rapidly transforming physical objects into an ubiquitous connected ecosystem. ...
Also, we implement a deep learningbased solution to detect malware and suspected traffic. ...
arXiv:2005.02456v1
fatcat:culse67ylzeqlnkedwepjshq5e
The Nepenthes Platform: An Efficient Approach to Collect Malware
[chapter]
2006
Lecture Notes in Computer Science
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2007; you can also visit the original URL.
The file type is application/pdf.
We present the nepenthes platform, a framework for large-scale collection of information on self-replicating malware in the wild. ...
This hampers research in these topics because many counter-strategies against malware, e.g., network-and host-based intrusion detection systems, need hard empirical data to take full effect. ...
We are currently in the process of deploying a network intrusion detection system (NIDS) based on nepenthes. ...
doi:10.1007/11856214_9
fatcat:qaydx546ezhp5gi2o5f2fcc2lq
A Hybrid Real-time Zero-day Attack Detection and Analysis System
2015
International Journal of Computer Network and Information Security
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
This paper presents a novel hybrid system that integrates anomaly, behavior and signature based techniques for detecting and analyzing zero-day attacks in real-time. ...
Present research exhibits various issues and is not able to provide complete solution for the detection and analysis of zero-day attacks. ...
The authors are highly obliged to the Computer Science and Engineering Department of Thapar University, Patiala for rendering their incessant help in providing best infrastructure and work-environment. ...
doi:10.5815/ijcnis.2015.09.03
fatcat:fac5u42jpfffhh53jpjzg7yzgq
PreCrime to the rescue
2014
Proceedings of 5th Asia-Pacific Workshop on Systems - APSys '14
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
PreCrime is a proactive malware detection scheme that detects and stops malware activities from happening. ...
PreCrime creates mirrors of a mobile device in a resource-rich and trusted cloud, which speculatively executes multiple likely user operations concurrently to detect potential tampering and information ...
. • The implementation of a scalable detection system on cloud cluster that can make full use of computing resources of the cloud to achieve low latency of malware detection. ...
doi:10.1145/2637166.2637224
dblp:conf/apsys/TanLXZCL14
fatcat:3fwkgejos5fjzngqswksbpttwe
Scalable fine-grained behavioral clustering of HTTP-based malware
2013
Computer Networks
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf.
In this paper, we present a new scalable system for network-level behavioral clustering of HTTP-based malware that aims to efficiently group newly collected malware samples into malware family clusters ...
We implemented a proof-of-concept version of our new scalable malware clustering system and performed experiments with about 65,000 distinct malware samples. ...
This material is partially based upon work supported by the National Science Foundation under Grant No. CNS-1149051. ...
doi:10.1016/j.comnet.2012.06.022
fatcat:3772btbrjvf3zdm2osh4rx5xna
Scalable malware clustering through coarse-grained behavior modeling
2012
Proceedings of the ACM SIGSOFT 20th International Symposium on the Foundations of Software Engineering - FSE '12
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
Due to large volume of malware samples, it has become extremely important to group them based on their malicious characteristics. ...
In this paper, we propose a scalable malware behavior modeling technique that models the interactions between malware and sensitive system resources in a coarse-grained manner. ...
From a set of malware samples, prototypes are selected based on a threshold value to represent the entire malware samples. ...
doi:10.1145/2393596.2393627
dblp:conf/sigsoft/ChandramohanTS12
fatcat:pyqjtbwia5cwzdsjx3b2yfkuta
Internet of Things Malware : A Survey
2017
International Journal of Computer Science & Engineering Survey
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf.
In this paper we review literature on internet of things malware categories, support technologies, propagation and tools KEYWORDS Internet of Things (IoT), Malware, Malware synthesis, Machine to Machine ...
Internet of Things environments poses unique challenges such as device latency, scalability, lack of antimalware tools and heterogeneity of device architectures that makes malware synthesis complex. ...
ACKNOWLEDGEMENTS This work was supported by EU-Intra-ACP Mobility under Mobility to Enhance Training of Engineering Graduates in Africa (METEGA) grant. ...
doi:10.5121/ijcses.2017.8301
fatcat:dqsotxtph5cm5gmagwdxd6rmju
Improving IoT Botnet Investigation Using an Adaptive Network Layer
2019
Sensors
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
The proposed solution can modify the traffic at the network layer based on the actions performed by the malware. ...
Current malware analysis solutions, when faced with IoT, present limitations in regard to the network access containment and network traffic manipulation. ...
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/s19030727
fatcat:sxqihxpo4nhsxcappheq755ydq
Robust Intelligent Malware Detection Using Deep Learning
2019
IEEE Access
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
Overall, this paper paves way for an effective visual detection of malware using a scalable and hybrid deep learning framework for real-time deployments. ...
Recent malwares use polymorphic, metamorphic, and other evasive techniques to change the malware behaviors quickly and to generate a large number of new malwares. ...
They would also like to thank Computational Engineering and Networking (CEN) department for encouraging the research. ...
doi:10.1109/access.2019.2906934
fatcat:hr4vctlh55cbhamkvh5fq2hubu
« Previous
Showing results 1 — 15 out of 4,487 results