Research on UPnP Protocol Security of Gateway Device

2017 ◽  
pp. 450-458
Author(s):  
Baojiang Cui ◽  
Qin Zhang ◽  
Xiangqian Zhang ◽  
Tao Guo
Keyword(s):  
Protocol Security ◽  
Upnp Protocol

Virtual Private Network Flow Detection in Wireless Sensor Networks using Machine Learning Techniques

2021 ◽  
Vol 10 ◽  
Author(s):  
S. Phani Praveen ◽  
T. Bala Murali Krishna ◽  
Sunil K. Chawla ◽  
CH Anuradha
Keyword(s):  
Machine Learning ◽  
Traffic Flow ◽  
Network Flow ◽  
Virtual Private Network ◽  
Machine Learning Techniques ◽  
Protocol Security ◽  
Learning Techniques ◽  
Private Network ◽  
Hyper Text Transfer Protocol ◽  
Transfer Protocol

Background: Every organization generally uses a VPN service individually to leather the actual communication. Such communication is actually not allowed by organization monitoring network. But these institutes are not in a position to spend huge amount of funds on secure sockets layer to monitor traffic over their computer networks. Objective: Our work suggests simple technique to block or detect annoying VPN clients inside the network activities. This method does not requires the network to decrypt or even decode any network communication. Method: The proposed solution selects two machine learning techniques Feature Tree and K-means as classifiction techniques which work on time related features. First, the DNS mapping with the ordinary characteristic of the transmission control protocol / internet protocol computer network stack is identified and it is not to be considered as a normal traiffic flow if the domain name information is not available. The process also examines non-standard utilization of hyper text transfer protocol security and also conceal such communication from hyper text transfer protocol security dependent filters in firewall to detect as anomaly in largely. Results: we define the trafic flow as normal trafic flow and VPN traffic flow. These two flows are characterized by taking two machine learning techniques Feature Tree and K-means. We have executed each experment 4 times. As a result, eight types of regular traffics and eight types of VPN traffics were represented. Conclusion: Once trafic flow is identified, it is classified and studied by machine learning techniques. Using time related features, the traffic flow is defined as normal flow or VPN traffic flow.

scholarly journals Marine Network Protocols and Security Risks

2021 ◽  
Vol 1 (2) ◽  
pp. 239-251
Author(s):  
Ky Tran ◽  
Sid Keene ◽  
Erik Fretheim ◽  
Michail Tsikerdekis
Keyword(s):  
Network Protocols ◽  
Network Protocol ◽  
Identification System ◽  
Automated Identification ◽  
Security Risks ◽  
Domain Specific ◽  
Protocol Security ◽  
Challenges And Opportunities

Marine network protocols are domain-specific network protocols that aim to incorporate particular features within the specialized marine context that devices are implemented in. Devices implemented in such vessels involve critical equipment; however, limited research exists for marine network protocol security. In this paper, we provide an analysis of several marine network protocols used in today’s vessels and provide a classification of attack risks. Several protocols involve known security limitations, such as Automated Identification System (AIS) and National Marine Electronic Association (NMEA) 0183, while newer protocols, such as OneNet provide more security hardiness. We further identify several challenges and opportunities for future implementations of such protocols.

scholarly journals Security Techniques for Wormhole Attack in Wireless Sensor Networks

2018 ◽  
Vol 7 (2.23) ◽  
pp. 59 ◽  
Author(s):  
Surinder Singh ◽  
Hardeep Singh Saini
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Base Station ◽  
Packet Transmission ◽  
Wireless Sensor ◽  
Security Threat ◽  
Wormhole Attack ◽  
Protocol Security ◽  
Routing Mechanism ◽  
Packet Drop

The wireless sensor network has group of sensors which can sense the data and route this data to base station. As there is no physical connection between sensor and base station the important data can be routed without wires. The broadcast nature of wireless sensor network makes it prone to security threat to the valuable data. The attacker node can detect the data by creating their own data aggregation and routing mechanism .The number of attacks can be possible on the network layer. Out of these attacks wormhole is one of the major attack which can change the routing method of the whole wireless sensor network. In this attack,the attacker node can control the packet transmission of whole network and route it to the tunnel of nodes. The major drawback of this attack is to increase the packet drop and disturbing the routing mechanism. A number of security techniques are developed by the researcher to reduce the packet drop ratio and secure the routing mechanism of the network. Out of all thesetechniquesfew related to packet drop ratio are discussed in this paper. TheLightweight countermeasure for the wormhole attack (LITEWORP) based on Dynamic Source routing (DSR) protocol security technique,Delay Per Hop Indication (Delphi) based on AODV(Avoidance Routing Protocol) Protocol security technique and MOBIWORP based on DSRprotocol security technique reduce the packet loss percentage 40%,43% and 35% respectively.   

scholarly journals The Sensors Connectivity within SCADA Automation Environment and New Trends for Security Development during Multicasting Routing Transmission

2015 ◽  
Vol 2015 ◽  
pp. 1-15 ◽  
Author(s):  
Aamir Shahzad ◽  
Kalum Priyanath Udagepola ◽  
Young-keun Lee ◽  
Soojin Park ◽  
Malrey Lee
Keyword(s):  
Protocol Stack ◽  
Simulation Environment ◽  
Protocol Security ◽  
Intelligent Sensors ◽  
Scada System ◽  
Water Pumping

This study examined the security of SCADA system and its protocols, more specifically, SCADA/DNP3 protocol security. To achieve the study goals, a SCADA simulation environment is designed for water pumping process through connectivity of intelligent sensors, the payload is constructed, and security is deployed inside DNP3 protocol stack and then bytes are multicast to subcontrollers.

scholarly journals A Quantum Dual-Signature Protocol Based on SNOP States without Trusted Participant

Entropy ◽  
2021 ◽  
Vol 23 (10) ◽  
pp. 1294
Author(s):  
Kejia Zhang ◽  
Xu Zhao ◽  
Long Zhang ◽  
Guojing Tian ◽  
Tingting Song
Keyword(s):  
Quantum Signature ◽  
Third Party ◽  
Trusted Third Party ◽  
Protocol Security ◽  
Verification Process ◽  
Orthogonal Product ◽  
First Time

Quantum dual-signature means that two signed quantum messages are combined and expected to be sent to two different recipients. A quantum signature requires the cooperation of two verifiers to complete the whole verification process. As an important quantum signature aspect, the trusted third party is introduced to the current protocols, which affects the practicability of the quantum signature protocols. In this paper, we propose a quantum dual-signature protocol without arbitrator and entanglement for the first time. In the proposed protocol, two independent verifiers are introduced, here they may be dishonest but not collaborate. Furthermore, strongly nonlocal orthogonal product states are used to preserve the protocol security, i.e., no one can deny or forge a valid signature, even though some of them conspired. Compared with existing quantum signature protocols, this protocol does not require a trusted third party and entanglement resources.

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