Chaotic Map Based Key Generation and Realistic Power Allocation Technique for Secure MU-MIMO Wireless System

2019 ◽  
pp. 142-155
Author(s):  
C. Manikandan ◽  
S. Rakesh Kumar ◽  
Kopparthi Nikhith ◽  
M. Sai Gayathri ◽  
P. Neelamegam
Keyword(s):  
Power Allocation ◽  
Chaotic Map ◽  
Key Generation ◽  
Wireless System

scholarly journals 3S-IoT an Algorithm to make the Network Secured and Smart

2020 ◽  
Author(s):  
Maneesh Pant ◽  
Brij Mohan Singh ◽  
Dharam Vir Gupta
Keyword(s):  
Denial Of Service ◽  
Chaotic Map ◽  
High Energy ◽  
Key Generation ◽  
Multicast Communication ◽  
Multicast Traffic ◽  
Proposed Model ◽  
Man In The Middle ◽  
Multicast Communications ◽  
Actuator Control

Abstract Internet of Things (IoT) evolving and widespread presence has made the lives of all comfortable and handy, while on the other hand posing various challenges, i.e. less efficiency, less security, and high energy drain, threatening smart IoT-based applications. Compared to unicast communication, multicast communication is considered more powerful in group-oriented systems, because transmission takes place using less resources. This is why many of the IoT applications rely on multicast in their transmission. This multicast traffic needs to be handled explicitly for sensitive applications requiring actuator control. Securing multicast traffic by itself is cumbersome as it requires an efficient and flexible Group Key Establishment (GKE) protocol. We propose a three-tier model that can, not only be used to control the IoT, but also to control multicast communications. The architecture is built with a 256-bit keyless encryption technique to protect the authentication to create the network link. Machine learning-based chaotic map key generation is used to protect GKE. Finally, using MD5, the system key is authenticated. The algorithm is checked for energy used, bandwidth, and time taken. The proposed model is applied and evaluated against numerous benchmark attacks such as Distributed Denial of Service (DDoS), Man in the Middle and Fishing.

Secret Key Generation Rate With Power Allocation in Relay-Based LTE-A Networks

2015 ◽  
Vol 10 (11) ◽  
pp. 2424-2434 ◽  
Author(s):  
Kan Chen ◽  
Balasubramaniam Bala Natarajan ◽  
Steve Shattil
Keyword(s):  
Power Allocation ◽  
Generation Rate ◽  
Key Generation ◽  
Secret Key ◽  
Secret Key Generation

scholarly journals AES WITH CHAOTIC USING CHEBYSHEV POLYNOMIAL

2018 ◽  
Vol 44 (2) ◽  
pp. 35-40
Author(s):  
Tanya jabor ◽  
Hiba Taresh ◽  
Alaa Raheema
Keyword(s):  
Real Time ◽  
Personal Information ◽  
Chaotic Map ◽  
Encryption Algorithm ◽  
The Internet ◽  
Key Generation ◽  
Generation Algorithm ◽  
Critical Data ◽  
Encryption And Decryption ◽  
Day By Day

All the important information is exchanged between facilities using the internet and networks, all these data should besecret and secured probably, the personal information of person in each of these institutions day by day need to organized secretlyand the need of the cryptography systems is raised which can easily encrypt the personal and critical data and it can be shared withother centers via internet without and concerns about privacy. Chaotic performance is added to different phases of AES but very few apply it on key generation and choosing ChebyshevPolynomial will provide a chaotic map which will led to random strong key. our system based on modified advanced encryptionstandard (AES) , with encryption and decryption in real time taking to consideration the criticality of data images that beenencrypted the main encryption algorithm is the same the modification is done by replacing the key generation algorithm byChebyshev Polynomial to generate key with the required key size.

scholarly journals 3S-IoT an Algorithm to make the Network Secure and Smart

2021 ◽  
Author(s):  
maneesh pant ◽  
Brijmohan Singh ◽  
Dharam Vir Gupta
Keyword(s):  
Denial Of Service ◽  
Chaotic Map ◽  
High Energy ◽  
Key Generation ◽  
Multicast Traffic ◽  
Proposed Model ◽  
Man In The Middle ◽  
Multicast Communications ◽  
Actuator Control ◽  
And Control

Abstract The growing and widespread presence of Internet of Things (IoT) has made the lives of all comfortable and handy, but poses various challenges, like efficiency, security, and high energy drain, threatening smart IoT-based applications. Small applications rely on Unicast communication. In a group-oriented communication, multicast is better as transmission takes place using fewer resources. Therefore, many IoT applications rely on multicast transmission. To handle sensitive applications, the multicast traffic requires an actuator control. Securing multicast traffic by itself is cumbersome, as it expects an efficient and flexible Group Key Establishment (GKE) protocol. The paper proposes a three-tier model that can control the IoT and control multicast communications. The first authentication is at network linking where we used a 256-bit keyless encryption technique. Machine learning-based chaotic map key generation authenticates the GKE. Finally, MD5 establishes the system key. 3S-IoT is smart to detect any tempering with the devices. It stores signatures of the connected devices. The algorithm reports any attempt to change or temper a device. 3S-IoT can thwart attacks such as Distributed Denial of Service (DDoS), Man-in-the-Middle (MiTM), phishing, and more. We calculated energy consumed, bandwidth, and the time taken to check the robustness of the proposed model. The results establish that 3S-IoT can efficiently deal with the attacks. The paper compares 3S-IoT with Benchmark algorithms.

scholarly journals Power Allocation Strategy for Secret Key Generation Method in Wireless Communications

2021 ◽  
Vol 68 (2) ◽  
pp. 2179-2188
Author(s):  
Bin Zhang ◽  
Muhammad Waqas ◽  
Shanshan Tu ◽  
Syed Mudassir Hussain ◽  
Sadaqat Ur Rehman
Keyword(s):  
Wireless Communications ◽  
Power Allocation ◽  
Key Generation ◽  
Secret Key ◽  
Allocation Strategy ◽  
Secret Key Generation

Joint Power Allocation and Match Access for Physical Layer Security of Heterogeneous Network

2017 ◽  
Vol 3 (2) ◽  
pp. 11
Author(s):  
Shiwei Yan ◽  
Yong Shang ◽  
Xiguang Zhang
Keyword(s):  
Power Allocation ◽  
Cellular Networks ◽  
Physical Layer Security ◽  
Physical Layer ◽  
Secrecy Capacity ◽  
Matching Problem ◽  
Wireless System ◽  
Joint Power ◽  
Weighted Bipartite Graph ◽  
Practical Constraints

In this paper, we investigate the Physical Layer Security (PLS) of a multiple friendly jammers and multiple users wireless system in Device-to-Device (D2D) communications underlaying cellular networks with an eavesdropper. The aim is to maximize the increase of secrecy capacity of the entire system through optimal power allocation and jamming matching under various practical constraints. Firstly, the total increase secrecy capacity of D2D pairs with the help of jamming is derived, then we obtain optimal jamming power for each D2D pair and formulate the D2D pairs and jammers matching problem in the weighted bipartite graph via designing the Kuhn-Munkres (KM) algorithm. Finally, numerical results demonstrate that our scheme could greatly improve the secrecy performance of heterogeneous D2D and cellular networks.

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