Dr.PYDIMARRI PADMAJA
@tkrec.ac.in
PROFESSOR.ECE DEPARTMEN
TEEGALA KRISHNA REDY ENGINEERING COLLEGE
RESEARCH, TEACHING, or OTHER INTERESTS
Electrical and Electronic Engineering, Computer Science Applications, Computer Networks and Communications, Speech and Hearing
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
P. Padmaja, D. Vemana Chary, R. Erigela, G. Sirisha, S. K. ChayaDevi, M. C. Pedapudi, B. Balaji, S. Cheerala, V. Agarwal, and Y. Gowthami
International Digital Organization for Scientific Information (IDOSI)
SVN Murthy, P.S. Ramesh, Pydimarri Padmaja, Bechoo Lal, G.Jagadeeswar Reddy, and Narender Chinthamu
Elsevier BV
Pydimarri Padmaja, Radhamma Erigela, D. Venkatarami Reddy, SK Umar Faruq, A. Krishnamurthy, B. Balaji, M. Lakshmana Kumar, Sreevardhan Cheerla, Vipul Agarwal, and Y. Gowthami
Springer Science and Business Media LLC
Nagireddy Venkata Rajasekhar Reddy, Pydimarri Padmaja, Miroslav Mahdal, Selvaraj Seerangan, Vrince Vimal, Vamsidhar Talasila, and Lenka Cepova
MDPI AG
The Internet of Things (IoT) is rapidly expanding and becoming an integral part of daily life, increasing the potential for security threats such as malware or cyberattacks. Many embedded systems (ESs), responsible for handling sensitive data or facilitating secure online activities, must adhere to stringent security standards. For instance, payment processors employ security-critical components as distinct chips, maintaining physical separation from other network components to prevent the leakage of sensitive information such as cryptographic keys. Establishing a trusted environment in IoT and ESs, where interactions are based on the trust model of communication nodes, is a viable approach to enhance security in IoT and ESs. Although trust management (TM) has been extensively studied in distributed networks, IoT, and ESs, significant challenges remain for real-world implementation. In response, we propose a hybrid fuzzy rule algorithm (FRA) and trust planning mechanism (TPM), denoted FRA + TPM, for effective trust management and to bolster IoT and ESs reliability. The proposed system was evaluated against several conventional methods, yielding promising results: trust prediction accuracy (99%), energy consumption (53%), malicious node detection (98%), computation time (61 s), latency (1.7 ms), and throughput (9 Mbps).
Mude Sreenivasulu, J. Ashok, Rakesh Kumar Godi, Pydimarri Padmaja, Puneet Kumar Aggarwal, and Dhiraj Kapila
Elsevier BV
Brijendra Gupta, Vilas D. Alagdeve, Pydimarri Padmaja, T. Coumaressin, V. Naresh Kumar Reddy, and R. Ganesh Kumar
IEEE
The term "Internet of Things" (IoT) describes the process of creating and modeling web-related physical objects across computing systems. IoT-based healthcare applications have offered multiple real-time products and benefits in recent years. For millions of people, these programmers provide hospitalization can get regular medical records and healthy lives. The introduction of IoT devices in the health sector has several technological developments. This study uses the IoT to construct a disease diagnostic system. Wearable sensors in this system initially monitor the patient's sympathy impulses. The impulses are then sent by a network environment to a server. In addition, a new hybrid approach to evaluation decision-making was presented as part of this research. This technique starts with the development of a set of features of the patient's pulses. Based on a learning approach qualifications are neglected. A fuzzy neural model was used as a diagnostic tool. A specific diagnosis of a particular ailment, such as the diagnosis of a patient's normal and abnormal pulse or the assessment of insulin issues, would be modeled to assess this technology.
N. Bharathiraja, Pydimarri Padmaja, S. B. Rajeshwari, Jagadish S. Kallimani, Ahmed Mateen Buttar, and T. Bheema Lingaiah
Hindawi Limited
Wireless networks include a set of nodes which are connected to one another via wireless links for communication purposes. Wireless sensor networks (WSN) are a type of wireless network, which utilizes sensor nodes to collect and communicate data. Node localization is a challenging problem in WSN which intends to determine the geographical coordinates of the sensors in WSN. It can be considered an optimization problem and can be addressed via metaheuristic algorithms. This study introduces an elite oppositional farmland fertility optimization-based node localization method for radio communication networks, called EOFFO-NLWN technique. It is the goal of the proposed EOFFO-NLWN technique to locate unknown nodes in the network by using anchor nodes as a starting point. As a result of merging the principles of elite oppositional-based learning (EOBL) and the agricultural fertility optimization algorithm (FFO), we have developed the EOFFO-NLWN approach, which is described in detail below. The EOBL concept makes it easier to populate the FFO algorithm’s population initialization, which results in an increase in the exploration rate. Various BNs and CRs were tested, and the findings revealed that the EOFFO-NLWN technique outperformed all other known techniques in all cases. A comprehensive experimental result analysis of the EOFFO-NLWN technique is performed under several measures, and the results described the sovereignty of the EOFFO-NLWN method associated to existing techniques.
N. Vadivelan, A. Ramamurthy, and P. Padmaja
American Scientific Publishers
Wireless sensor networks were organized with the collections of sensor nodes for the purpose of monitoring physical phenomenon such as temperature, humidity and seismic events, etc., in the real world environments where the manual human access is not possible. The major tasks of this type of networks are to route the information to sink systems in the sensor network from sensor nodes. Sensors are deployed in a large geographical area where human cannot enter such as volcanic eruption or under the deep sea. Hence sensors are not rechargeable and limited with battery backup; it is very complicated to provide the continuous service of sending information to sink systems from sensor nodes. To overcome the drawback of limited battery power, this paper proposes the concept of minimizing energy consumption with the help of neural networks. The modified form of HRP protocol called energy efficient HRP protocol has been implemented in this paper. Based on this concept, the workload of cluster head is shared by the cluster isolation node in order to increase the lifetime of the cluster head node. Also cluster monitoring node is introduced to reduce the re-clustering process. The implementation procedure, algorithm, results and conclusions were proved that the proposed concept is better than the existing protocols.
P. Padmaja and G.V. Marutheswar
Elsevier BV
P. Padmaja and G. V. Marutheswar
IEEE
Optimization of Wireless Sensor Network is necessary to reduce redundancy and energy consumption. This paper is mainly focused on TESDA protocol against the compromised nodes that attempt to inject fake data into the data aggregation process. To optimize the data aggregation process in the existence of compromised nodes, the TESDA integrates an energy efficient clustering approach and a trust-based security mechanism. The trust-based security mechanism of TESDA allows the sink and cluster head to estimate a deviation based trust and it diminishes the impact of the compromised sensor node contribution in aggregation performance. By considering the current trust values of sensor nodes in the cluster head election process, the TESDA optimizes the cluster head election performance and also enhances the routing performance By electing a CH based on residual energy, the clustering mechanism of TESDA attains fair energy consumption among nodes within the cluster. Thus, it prolongs the overall network.
P. Padmaja and G.V. Marutheswar
IEEE
Optimization Wireless Sensor Network (WSN) is necessary to reduce redundancy and energy consumption. To optimizing wireless sensor networks for secured data transmission both at cluster head and base station data aggregation is needed. Data aggregation is performed in every router while forwarding data. The life time of sensor network reduces because of employing energy inefficient nodes for data aggregation. Hence aggregation process in WSN should be optimized in energy efficient manner. So introduced one protocol on trust based with weights. This paper completely about theattacks, and some methods for secured data transmission.
P. Padmaja and G.V. Marutheswar
IGI Global
Wireless Sensor Network (WSN) need to be more secure while transmitting data as well as should be deployed properly to reduce redundancy and energy consumption. WSNs suffer from many constraints, including low computation capability, small memory, limited energy resources, susceptibility to physical capture and the use of insecure wireless communication channels. These constraints make security in WSNs a challenge. In this paper, a survey of security issues in WSNs is presented and a new algorithm TESDA is proposed, which is an optimized energy efficient secured data aggregation technic. The cluster head is rotated based on residual energy after each round of aggregation so that network lifetime increases. Based on deviation factor calculated, the trust weight is assigned, if more deviation, then the trust value is less. Simulation results observed by using NS-2. From network animator and x-graphs the result are analyzed. Among all protocols tesda is an energy efficient secured data aggregation method.
P. Padmaja and G.V. Marutheswar
IEEE
Optimization Wireless Sensor Network (WSN) is necessary to reduce redundancy and energy consumption. To optimizing wireless sensor networks for secured data transmission both at cluster head and base station data aggregation is needed. Data aggregation is performed in every router while forwarding data. The life time of sensor network reduces because of employing energy inefficient nodes for data aggregation. Hence aggregation process in WSN should be optimized in energy efficient manner. When sensors are deployed at differet locations in wider area, it is possible to compromising attacks by adversaries. false data injected in compromised sensors during data aggregation process which results in false decision making at the Base Station (BS). Simple average data aggregation process is suitable only in attacker free environment. So to filter the false data during data aggregation, induced by the attacker. For every round of data agg.regation need to observe the behavior of nodes. So that it easy to minimize an impact of attacker contribution at the final result. For secure data aggregation process along with trustworthiness estimation using Trust wEighted Secure Data Aggregation algorithm (TESDA). Data aggregation process is optimized by performing aggregation in energy efficient manner through clustering If the aggregator is compromised, then it affects entire aggregation accuracy. Hence it is necessary to propose a aggregation protocol that is resilient against compromised sensor and compromised aggregator in energy efficient and secure manner.