Published in 2026
S.Danusree, D.Aldrine Douglas, N.Anurag
This mobile application over security is about the essential mobile app security ecosystem security decisions on authentication and authorization one based on the values of these inputs. The World where communication traffic between mobile Apps will be completely secure. Nowadays in Android Smartphone many apps are developed some of them are causing virus hanging to their mobile phones because these phones are not protected by the security it appears to be impervious to decryption efforts. The trend to encrypt communication is a consequence of this reach for privacy secure communication is peer to peer architecture with end to end encryption. Data storage is protected data stored on the device whether in volatile memory persistent memory or removable storage. Security uses to secure access and deployment of approval enterprise is in they give security any thought they figure developers too late of all that for them 360 security apps IV manager are the Some of the apps to secure the mobile phones through security.
Mobile Application Security, Data Storage, Android, Smartphone
Suresh.H, Ravindra.S.Hegadi
Wireless Sensor Networks (WSNs) are the type of networks there will be no physical connectivity and are commonly used in often deployed in adverse environments where the attacker can physically capture some of the nodes, first can reprogram, and then, can duplicate them in a large number of clones, easily taking control over the network. Many classical and basic steps are undergone to prevent and eradicate such attacks. But those existing methods are not up to the mark. Basically, WSN are depended on energy aware networks. A serious drawback for any protocol to be used in the WSN- resource constrained environment. Further, they are vulnerable to the specific adversary models introduced in this paper. The contributions of this work are threefold. First, we analyze the desirable properties of a distributed mechanism for the detection of node replication attacks. Second, we show that the known solutions for this problem do not completely meet our requirements. Third, we propose a new selfhealing, Randomized, Efficient, and Distributed (RED) protocol for the detection of node replication attacks, and we show that it satisfies the introduced requirements. Our Implementation specifies, user will specify its ID, Location ID, Random number, Destination ID along with Destination Location ID, to the Witness node. The witness will verify the internally bounded user ID with the user specified ID. If the Verification is Success, the packets are sent to the destination. We Propose Modified RED Scheme to identify Cloning attacks in the Network.
WSN, Security, Clone Attacks, RED.
R.Ame Rayan, A.Kaviya
We are at the beginning of the digital industrial era and the digital twin is in its infancy. As these Digital twins become the ‘living’ models of physical entities that they represent, they embody asset ’memories’ and even ‘group consciousnesses. The next big thing in industrial services will be about accurately forecasting the future of physical assets through digital twin. Digital twins refer to computerized companions of physical assets that can be used for various purposes. Digital twins use data from sensors installed on physical objects to represent their near real-time status, working condition or position. The digital twin is essentially a living model of the physical asset or system, which will continually adapt to changes in the environment or operations and deliver the best business outcome. It can also be rapidly and easily scaled for quick deployment for other, similar applications.
Sensor, Digital twins, PLM, Gauges, CMMs, UR
R.Waheetha, S.Jeya Revathi
Haptic is the “science of applying tactile sensation to human interaction with computers”. In our paper we have discussed the basic concepts behind haptic along with the haptic devices and how these devices are interacted to produce sense of touch and force feedback mechanisms. Also the implementation of this mechanism by means of haptic rendering and contact detection were discussed. We mainly focus on ‘Application of Haptic Technology in Surgical Simulation and Medical Training’. Further we explained the storage and retrieval of haptic data while working with haptic devices. Also the necessity of haptic data compression is illustrated.
Haptic, tactile,CyberGrasp,PHANTOM, Surgical Simulation
J.Maria Merceline Vijila, R.Abinaya
There has been a recent surge in interest in the application of Artificial Intelligence (AI) techniques to Software Engineering (SE) problems. The work is typified by recent advances in Search Based Software Engineering, but also by long established work in Probabilistic reasoning and machine learning for Software Engineering. This paper explores some of the relationships between these strands of closely related work, arguing that they have much in common and sets out some future challenges in the area of AI for SE. Software development is a very complex process that, at present, is primarily a human activity. Programming, in software development, requires the use of different types of knowledge: about the problem domain and the programming domain. It also requires many different steps in combining these types of knowledge into one final solution. This paper intends to review the techniques developed in artificial intelligence (AI) from the standpoint of their application in software engineering. In particular, it focuses on techniques developed (or that are being developed) in artificial intelligence that can be deployed in solving problems associated with software engineering processes.
Analysis, Synthesis, Programming, Domain, Conversion, Design, Coding
S.Dhivya, T.T.Mathangi, S.Jeniba
Frequent pattern mining discovers patterns in transaction databases based only on the relative frequency of occurrence of items without considering their utility.High utility pattern (HUP) mining is one of the most important in data mining due to its ability to consider the non-binary frequency values of items in transactions and different profit values for every item. On the other hand, incremental data mining provide the ability to use previous data structures and mining results in order to reduce unnecessary calculations In this project, three tree structures have been implemented called IHUPL,IHUPTF,IHUPTWU (Incremental High Utility Pattern).All the IHUP tree structures maintains the tf and twu values in the header table and the tree nodes. The first tree structure is arranged in the lexicographic order(IHUPL). It can capture the incremental data without any restructuring operation. The second tree structure is arranged in descending order based on the transaction frequency(IHUPTF).The third tree structure is arranged in the descending order based on the transaction weighted utilization(IHUPTWU) to reduce the mining time. IHUP has the "build once mine property" and is suitable for incremental mining. The experimental results shows that the tree structures are efficient and scalable for incremental mining.
Data Mining, Frequent Pattern Mining, High Utility Pattern Mining, Incremental Mining.
G.Prathima
Publishing data on a social networking site has become a part of online social activity .Social networking offers an important means for users to converse, interact and share information. Due to rapid growth of social network, data has been publicly available across in one way or another. Preserving the data Privacy of social network data has becomes a more and more important Factor. In the present paper, we focus on a brief review of the existing anonymization techniques for privacy preserving of social network data. We also try to identify the new challenges in Data privacy preserving of social network data.
Data Publishing, Online Social Networks, Data Privacy
Dr.G.Anandharaj, Dr.Srimanchari
File system is used to control how data is stored and retrieved. Without a file system, information placed in a storage medium would be one large body of data with no way to tell where one piece of information stops and the next begins. By separating the data into pieces and giving each piece a name, the information is easily isolated and identified. The rapid development of biomedical monitoring technologies has enabled modern intensive care units (ICUs) to gather vast amounts of multimodal measurement data about their patients. However, processing large volumes of complex data in real-time has become a big challenge. Together with ICU physicians, we have designed and developed an ICU clinical decision support system icuARM based on associate rule mining (ARM), and a publicly available research database MIMIC-II (Multi-parameter Intelligent Monitoring in Intensive Care II) that contains more than 40,000 ICU records for 30,000+ patients. icuARM is constructed with multiple association rules and an easy-to-use graphical user interface (GUI) for care providers to perform real-time data and information mining in the ICU setting. The EU is imposing strict limitations on the use of data obtained from its citizens’ online activities [9], while Big Data advocates and online advertisers in the United States are concerned that this may represent interference in their basic business models or even in international trade. It is clear that laws and regulations are inconsistent across national borders. They are also inconsistent within nations, depending on the industry classification of companies, or even the designation given to specific technologies. ISPs are prohibited from reading subscribers’ email; other information services companies can do so legally. Data stored electronically is offered protection that is denied to data stored in the cloud. More importantly, it suggests that regulation be driven by what consumers actually want, and provides some preliminary research aimed at determining what consumers want from privacy regulation around the world.
Big data, Units, Email, and Data store
Dr.S.Suriya, K.Nagalakshmi, G.Balakrishnan, S.J.Subhashini
This paper presents a new MapReduce cloud service model, Cura, for profitable MapReduce services in a cloud. In contrast to existing MapReduce cloud services such as a generic compute cloud or a dedicated MapReduce cloud, Cura has a number of unique benefits. First, Cura is designed to provide a cost-effective solution to efficiently handle MapReduce production workloads that have an important amount of interactive jobs. Second, unlike existing services that require customers to decide the resources to be used for the jobs, Cura leverages MapReduce profiling to automatically create the best cluster configuration for the jobs. While the existing models allow only a per-job resource optimization for the jobs, Cura implements a globally efficient resource allocation scheme that significantly reduces the resource usage cost in the cloud. Third, Cura leverages unique optimization opportunities when dealing with workloads that can withstand some slack .By effectively multiplexing the available cloud resources among the jobs based on the job requirements, Cura achieves significantly lower resource usage costs for the jobs and it also includes identifying the shortest execution time. Cura’s core resource management schemes include cost-aware resource provisioning, M-aware scheduling and online virtual machine reconfiguration. Our experimental results using Census workload traces show that our techniques lead to more than 80 percent reduction in the cloud compute infrastructure cost with upto 65 percent reduction in job response times.
Mapreduce, Cloud Services, bigdata, Hadoop
J.Saranya, R.Arun sanjay, R. Aishwarya
Mobile computing is a technology that allows transmission of data, voice and video via a computer or without having to be connected to a fixed physical link.LTE refers to a standard for smooth and efficient transition toward more advanced leading-edge technologies to increase the capacity and speed of wireless data networks .LTE is often used to refer to wireless broadband or mobile network technologies
Long Term Evolution, LTR, wireless standards, Techniques & Technology, advantages.
M.M.Kavitha, Dr. B.Anandhi
With the exponential growth of data from various social networks like Facebook, Twitter, Mobile applications, Digital cameras, Sensor networks etc., and also from biomedical researches the overall data volume has increased tremendously. So analyzing and extracting fruitful information from such a dynamic data is very much challenging task today. Data grouping or clustering plays a vital role in handling big data which is the basic foot step in data mining, pattern recognition and also in medical predictions. The clustering techniques are very much suitable for handling big data in this case the learning parameters are computed from learning data. Clustering approaches can be classified into two categories namely- Hard clustering and soft clustering. In hard clustering data is divided into clusters in such a way that each data item belongs to a single cluster only while soft clustering also known as fuzzy clustering forms clusters such that data elements can belong to more than one cluster based on their membership levels which indicate the degree to which the data elements belong to the different clusters. This paper deals with an attempt at studying the data clustering algorithms based on fuzzy techniques. These fuzzy clustering algorithms have been widely studied and applied in a variety of substantive areas
Big Data, Fuzzy Clustering, C-Means, K-means, KNN
K.M.Padmapriya, Dr. B.Anandhi
Data clustering is a common technique for data analysis, which is used in many fields, including machine learning, data mining, pattern recognition, image analysis and bioinformatics. K-means is a simple and widely used algorithm for clustering data. But, the traditional k-means is computationally expensive; sensitive to outlier’s i.e. unnecessary data and produces unstable result hence it becomes inefficient when dealing with very large datasets. Solving these Issues is the subject of many recent research works. In this paper, we will do a review on k-means clustering algorithms.
Big Data, K-Means Clustering, Map Reduce, Datamining