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Network traffic visitor’s classification is fundamental to network management and its performance. However, traditional traffic classifications, which were designed to work on a devoted hardware at very high line rates, may not feature well in digital software-primarily based surroundings. The advised fingerprinting scheme is strong to community conditions which include congestion, fragmentation, put off, retransmissions, duplications, and losses and to various processing abilities. Hence, its overall performance is largely independent of placement and migration problems, and consequently yields an appealing answer for virtualized software program-primarily based environments. We recommend an identical fingerprinting scheme for consumer datagram protocol traffic, which advantages from the equal blessings as the TCP one and attains very excessive accuracy as properly. Results show that our scheme effectively labeled about 97% of the flows on the dataset examined, even on encrypted facts.

Network traffic classification, Network monitoring and measurements, Machine learning, Network function virtualization, Software-defined networking

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[18] S. Zander, T. Nguyen, and G. Armitage, “Automated traffic classification and application identification using machine learning,” in Local Computer Networks, 2005. 30th Anniversary. The IEEE Conference on. IEEE, 2005, pp. 250–257.
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[20] Y.-D. Lin, C.-N. Lu, Y.-C. Lai, W.-H. Peng, and P.-C. Lin, “Application classification using packet size distribution and port association,” Journal of Network and Computer Applications, vol. 32, no. 5, pp. 1023–1030, 2009.

S.Kalpana, T. Raghu Trivedi, "Classification of Network Traffic Based on Zero-Length Packets: A Review", International Journal of Computer Sciences and Engineering, Vol.07, Issue.06, pp.103-105, 2019.

Multi-task clustering improves the clustering performance of each task by transferring knowledge among the related tasks. An important aspect of multi-task clustering is to assess the task relatedness. However, to our knowledge, only two previous works have assessed the task relatedness, but they both have limitations. In this paper, we propose two multi-task clustering methods for partially related tasks: the self-adapted multi-task clustering (SAMTC) method and the manifold regularized coding multi-task clustering (MRCMTC) method, which can automatically identify and transfer related instances among the tasks, thus avoiding negative transfer. Both SAMTC and MRCMTC construct the similarity matrix for each target task by exploiting useful information from the source tasks through related instances transfer, and adopt spectral clustering to get the final clustering results. But they learn the related instances from the source tasks in different ways.

Multi-task Clustering, Partially Related Tasks, Negative Transfer, Instance Transfer

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C.Rupakumar, S. Girinath, "A Review on Multi-Task clustering with self-adaptive and Model Relation Learning", International Journal of Computer Sciences and Engineering, Vol.07, Issue.06, pp.106-108, 2019.

Cloud storage system provides helpful file storage and sharing services for distributed purchasers. to handle integrity, manageable outsourcing and origin auditing issues on outsourced files, we have a tendency to propose Associate in Nursing identity-based information outsourcing (IBDO) theme equipped with fascinating options advantageous over existing proposals in securing outsourced information. First, our IBDO theme permits a user to authorize dedicated proxies to transfer information to the cloud storage server on her behalf, e.g., an organization could authorize some staff to transfer files to the company’s cloud account in an exceedingly controlled means. The proxies area unit known and approved with their recognizable identities, that eliminates difficult certificate management in usual secure distributed computing systems. Second, our IBDO theme facilitates comprehensive auditing, i.e., our theme not solely permits regular integrity auditing as in existing schemes for securing outsourced information, however conjointly permits to audit {the information|the knowledge|the information} on data origin, kind and consistence of outsourced files. Security analysis and experimental analysis indicate that our IBDO theme provides robust security with fascinating potency.

Cloud storage, information outsourcing, Proof of storage, Remote integrity proof, Public auditing

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[5] J. Sun and Y. Fang, “Cross-Domain information Sharing in Distributed Electronic Health Record Systems,” Parallel and Distributed System- s, IEEE Transactions on, vol. 21, no. 6, pp. 754–764, 2010.
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C. Anilkumar Raju, "Identity-Based information Outsourcing with Comprehensive Auditing in Clouds: A Study", International Journal of Computer Sciences and Engineering, Vol.07, Issue.06, pp.109-115, 2019.

Direct storage of biometric templates in databases exposes the authentication system and legitimate users to numerous security and privacy challenges. Human beings can no longer be separated from electronic devices and the Internet technology. The need for information made available on systems and networks which are connected on the internet. It is very essential to provide an effective security measure and system that ensures the confidentiality, integrity, and availability of information system, networks, and the services and resources made available. In this paper a new way of technique is Fuzzy vault. Fuzzy Vault is one of the most promising bio-cryptographic techniques to prevent the template data from being misused. To make the fuzzy vault practically realizable in real-life applications especially for large databases, the chaff generation time needs to be reduced to greater extent. This work focuses on decreasing the chaff generation time to reduce the overall vault creation time This can be achieved using Biometric and Digital Forensic Technology.

Biometrics, Digital Forensic Technology, Biometric Security, fingerprint recognition, Fuzzy Vault, Chaff Points

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Syed Javid Basha, B. Muni Hema Kumar, "Analysis on Biometrics, Forensics Protecting Using Key Binding Mode Based Ppbss Using Fuzzy Vault", International Journal of Computer Sciences and Engineering, Vol.07, Issue.06, pp.116-121, 2019.

Groundwater plays a major role in human life. Now-a-days, the Groundwater levels are gradually decreasing due to pollution and over usage of water and lack of rains. The air pollution caused by industries and human wastage reducess the Groundwater. The increased Groundwater threat is a threat to human life. There is no proper planning and infrastructure to preserve the Groundwater. The bore wells and tube wells pump the Groundwater from a very deep source. Over usage of sand also causes the decrement of Groundwater level. Now-a-days, due to the the scarcity of Groundwater, the farmer is unable to decide the kind crop to be grown in his/her land. This is a complex task. The food bowl of India is day by day becoming weak due to a the scarcity of Groundwater. “Atmospherical science is the best source of study for analyzing and predicting the weather phenomenon and suggests ways and means overcome the problem”[1].

Rainfall, Geographical Parameters,an aquifer

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Mooramreddy Sree Devi, Vempalli Rahamathulla, "Prediction of Groundwater Level In District Level By Implementing Machine Learning And Advanced Softcomputing Techniques", International Journal of Computer Sciences and Engineering, Vol.07, Issue.06, pp.122-124, 2019.

Cipher textual content-coverage characteristic-based totally encryption (cp-abe) has been a desired encryption technology to clear up the difficult problem of comfy details sharing in CC. the shared information documents commonly has the function of multilevel hierarchy, mainly inside the place of healthcare and the military. But, the hierarchy shape of shared documents has been not explored in older systems. on this paper, a green record hierarchy function-based encryption concept is proposed in cloud computing. The layered get admission to structures are included into a unmarried right wing after which the hierarchical files are encrypted with the incorporated get right of entry to format. The cipher text additives associated with attributes may be shared thru way of the documents. Therefore, each cipher text storage and time charge of encryption is saved. Moreover, the proposed scheme is proved to be cozy under the equal vintage assumption. our experimental simulation indicates the proposed scheme that is quite in phrases of encryption and decryption.

Cipher textual content-coverage characteristic-based totally encryption (cp-abe), cloud computing, adequate cloud files encryption

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Y. Gnanendra, K. Thanweer Basha, "An Integrated Access Structure and Encryption Scheme for Adequate Cloud Files: A Review", International Journal of Computer Sciences and Engineering, Vol.07, Issue.06, pp.125-127, 2019.

Content-based picture recuperation (CBIR) applications had been fast created along the enlargement in the quantity, accessibility and importance of pix in our day by day existence. Be that as it may, the huge association of CBIR conspire has been constrained with the aid of it`s the extreme calculation and potential prerequisite. Content Based Image Retrieval (CBIR) is an efficient retrieval of relevant images from large databases based on features extracted from the image. This paper proposes a system that can be used for retrieving images related to a query image from a large set of distinct images. It follows an image segmentation based approach to extract the different features present in an image. The above features which can be stored in vectors called feature vectors and therefore these are compared to the feature vectors of query image and the image information is sorted in decreasing order of similarity. The processing of the same is done on cloud. The CBIR system is an application built on Windows Azure platform. It is a parallel processing problem where a large set of images have to be operated upon to rank them based on a similarity to a provided query image by the user. Numerous instances of the algorithm run on the virtual machines provided in the Microsoft data centers, which run Windows Azure. Windows Azure is the operating system for the cloud by Microsoft Incorporation.

Cloud computing, image retrieval, encryption techniques, LP transformation

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K.Anitha, P. Madhura, "A Review of Security Technique for Content-Based Image Retrieval in the Cloud Computing", International Journal of Computer Sciences and Engineering, Vol.07, Issue.06, pp.128-131, 2019.

A system, or information arrange, is a computerized media communications organize which enables hubs to share assets. In PC systems, registering gadgets trade information with one another utilizing associations between hubs. In this paper, we devise a novel fingerprinting method that can be used as a product based arrangement which empowers machine-learning based characterization of progressing streams. The proposed plan is extremely easy to actualize and requires negligible assets, yet accomplishes high exactness. In particular, for TCP streams, we propose a unique finger impression that depends on zero-length parcels, subsequently empowers an exceedingly proficient inspecting technique which can be embraced with a solitary CAM rule. The proposed fingerprinting plan is vigorous to organize conditions, for example, clog, fracture, delay, retransmissions, duplications and misfortunes and to changing preparing abilities. Consequently, its execution is basically free of position and relocation issues, and in this way yields an appealing answer for virtualized programming based conditions. We recommend a practically equivalent to fingerprinting plan for UDP traffic, which profits by indistinguishable favorable circumstances from the TCP one and achieves high precision also. Results demonstrate that our plan effectively ordered about 97% of the streams on the dataset tried, even on scrambled information.

Machine Learning, Software-defined networking, Network traffic classification

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M.G. Divya, "A Review on Traffic classification Based on Zero-Length Packets", International Journal of Computer Sciences and Engineering, Vol.07, Issue.06, pp.132-134, 2019.

Cloud computing uses the concepts of scheduling and load balancing to move around tasks to underutilized VMs for effectively sharing the resources. The scheduling of the tasks in the cloud computing environment is an irrecoverable restraint and hence it has to be assigned to the most appropriate VMs at the initial placement itself. Practically, the arrived jobs consist of multiple tasks and they may execute the tasks in multiple VMs or in the same VM’s multiple cores. Also, the jobs arrive during the run time of the server in changeable random intervals under various load conditions. The participating various resources are managed by allocating the tasks to appropriate resources by static or dynamic scheduling to make the cloud computing more efficient and thus it improves the user satisfaction. Objective of this work is to introduce and evaluate the proposed scheduling and load balancing algorithm by considering the capability of each virtual machine (VM), the task length of each requested job, and the of multiple tasks. Performance of the proposed algorithm is studied by comparing with the accessible methods.

cloud computing, scheduling, load balancing, virtual machine

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S.Noortaj, K.Venkataramana, "A Review on Task Scheduling Approaches Based on Weighted Round Robin Algorithm in Cloud Environment", International Journal of Computer Sciences and Engineering, Vol.07, Issue.06, pp.135-138, 2019.

With the development of Internet technology, the volume of data is growing immensely. To deal with large-scale data, cloud storage has gained great attention from organizations and businesses because of its easy and efficient to adoption. Traditional cloud storage has come to rely almost exclusively on large storage providers acting as trusted third parties to transfer and store data. Though, cloud Provider offers considerable security features, with increasing demands and usage, these centralized systems have become major targets for hacks and data breaches. This makes the data vulnerable and prone to tampering. In this paper, to address the above problems we proposed a blockchain-based security scheme for distributed cloud storage, where users can divide their own files into encrypted data chunks, and upload those data chunks randomly into the federated clouds.

Cloud storage, Security, Blockchain, Architecture, Distributed Cloud computing, federated cloud

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Shaik. Munwar, K.Ramani, K. Madhavi, "Secure Data Storage Scheme Using Blockchain in Federated Cloud", International Journal of Computer Sciences and Engineering, Vol.07, Issue.06, pp.139-143, 2019.