Cloud computing technology and legal challenges
Law influences society and society influence the lawmaking procedure. This symbiotic relationship is unavoidable. Any change in society has an impact on the legal process. Technology is no exception to it. Technology is today’s lifeline. Technology has become part and parcel of everyone’s daily life. Law and technology are becoming two balances of the scale by which human behavior is controlled. It is interesting to observe how these variants, law, and technology interact with each other and what effect is caused in society by such interaction. With the latest technological development in cloud computing, an opportunity has been created for researchers to investigate the action and reaction formula of law and technology on society. Cloud computing technology is very popular in the present days. It is the new technology that is looked upon by industries. Nowadays cloud computing is gaining popularity amongst business community because of its features like low cost, easy maintenance, scalability etc. Indian business is also adapting to cloud computing very rapidly. India is outsourcing in the field of cloud computing services. This increase in the adaptation of cloud computing technology is not without risks, the advantage of cloud computing technology comes with many disadvantages. As cloud computing technology transcends boundaries it has resulted in the spreading of legal problems like violation of privacy of cloud customers, access, and safety in online handling of data, copyright issues of the data stored in cloud and questions of jurisdiction. If regulatory framework with regard to the above-stated issues is not clear, the confidence of stakeholders will not be boosted. Additionally, any breach of privacy, data loss or data theft, on cloud causes catastrophic effects. The purpose of this research is to find out the necessity of regulating cloud computing, to inquire about the available methods of cloud regulation and also to find out suitable methods of cloud regulation for India.
Published by: Sreevidya KV
Author: Sreevidya KV
Paper ID: V4I4-1304
Paper Status: published
Published: July 24, 2018
Speech reconstruction using machine learning approach for speech impaired persons
The speech disordered persons are able to produce speech which sounds like they are whispering. The main objective of this work is to reconstruct the abnormal to normal sounding speech by using MFCC coefficients to extract the feature and use these to train cascaded Gaussian Mixture Model (GMM) and Objective measures are used to evaluate the performance of the work. The data used for the work are from WTIMIT online corpus and the speech signals recorded from speech impaired subjects. In this work STRAIGHT toolbox is not employed for its complexity and muffled voice. The obtained SNR is reduced
Published by: Kruthika R, Rajeswari P
Author: Kruthika R
Paper ID: V4I4-1307
Paper Status: published
Published: July 24, 2018
Time based electricity and load shedding monitoring using embedded systems
Electricity is one of the most important requirements of modern civilization, without which various indispensable applications will bind to bring to a standstill. As we know that demand for electricity is increasing nowadays. So electric utilities prefer load shedding when the demand exceeds the supply. Thus in a distribution system, it needs to be precisely measured for the specific period of time. The Time Based Electricity and Load Shedding Monitoring Using Embedded Systems is a reliable & effective load shedding technique that takes over the manual task of switch ON/OFF the electrical supply with respect to time. It uses a software-based real-time clock (RTC) interfaced to the ARM processor. The paper on "Time Based Electricity and Load Shedding Monitoring Using Embedded Systems" will provide real & competent load shedding techniques such that distribution substation can be monitored & load shedding from one particular place for more than one cities.
Published by: Abhishek Pawar, Zainab Mizwan
Author: Abhishek Pawar
Paper ID: V4I4-1302
Paper Status: published
Published: July 24, 2018
Privacy and trust in cloud computing
This paper focuses on analyzing security and privacy problems facing cloud computing. The major issue discussed in the research that of losing control of data by both the cloud service providers (CSPs) and cloud service users (CSOs). Cloud computing offers organizations an innovative business model to adopt IT services without having to incur massive investment costs. A general analysis of the cloud is provided including its various forms. The growth and development of cloud computing technology are hampered by the fears of losing control of sensitive data by corporations and individuals. Solutions regarding this problem are discussed., and an intensive elucidation of the optimal one is included.
Published by: Faisal Alghayadh, Yasamin Alagrash, Debatosh Debnath
Author: Faisal Alghayadh
Paper ID: V4I4-1314
Paper Status: published
Published: July 24, 2018
Static pointer compression
Static Pointer Compression automatically identifies and transforms instances of type-safe data structures, replacing pointers in the data structure with smaller integer offsets from the start of the pool they are located in. Because pool allocation divides a program up into pools, it allows recursive data structures to each grow to 232 bytes and in some cases 232 nodes, without encountering a runtime error. However, the possibility of this runtime error is not acceptable for all domains. Static Pointer Compression can speed up pointer intensive programs from 20% to 2x in extreme cases over pool allocation, matching the performance of programs compiled to use native 32-bit pointers in many cases. In cases where the use of 64-bit mode enables features that are not available in 32-bit mode e.g. the AMD64 architecture, pointer compression can even beat native 32-bit performance. The pointer compression runtime library is almost identical to the standard pool allocator runtime. The only two functionality differences are that it guarantees that the pool is always contiguous and that it reserves the 0th node to represent the null pointer. The library interface is also cosmetically different in that the memory allocation/free functions take indices instead of pointers, and numbers of nodes to allocate instead of the number of bytes
Published by: Pramod Kumar
Author: Pramod Kumar
Paper ID: V4I4-1315
Paper Status: published
Published: July 24, 2018
Intrusion detection based on ANN by analyzing network traffic parameter
Nowadays, every individual is interchange the data from information systems, that are more open to the Internet and communication medium, the value of security of networks is extremely increased because of its tremendous utilization. In Internet different types of server are connected to each other now they are under the threats of network attackers. Actually, Intrusion Detection System (IDS) is the second level of defense for which it can be the most powerful system that handles the Attacks done at computer System by making alerts to do the analysts take some sort of actions to prevent this Attacks. IDS are based on the Principle of that an attacker behavior will be clearly different from that of a genuine user. In the proposed system we use a KDD-NSL dataset which will be as the first line of implementation for collect different attribute related to network packet then extract certain attributes from the actual dataset and use such attribute parameter is used to make training dataset and save it into the database. Our training dataset includes 4500+ data rows of values and forty-one attributes. Then in next step is to implement a real-time IDS again find out the different network packets features from dataset according attribute then load training dataset then apply artificial neural network algorithm which is work in three layers input layer, output layer and hidden layer which is a Back Propagation (BPN) and Feed Forward (FF) algorithms so that it provides two outputs normal packets and attacks packet. Proposed system evaluated on the base of performance are classified correctly for both anomaly-based detection and misuse based detection using a dataset of network packets and normal packets.
Published by: Rahul R Bhoge, Dr. M. A. Pund
Author: Rahul R Bhoge
Paper ID: V4I4-1323
Paper Status: published
Published: July 24, 2018
