Introduction 1 Background 2 Research.

Full Name Student ID Subject ITC571 – Emerging Technology and Innovations Assignment No Annotated Bibliography Due Date 08-09-2017 Lecturer’s Name Big Data Security Issues in Smart Systems Table of Contents I. Introduction 1 Background 2 Research Significance 2 Research Gap 2 Aim 2 Objective 3 Literature Review 3 II. MATERIALS AND METHODS 6 III. Results 8 IV. Conclusion 8 References 9 I. Introduction Security of data is the foundation of anyorganization in any field. The corporate organizations generate data for every second that could be stored in the cloud system. Many companies lack proper cloud storage system due to which data is insecure. Even though cloud storage system brings more benefits for corporates or other fields, still the security risks are big challenges due toits wide range of adoption. Background Big data is a collection of data that has growing number of privacy and security issues. However, technical advances are attended with various threats that can trick dangerous confidentiality risks. Privacy of data is the main concern of various investigators all over the globe. It has more security and privacy issues like viruses with USB technology and so on. Cloud computing has advanced, where it provides fast-developing virtual document storage based platforms, which can provide facilities with least expense in the corporate society. The main purpose of fog is to decrease more amount of information transported for handling, investigation, and storage, to speed-up the overall computing processes. At the same time cloud also have many security challenges. Research Significance The computer virus are the destructive risks that can damage the files and data in the system of any organization. The information plays a vital role and it is necessary to secure it. It has the feature of affecting other systems by escaping from one system to another. Research Gap The limitations are related to emerging technology thatare as follows: 1) Big data management and development of data analytics and reliability. 2) Integrating “Big Data” with cloud computing. 3) Requirements of scalability and real time are challenging. 4) Security and confidentiality challenges in cloud computing system and mobility fog. 5) Multiple sensors and chips are required. 6) Challenge to manage and collect large amounts of data. 7) Lacks software and security upgradation. 8) Lacks advanced algorithms. Aim To overcome the research gap it is necessary to increase the stability, security with advanced technology and update the anti-virus in the systems.The aim of this research is to investigate on security attacks in the corporate network. Objective The objective of this report is to analyze the security attacks in various corporate network and in other fields, to find the appropriate solution for the issues faced. The existing research works are utilized for the analysis, which shows the real time issues faced in the organizations. Thus, the analysis is based on real-time approaches. Literature Review According to [1], some security risks have been associated with universal serial bus. USB devices have U3 technology, which is very interesting for the user who need to access the hack tools. USB drivers have been used as hacking tool for the cell phones. Alternative technologies are available to hack the mobile phones, which easily hacks the information by running the USB drives. Portable application allows the attacker to hack the information that does not require any platform like U3. Description for different hack tools have been complied and data would be in portable format. The solution for this hacking tool portability is malware scanners. As per [2], many security issues are encountered in recent research like Trojan horses, worms and virus those are additional issues associated with hack tools based on USB technology. These attacks are launched into host computers directly.by analyzing the operating system’s vulnerabilities and malware attacks could be investigated. Packages in script format have been used in more systems with complex processes. There is no additional software are required.by detecting the behavior pattern of the antimalware these issue are encountered If malware in sleeping mode or inside the storage devices (USB) this result cannot address the issues directly. It is stated that, [3] Universal serial bus having many security issues like information security which is big issue in corporate world. Hacking tools based on multi payload was investigated in this work. USB technology having many open standard such as embedded security software for USB, universal serial bus drivers. To identify the attacks in the system and to investigate the taxonomy of attacks. Software attacks which is based on USB drivers was handled by security framework created in this work. According to [4], this research paper highlights implementation of Big Data and Business Intelligence tools. The authors state that the analytical tools can have negative impact on the company’s sustainability and its growth, due to competitive market. The authors conduct comparison between a couple of best positioned BI open source tools like Pentaho and Jaspersoft. The big data is processed with six databases with various sizes. The performance is measured with Computer Algebra Systems (CAS). Additionally, more focus is given on the extract transform and Load (ETL). The results of ETL displays that Jaspersoft BI contains increased CPU time when compared to Pentaho BI, where the performance metrics denotes 42.28%. Therefore, this research acts as a guidelines for various other researchers along with the IT professionals in terms of Big Data processing. It also helps in implementing the BI open source tool. As per [5] the authors state that, this research aims to conduct the data analysis withthe help of reviewed work from 1996 to 2016, where the implementation of algorithm models for data wrangling in Big Data is analyzed. The research paper compares and contrasts the algorithms with the data applications, to evaluate the best method. The data wrangling algorithms has various applications like in textual data, medical data, topological data,financial data, governmental data, galaxy data, and educational science and so on. This paper finds the best application area for this algorithm. Therefore, from the researchanalysis, the Clustering algorithm is recommended for the medical data, to be used for wrangling. It is stated in [6] that, the authors investigate the hypothesis of computer virus threat, and its impact on the targeted system. The measures are taken for protecting the systems, where the analysis is conducted based on the collected information from various test of scenarios and labs tests. The result of the research displays that the effective security measures must be taken to update the operating system. On the other hand, anti-virus are essential for prevention from any data loss or attack on the computer. According to [7], mostof the organizations subcontract their databases in terms of big data and then move it into the cloud service. The cloud computing knowledge brings many advantages for any organization, even though there are certain security risk issues, still it is considered as a big barrier. Therefore, this issue poses critical question such as-“Is the data secure in the cloud?” Due to this uncertainty, the author describes and identifies the most vulnerable characteristics of security extortions in the cloud environment. The investigation will focus on both the vendors and the end users,about the security issues that have beensensitive with recent populace developments and demands that have been keen for the improvement. As per [8], the development and enhancement of new technology in the Business society. That has directed to data storage and privacyissues. Theissue arises from the various management of lots of data, producedeach and every second in companies, exactly identified as “Big Data”. The author find a solution to this developing problem by investigation process and to evaluat
e possible solutions and analyzedthe content from top go through scientific. The overall system routines are analyzed by the consistency, availability and partition bigotry. All the three system based on Master Node Approach, unlike Dynamo, and Cassandra, it follows a Peer-to-Peer system. According to [9], the author aims to find different security concerns of big data in different areas and gives solution by analyzing results. The results of the content analysis recommend that the internet applications and financial institutes are trading with exact security problems, while social media and other trades are dealing with the privacy issues of sensitive data that have sensitive privacy concerns. After the overall analysis and valuation, ideas that can confront privacy issues are exposed by using a multiple algorithm method. By analyzing all these security concerns of big data and provide future investigator guidelines to solve them. As per [10], the author mainly discusses about the security and privacy issues of fog computing, by a comprehensive review along with recommended results for recognized problems. The author analyzes 49 issues, 32 issues have been provided with a result technique and remaining issues has not found solution, and suggests 35 requirement for better attention of investigators to these areas. It is evident from the entire review that, Fog computing is still new, and is still not well researched. There are many challenges in instituting results to the issues that are upraised, but finding solutions need urgent attention. According to [11] the traditional method of Paper Storage in the field of medical practice has entirely obsolete and necessities to develop and assist the patients with quicker diagnosis in critical situations. The author has analyzed the data storage and suggests better solution. This investigation has establishedthe useful tool that can be used to develop the medical data. Here, the functionality and value of each and every procedure and approaches are also determined. The author finds that by using the cloud and Big Data services, it is possible to increase the investigation of medical information in network of local Health Information System, it has huge measurements that guarantees convenient organization, informal extension, flexible asset, and low necessities for low technical related private medical components. The removal, containment and privacy of medical records must be sustained in for the purpose of compete with the developing challenges and demands. As per [12] the overall review of this paper will perform a comparative type of analysis associated with the Big Data Techniques which is obtained from 16 peer-reviewed in scientific magazines (2007-2015) about many Social Medias such as Google, Amazon, FB and Twitter. Since all these companies should need Data Ware House approach, Google has wished the difference of data Ware House Storages and difference of information transaction methods. Facebook and Twitter companies contains various requirements. Hence, Facebook needs the cascade based prediction system with programming language for the information transition and the Twitter requires a system set-up in order to handle the limitless data. Finally, the author clearly explains and identifies all the big data techniques according to their approaches that vary. The necessity of big data is great and these whole requirements are partially contingent on each alternative, as they are isolated. II. MATERIALS AND METHODS Initially, various existing papers were studied. Next, the considerations, implementation, issues and related solutions are jotted down. Based on the collected information, the analysis of the research is analysed, to find the appropriate solution for the security issues. Figure: Graphical Representation The following table represents the approach followed for accomplishing the objective of the research: Author Consideration Data Issues Solutions (Sushma Munugala,n. d) Reliability in online information, Cloud computing Integration, Computations based on optimization. Quick grid method is used to protect the data in cloud. Dos attacks, exfiltration, Encryption, Authorization in security Big data is related to medical health Organization. Analytics and Management in big data. Security level is increased by using cloud computing. (ThularaN.Hewage, 2017) Analysis is based on raw data. Comparison between the Data collections. Raw data collection (Google, Facebook, Twitter) Internationally shared database. Engine based on Query. Map reduce and Hadoop technology is used in Google file system. Sequential mode and parallel mode techniques are used. (Binara N.B Ekanayake, n. d) Analysis of Data processing. Heterogeneous fog modes. Security and privacy issues involved in Scalability and has less efficiency. In Fog applications micro-clouds are used to collect the RasberryPis. (Manbir Singh, n. d) Big data which is based on Security challenges. Evaluation of pattern, Data mining, Transmission of data. Monitoring real time issues. Protection based on layers. Outer layer coveres the inner layer data for security purpose. (Sultana Kalid, n. d) Scalability. Availability. Analysis of big table like Google product projects. It requires primary server to handling the datasets. High System Performance. (Kamalpreet Kaur, n. d) Access control, Protection of data. Management trust. Implementation of open source VLC Cloud environment having different challenges. Efficient end to end data verification. (R.A.Jeewantha,2007) Data collection, Evaluation of performance. Root mean square Seven different classifiers are required to measure the performances. Instances are classified correctly. (Harris A Khan, n. d) Cyber security Virus attacks Computer viruses and its attacks Antivirus programs like deduction based on behavior, heuristic and signature (Dung V Pham, Ali Syed, n. d) Attacks based on USB devices. U3 based hacking tools Hacking the portable devices easily without the knowledge of the user without even using U3. Data recovery software, switchable USB platform based on U3. (Dung V Pham,2010) User account control, Behavioral pattern analysis USB storage devices. Malwares including virus warms and other Trojan Horses can attack. Unsecured executable threats are blocked and antimalware system is updated. III. Results The result of this investigation is based on the real time security attacks like virus, warms and Trojan horses. Outer layer covers the inner layers of data, to protect the data and to provide security. IV. Conclusion The type of the harmful attack is clearly discussed in the analysis table. In addition to this type of attack, the detailed explanation of the steps of the attack is also discussed. The discussion is done in such a way that by understanding the investigation, the threat could be overcome. The data hacking prevention method has been completed by using the clustering algorithm. Then, the data processing has been analysed by using the heterogeneous fog mode method. The analysis determines that recovery software is a must, to retrieve the data if it is hacked. Therefore, advanced solution with improved technology must be implemented for securing the data. References [1]D. Pham, A. Syed, A. Mohammad and M. Halgamuge, “Threat Analysis of Portable Hack Tools from USB Storage Devices and Protection Solutions”, 2017. [2]D. Pham, M. Halgamuge, A. Syed and P. Mendis, “Optimizing Windows Security Features to Block Malware and Hack Tools on USB Storage Devices”, 2017. [3]D. Pham, A. Syed and M. Halgamuge, “Universal serial bus based software attacks and protection solutions”, 2017. [4]A. Gupta, A. Syed, A. Mohammad and M. Halgamuge, “A Comparative Study of Classification Algorithms using Data Mining: Crime and Accidents in Denver City the USA”, 2017. [5]V. M., A. Syed, A. Mohammad and M. N., “Pentaho and Jaspersoft: A Comparative Study of Business Intelligence Open Source Tools Processing Big Data to Evaluate Performances”, International Journal of Advanced Computer Science and Applications, vol. 7, no. 10, 2016. [6]C. Bashyal, M. Halgamuge and A. Mohammad, “Review on Analysis of the A
pplication Areas and Algorithms used in Data Wrangling in Big Data”, Charles Sturt University. [7]H. Khan, A. Syed, A. Mohammad and M. Halgamuge, “Computer Virus and Protection Methods Using Lab Analysis”, Charles Sturt University. [8]K. Kaur, A. Syed, A. Mohammad and M. Halgamuge, “Review: An Evaluation of Major Threats in Cloud Computing Associated with Big Data”, 2017. [9]S. Kalid, A. Syed, A. Mohammad and M. Halgamuge, “Big-Data NoSQL Databases: A Comparison and Analysis of “Big-Table”, “DynamoDB”, and “Cassandra””, 2017. [10]B. Ekanayake, M. Halgamuge and A. Mohammad, “Review: Security and Privacy Issues of Fog Computing”, 2017. [11]S. Munugala, A. Syed, G. Brar, A. Mohammad and M. Halgamuge, “The Much Needed Security and Data Reforms of Cloud Computing in Medical Data Storage”, 2017. [12]T. Hewage, M. Halgamuge, A. Syed, A. Mohammad and C. Bellamy, “Review: Big Data Techniques of Google, Amazon and Social Networks from 2007-2015”, 2017.

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