ENISA Big Data Threats Report | Assignment
Added on 2019-11-20
12 Pages3688 Words260 Views
Running head: ENISA BIG DATA THREATS1ENISA Big Data ThreatNameInstitutionProfessorCourseDate
ENISA BIG DATA THREATS2OverviewIn current business market, Big Data has come to be a norm of the day as it combinesvarious technological aspects. Some of the aspects of Big Data are; distributed systems, Internetof Things (IoT), communication networks, distributed multimedia sensors and web basedapplications which are being sued for business transactions in modern world. Due to its increasein market activities and maturity in system development, Big Data is currently being adopted bymany businesses in daily operations (Kerikmae, 2014). The case study provides a descriptiveproof of how Big Data is of great importance and efficiency it brings into the market in terms ofdecision making in complex organizational structure. Bid Data is expected to provide animportant aspect economy as far as businesses and world economy are relying on data forcomplex organizational decision making. Big Data will soon be a necessity of business becauseits application is expected to grow from normal business activities to military and businessintelligence application. In this regard, due to value of data being used in various businesses, datasecurity becomes a fundamental aspect due to number of threats facing Big Data. Big Data hasturned to be target of attack in business, by threat agents and it is expected the nature of attackwill be growing rapidly (Tryfonas, Askoxylakis & International Conference on Human-Computer Interaction, 2015). Data security threats is alarming rapidly because of need andimportance of organizational data to competitors and even other non- interested parties. Thismakes Big Data security core of any business that makes use of its services to transact businessactivities. The ENISA Data threat considers various scenarios in data security. It focuses onordinary data threat which involves Big Data replication strategy in storage and frequencyinvolved in organizational information sourcing. According to Axelrod (2013), in data storage
ENISA BIG DATA THREATS3replication strategy, data leakage and its related degradation threats are some of the emergingspecific Data security lapses. With emergency of Big Data, there is significance need for dataprivacy and protection of organizational data. Similarly, there is growing demand and interest oforganizational assets which owners has to put a lot of privacy. In regard to organizational need tosafeguard its assets, there is emergency of complex ecosystem of desirable securitycountermeasures which should be planned and be executed to protect organizational data.Application of privacy and data protection has been implemented as some of the measures beingused by organizations to uphold good security practices and lower data risks encountered in BigData. Lastly, there is provision of existing gaps when analyzing, comparing Big Data threats andnecessary counter measures in solving data security lapses. Mainly, this analysis revolves aroundmoving from traditional data approaches, coming up with Big Data solution specifications,developing a focus on gaps and other needs in regard to current organizational standards whileplanning on standardization. Additionally, according to Felici & Fernandez-Gago (2015), thereis a focus on professional training specialization, defining tools to be implemented on securityand privacy of Big Data, selecting and identifying Big Data assets while making it easy tomitigate data threats and risks. PresentationWeb BrowserDesktopsMobile DevicesWeb ServicesAnalytics & Computing modelsQuery & Reporting Map ReduceStream Analytics Advanced analytics Data storageNo/New SQL databaseDistributed File SystemsRDF StoresIntegration processETLMessagingAPIInfrastructureData sourcesStreaming Data from sensorsUnstructured DataSemi-Structured dataStructured Data
ENISA BIG DATA THREATS4Insufficient Web Application SecurityHolding to the fact that most of organizations rely on various applications to contact orinterface with their customers, data security has become one of the challenging issue(KORSTANJE, 2017). Each application need to be secured in order to make all transactionssecure and safe. In regard to Big data security, organizations has to make sure all transactions aresecure and data collected from customers is free from manipulation and transactions are real andfree from manipulation. Some of attacks that are prone to data include; insufficientauthentication occurs when organizational website allows attackers to have access to verysensitive functionality and content without being authenticated by the system in the right manner.A good example of the system that has been permitting users without undergoing properauthentication procedures. ENISA Big Data threat on authentication procedures has to follow thedue procedure in regard to available online data resources. Proper authentication proceduresstipulates that, any web application should not give direct access to Big Data infrastructurewithout requesting proper user identity. To facilitate complete authentication procedures,websites and other applications which are used by organization to transact and communicatewith customers should involve location hiding (Lepofsky, 2014). This makes it possible toprotect users’ point of operations. To ensure maximum security of the system, ENISArecommends that, system should hide their specific locations in which they are operating from. Consequently, Web shell where its functionality is based on scripts which is uploaded onwebservers to facilitate remote user authentication and administrative checks as it providesorganizational internal operations. Generally, web-shell is described as malicious scripts whichare used by attackers targeting websites that escalates continuous access to any web applicationthat has been attacked (Harwood, 2015). In regard to persistent system remote access, web shell
End of preview
Want to access all the pages? Upload your documents or become a member.
Related Documents
Case study on Risk Management of Big Datalg...
|15
|3274
|170
Big Data Threat Landscape of Europe- Assignmentlg...
|15
|3480
|152
Big Data Analysis | ENISAlg...
|16
|3718
|133
Analysis of the Big Data Threats- Assignmentlg...
|13
|3388
|176
IT Risk Management | Assignmentlg...
|13
|3398
|75
IT RISK MANAGEMENT Case Scenario: Big Data Securitylg...
|13
|2769
|478