Cy­ber­se­cu­rity tech­nol­ogy in­no­va­tion

As dig­i­tal con­nec­tiv­ity in­creases, there are higher lev­els of threat. These in­ter­est­ing cy­ber­se­cu­rity in­no­va­tions could tighten se­cu­rity of data sys­tems from be­ing com­pro­mised by cy­ber-at­tacks.

Distinguished Magazine - - CONTENTS - RAFIAA KHAN

As the num­ber of cy­ber­se­cu­rity breaches are on the rise, there is def­i­nitely an in­creased re­spon­si­bil­ity of pro­tect­ing cus­tomer data. Hack­ers who threaten to com­pro­mise user in­for­ma­tion are on the rise and they are com­ing up with big­ger and bet­ter ways to do so. This said, there def­i­nitely should be bet­ter ways to deal with such threats and that’s where cy­ber­se­cu­rity in­no­va­tions come to play which will help deal with these breaches much more suc­ces­sively. As dig­i­tal con­nec­tiv­ity in­creases, there are higher lev­els of threat. Here we dis­cuss three of the most in­ge­nious cy­ber­se­cu­rity in­no­va­tions that could tighten se­cu­rity of data sys­tems from be­ing com­pro­mised by cy­ber-at­tacks.


Deep learn­ing to pro­tect against hacker at­tacks and mal­ware is very rarely dis­cussed. Although the big­gest tech­no­log­i­cal com­pa­nies like Sales­force, Mi­cro­soft, Face­book, and Google have been in­cor­po­rat­ing deep learn­ing in their prod­ucts, the in­dus­try of cy­ber­se­cu­rity is still in its nascent stages.

Deep learn­ing can­not de­ci­pher all the prob­lems of In­foSec as it re­quires im­mense la­beled datasets which some­times are not eas­ily ob­tained. How­ever, there is def­i­nitely an im­prove­ment in this area due to the deep learn­ing net­works. Net­work in­tru­sion de­tec­tion and mal­ware de­tec­tion are ar­eas where deep learn­ing has shown im­mense de­vel­op­ment. These net­work in­tru­sion de­tec­tion sys­tems are usu­ally sig­na­ture and rule based con­trols that are used to find threats. An­tag­o­nists change the sig­na­ture of the mal­ware and eas­ily es­cape the de­tec­tion sys­tems. They use an anony­mous net­work which makes it harder to de­tect or trace traf­fic for the se­cu­rity de­fend­ers.

Ar­ti­fi­cial In­tel­li­gence(AI) and ma­chine learn­ing are in­te­gral com­po­nents of deep learn­ing. In these tech­nolo­gies, there is a high amount of im­por­tance for sys­tems se­cu­rity. Ano­ma­lous be­hav­iour is the main fo­cus of deep learn­ing. At­tacks can stream from lit­er­ally any end, hence it is ab­so­lutely cru­cial to keep track of the lat­est tech­nolo­gies, and deep learn­ing is an im­por­tant tech­nol­ogy that can help scru­ti­nize en­ti­ties at all lev­els.


Although the cloud has been around for decades, it did take com­pa­nies a long time to fully use the tech­nol­ogy. To­day, the cloud has be­come om­nipresent, as we store lit­er­ally our very iden­ti­ties, that com­prise of all our data such as busi­ness files, email ac­counts, mem­o­ries, videos and pho­tos. Cloud ser­vices se­cure data saved within the cloud and also grips the meta­mor­phic cloud in­dus­try to safe­guard the end­point users that uti­lize the ser­vice. Cy­ber­se­cu­rity must progress to the cloud, if it wants to de­feat and pre­dict at­tacks in real time. The cloud grips im­me­di­ate an­a­lyt­ics and big data over a large space of end users to im­me­di­ately ad­dress the known about threats and also fore­tell threats that at­tempt to en­gulf se­cu­rity.

Cloud se­cu­rity must cre­ate a col­lec­tive ap­proach that scru­ti­nizes event streams of ab­nor­mal and nor­mal ac­tiv­ity of all users to con­struct a threat ob­serv­ing sys­tem. Many users grip the same en­vi­ron­ment of cloud. Cloud se­cu­rity is es­pe­cially a match to build a col­lec­tive en­vi­ron­ment that im­me­di­ately pre­dicts and al­lots threats among all the users within the cloud um­brella.

Cy­ber at­tack­ers con­tin­u­ously dis­tort our way of liv­ing with cre­ative new ways to is­sue mal­ware and steal our se­cu­rity should in turn work ac­tively to de­stroy the ter­ror­ists, at­tack­ers, and cy­ber spies. Now is the fu­ture of cloud se­cu­rity. The in­no­va­tive and pre­dic­tive se­cu­rity in the cloud will out­rage cy­ber at­tack­ers for many more years to come. The lat­est ap­proach to se­cu­rity will pro­vide a se­cu­rity with an ad­van­tage. Cy­ber­at­tacks de­pend on sur­prise and stealth to steal, de­stroy, and dis­rupt which are the weapons of a spy. This type of pre­dic­tive se­cu­rity will help de­tect the spies even be­fore they at­tack.


With the le­gal, fi­nan­cial, and rep­u­ta­tional costs re­volv­ing cy­ber threat in­ci­dents and other data breach in­ci­dents cor­po­rate net­work ad­min­is­tra­tors’ re­quest vig­or­ous pro­to­cols and tech­niques for run­ning the ac­cess priv­i­leges and rights of their users.

Hard­ware au­then­ti­ca­tion al­lows firms to ver­ify iden­ti­ties of their users and to al­lot net­work priv­i­leges to them while as­sur­ing their po­si­tion within the hi­er­ar­chy of the cor­po­rate. Ro­bust au­then­ti­ca­tion mea­sures act as a shield against in­fil­tra­tors and guards the en­ter­prise in case of fraud, iden­tity or data theft, and in­fil­tra­tion.

The most pop­u­lar op­tion world­wide is def­i­nitely the stan­dard com­bi­na­tion of pass­word and user name, how­ever due to the evolv­ing tech­nolo­gies and change in work prac­tices or­ga­ni­za­tions have started to seek other di­rec­tions. Car­ry­ing re­sources and in­for­ma­tion to on­line modes of dis­tri­bu­tion un­cov­ers a larger pool of di­ver­gent forms of data to pos­si­ble threat. There­fore, aug­mented pro­to­cols of au­then­ti­ca­tion limit the ac­ces­si­bil­ity of these ad­van­tages to unau­tho­rized users.

And us­ing phys­i­cal at­tributes or unique hard­ware com­po­nents of users pro­vides de­vice own­er­ship and en­tire range of cir­cum­stances for in­di­vid­u­als. There are var­i­ous threats to se­cu­rity that is hard­ware-based.

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