Copy igh © 2023 by Au ho /s and Licensed by IADITI. This is an open access a icle dis ibu ed unde he C ea i e Commons A ibu ion License which pe mi s
un es ic ed use, dis ibu ion, and ep oduc ion in any medium, p o ided he o iginal wo k is p ope ly ci ed.
Jou nal o In o ma ion Sys ems Enginee ing and Managemen
2023, 8(1), 19218
e-ISSN: 2468-4376
h ps://www.jisem-jou nal.com/
Li e a u e Re iew
Repu a ion Sys ems: A amewo k o a acks and auds
classi ica ion
Rui Humbe o Pe ei a1*, Ma ia José Angélico Gonçal es2, Ma a Alexand a Gue a Magalhães
Coelho3
1 CEOS.PP/ Uni e si y o Maia, 4475-690 Maia, Po o, Po ugal
2 CEOS.PP, ISCAP, Poly echnic o Po o, 4465-004 Mamede In es a, Po o, Po ugal
3 ISCAP, Poly echnic o Po o, 4465-004 Mamede In es a, Po o, Po ugal
*
Co esponding Au ho :
hpe ei [email protected]
Ci a ion: Pe ei a, R. H., Gonçal es, M. J., & Magalhães, M. A. G. (2023). Repu a ion Sys ems: A amewo k o a acks and auds
classi ica ion. Jou nal o In o ma ion Sys ems Enginee ing and Managemen , 8(1), 19218. h ps://doi.o g/10.55267/iad .07.12830
ARTICLE INFO
ABSTRACT
Recei ed: 05 Dec 2022
Accep ed: 13 Jan 2023
Repu a ion and ecommending sys ems ha e been widely used in e-
comme ce, as well as online collabo a i e
ne wo ks, P2P ne wo ks and many o he con ex s, in o de o p o ide us o he pa icipan s in ol ed in he online
in e ac ion. Based on a epu a ion sco e, he e-comme ce use eels a sense o secu i y, leading he pe son
o us o
no when buying o selling. Howe e , hese sys ems may gi e he use a alse sense o secu i y due o hei gaps.
This a icle discusses he limi a ions o he cu en
epu a ion sys ems in e ms o models o de e mine he
epu a ion sco e o he use s. We in end o con ibu e o he knowledge in his ield by p o iding a sys ema ic
o e iew o he main ypes o a ack and aud ound in hose sys ems, p oposing a no el
amewo k o
classi ica ion based on a ma ix o a ibu es. We belie e such a amewo k could help analyse new ypes o a acks
and aud. Ou wo k was based on a sys ema ic li e a u e e iew me hodology.
Keywo ds: e-comme ce, us , epu a ion sys ems.
INTRODUCTION
Comme cial ansac ions equi e ha he pa icipan s us
each o he . This us gi es pa icipan s a no ion abou he isk,
hus, leading he pe son o conclude, o no , he ansac ion. In
e-comme ce, his sense o isk/secu i y based on us is much
mo e c i ical, pa icula ly when he e is no p io knowledge o
he pe son on he o he side. In e-comme ce, he use s mus be
awa e o some in e ela ed aspec s ega ding he o he
pa icipan in he ansac ion: (1) he eal iden i y; (2) hones y;
and (3) he quali y o he p oduc /se ice. Rega ding he eal
iden i y o he pe son, his can be a complex p oblem in on-
online ma ke places, due o he inco ec , o absence, o an
e ec i e iden i y alida ion o he pe son associa ed wi h he
use (p o iles o buye , selle , o bo h) in ha e-comme ce
pla o m. On he o he hand, ega ding he hones y o he use
and he quali y o he p oduc /se ice, hese issues ha e been
add essed by means o epu a ion and ecommenda ion
sys ems. In he case o B2C, when he e is a company o b and
associa ed wi h he pla o m, he buye s’ us is mainly based
on hei p io knowledge abou he c edibili y o ha company,
b and, o p oduc /se ice quali y, which may be addi ionally
complemen ed by a epu a ion and ecommenda ion sys em.
Repu a ion and us a e dis inc and in e ela ed concep s.
Jøsang e al. (2007) dis inguish “Reliabili y us ”, and “Decision
us ”. In he o me concep , he au ho uses he de ini ion
p oposed in (Gambe a, 1988). Howe e , he au ho s conside he
concep o us o be mo e complex, e e ing o his as such:
Decision us as: “T us is he ex en o which one pa y is willing o
depend on some hing o somebody in a gi en si ua ion wi h a eeling o
ela i e secu i y, e en hough nega i e consequences a e possible”
(Jøsang e al., 2007, p. 620). Rega ding o he concep o
epu a ion, he same au ho s de ine epu a ion acco ding o he
Concise Ox o d Dic iona y, as: “Repu a ion is wha is gene ally said
o belie ed abou a pe son's o hing's cha ac e o s anding” (Jøsang
e al., 2007, p. 620). Thus, du ing an e-comme ce ansac ion, us
and epu a ion a e wo subjec i e concep s on which he decision
o conclude is based, accep ing a ce ain le el o isk. This
obse a ion le s us iden i y he i s limi a ion o epu a ion
sys ems.
Pe ei a R. H. e al./ J INFORM SYSTEMS ENG, 8(1), 19218
2 / 10
As p e iously men ioned, he epu a ion o a p oduc o
use can be de e mined by means o epu a ion sys ems. In he
p esen wo k, we ocus on he epu a ion o he use s, since i
is a dis inc p oblem o p oduc epu a ion/ ecommenda ion,
despi e he ac ha hey sha e common p inciples. We should
no ice ha he e a e o he ypes o h ea s, such as he ones in
he ield o cybe secu i y, a in as uc u e and ne wo k le els,
ha we do no conside in his wo k, because hey a e dis inc
om he epu a ion sys ems as a mean o p o ide us o he
use s.
Repu a ion sys ems ha e been widely used in pee - o-pee
(P2P) ne wo ks o es ablishing a use 's epu a ion sco e based
on wha he gi es o he ne wo k and ge s, in e ms o he
c i e ia o choosing iles (Damiani e al., 2002). C owdsou cing
pla o ms also could apply simila p inciples, bu in his case,
i is o es ablish a a ing sco e o he use ’s epu a ion in e ms
o he alue o asks (Gong e al., 2021). In heo y, all
collabo a i e ne wo k en i onmen s could bene i om
epu a ion sys ems as a mean o p o ide us . In he con ex o
ou wo k, e-comme ce ma ke places, such as Amazon and
eBay, also apply epu a ion sys ems in o de o enable hei
use s o a e o he use s. This is o say, ypically a buye a es
a selle a e a inished ansac ion. Ou ocus will be on his
la e case, in which he us o an e-comme ce use , a he
momen o deciding abou a ansac ion, is based on he
epu a ion o he o he pa icipan .
We expec o con ibu e o he inc ease o knowledge in he
ield, by answe ing he ollowing esea ch ques ion:
Wha has been esea ched abou he mos common a acks and
auds on e-comme ce pla o ms ha may a ec he use ’s us based
on epu a ion sys ems?
In o de o answe his ques ion, we choose a sys ema ic
li e a u e e iew as me hodology using h ee ci a ions
da abases: Web o Science, Scopus, and Google Schola . Nex ,
we p oposed a new amewo k o a acks and aud
classi ica ion. We belie e ha such a amewo k can be a use ul
ool o analysing new ypes o a acks and aud, hus,
con ibu ing o he knowledge in he ield.
In he nex sec ion, we p esen he concep s ela ed o
epu a ion sys ems ocusing ou discussion on e-comme ce
communi ies. In he sec ion Me hodology, we p esen he
me hodology used, based on a li e a u e e iew. The
discussion, abou he ypes o a acks, and auds and how
hese secu i y issues a e classi ied in he li e a u e, is p esen ed
in he sec ion Discussion. A e , we discuss ou p oposal o a
new amewo k o classi ica ion and pe o m i s alida ion
based on he scena ios ound in he li e a u e. We inish he
pape p esen ing ou inal ema ks and he ocus o ou u u e
wo k.
BACKGROUND ON REPUTATION
SYSTEMS
In o de o con ex ualize he eade as o he weaknesses o
epu a ion sys ems, we conside i impo an o cla i y some
concep s, p inciples and s a egies ha a e usually adop ed in
hese sys ems.
The scope o he p esen pape is epu a ion sys ems o e-
comme ce use s, howe e , he discussion o he ollowing
aspec s and p inciples is gene alizable o o he ypes o
collabo a i e ne wo ks, as well as o p oduc ecommenda ion
sys ems in e-comme ce. Jøsang e al. (2007) dis inguish
epu a ion sys ems om ecommenda ion sys ems e e ing o
hem as collabo a i e sanc ioning and collabo a i e il e ing. In
epu a ion sys ems (i.e., collabo a i e sanc ioning), he use is
judged a e a ansac ion. This con as s wi h he
ecommenda ion sys ems (i.e., collabo a i e il e ing), which a e
based on di e en as es and he subjec i e opinions o he use s.
Hend ikx e al. (2015) p opose a axonomy o epu a ion
sys ems, which, a he i s , classi ies he epu a ion sys ems as
implici and explici . Acco ding o he au ho s, implici
epu a ion sys ems a e sys ems ha do no ha e a de ined
epu a ion sys em, al hough epu a ion in o ma ion is used by
i s membe s o assis in decision making. Examples o such
epu a ion app oaches exis in social ne wo ks (e.g., Facebook
and LinkedIn), in which we can ex ac some deg ee o us om
he in o ma ion ga he ed h ough iends o iends. Ano he
example is Google’s sea ch engine, in which he o de o he
sea ch esul s ep esen s a anking o pages, based on he
epu a ion o each page. The epu a ion is de e mined by he
numbe o links ha poin o he page, and whe e he links
o igina e (Hend ikx e al., 2015). On he o he hand, explici
epu a ion sys ems ha e implemen ed a model ha enables he
es ima e o a epu a ion using a sco e. The la e a e he ocus o
he p esen pape .
The epu a ion es ima ion model encompasses he h ee
dimensions (1) sou ces and ypes, o da a, (2) he algo i hm based
on ma hema ical calcula ions and (3) he ype o ou pu o he
epu a ion sco e and how i is dissemina ed. In (Ho man e al.,
2009), he au ho s e e o hese h ee dimensions as Fo mula ion,
Calcula ion and Dissemina ion. The accu acy o he epu a ion
sco e depends on he e ec i eness o he model, as well as he
ypes o h ea s ha i is immune o. Ano he cha ac e is ic o he
model is i s a chi ec u e, which is a cen al o dis ibu ed sys em.
On he second le el o he axonomy p oposed by Hend ikx e al.
(2015) he iden i ied aspec s a e sys ema ized, as well as
discussed in o he wo ks (Ho man e al., 2009). In he ollowing
sec ion, we will b ie ly discuss hese aspec s.
Sou ces and ype o da a
The sou ces o in o ma ion ha suppo he o mula ion o
epu a ion p o ide he aw da a ha eeds he algo i hm
implemen ed a he compu a ional le el. This da a is di e se and
complemen a y o each o he . We can g oup i in o wo main
sou ces: Manual and au oma ic. Ho man e al. (2009) sugges he
ollowing classi ica ion o sou ces o in o ma ion:
 Manual sou ces a e ob ained om human eedback, usually
in he o m o use a ings o o he iden i ies based on he
expe ience o a single ansac ion such as he eedback in a
ma ke place, a speci ic ime pe iod o a bi a y eedback;
 Au oma ic sou ces a e ob ained au oma ically ei he ia
di ec o indi ec obse a ion.
o Di ec obse a ions p o ide da a ega ding di ec ly
obse ed e en s such as he success o ailu e o
Pe ei a R. H. e al./ J INFORM SYSTEMS ENG, 8(1), 19218
3 / 10
in e ac ion, he di ec obse a ions o chea ing, o in
he case o he P2P ne wo k, he measu emen o
esou ce u iliza ion by neighbou s;
o Indi ec obse a ions a e ob ained second-hand o a e
in e ed om i s -hand in o ma ion.
These sou ces o in o ma ion could in luence he epu a ion
posi i ely, nega i ely, o neu ally, acco ding o i s le el o
ele ance, calcula ed by he algo i hm implemen ed in he
sys em. Rega ding o he axonomy o he da a ypes, his da a
can be bina y, disc e e o con inuous. O he ypes a e possible
bu could es ic he ype and accu acy o he esul s o he
compu a ional algo i hm. In o de o achie e a quan i a i e
me ic on use epu a ion, he quali a i e-inpu da a ypes
could equi e he con e sion o a quan i a i e alue. Fo
example, ee ex e iews can complemen a nume ical sco e
bu equi e some manual analyses, which a e no iable, o
p ocessed by means o a i icial in elligen mechanisms in
o de o con e o a quan i a i e a iable.
The compu a ional app oach applied o calcula e he
epu a ion alue o he a ge
The esul o he algo i hm ha compu es he da a,
ob ained om manual o au oma ic da a sou ces, consis s o a
me ic ega ding he epu a ion o a use , which in gene al is a
quan i a i e one. Se e al algo i hm-based app oaches o
epu a ion models can be ound in he li e a u e (C. Della ocas,
2000; Hend ikx e al., 2015; Panagopoulos e al., 2017). The
main challenge placed on he designe o such algo i hms is
choosing which a e he inpu a iables and hei espec i e
weigh s o he ou pu me ic.
The empo al a iable is ano he ac o ha some models
conside in hei ma hema ical analyses, in which he impac
(o ele ance) o he eedback, o di ec /indi ec obse a ion,
dec eases wi h ime, which is da a ageing (Hend ikx e al.,
2015).
Rega ding new use s, who do no ha e his o ical eco ds o
ansac ions, and o which an ini ial epu a ion sco e can be
es ima ed, de aul neu al alue o epu a ion is ypically se
o h. Panagopoulos e al. (2017) discuss some app oaches o
dealing wi h newcome s, as well as o he economic and social
issues such as inducing use pa icipa ion, using incen i es,
and dealing wi h ecip oci y and e alia ion.
O he app oaches such as he ones based on machine
lea ning (Wang e al., 2020), o au oma ic de ec ion o alse o
un ai a ings, o o he s blockchain-based (Zul iqa e al., 2021)
app oaches, in which he inancial model is no iable o a
dishones use . Fu he mo e, in dis ibu ed a chi ec u es
epu a ion da a is sha ed among se e al e-comme ce
pla o ms. Below, in he subsec ion 0, we de ail his discussion.
The ou pu epu a ion sco e can be classi ied as ei he
bina y, disc e e, o con inuous. A bina y one could ep esen i
he use is epu able o no . The disc e e ou pu s, o example,
one o i e s a s, de ine he le el o epu a ion, as well as he
con inuous sco es, bu in his case, gi e a much ine-g ained
classi ica ion.
Accu acy and immuni y o he epu a ion model
The accu acy o he model depends on he quali y o he inpu
da a and he obus ness o he algo i hm and ma hema ical
app oach. Addi ionally, he accu acy can be subjec o aud and
manipula ion. These h ea s o he epu a ion sys ems ha e wo
possible pu poses: o inc ease o dec ease he epu a ion o a
use , based on a malicious s a egy (Kou ouli & Tsalga idou,
2012). In he Discussion Sec ion, we will examine hese h ea s in
de ail, which is he ocus o he p esen pape .
The incen i es o pa icipa ion in a ing he ansac ion a e
one app oach o inc ease he olume o inpu da a, which is
impo an o ge eliable ou pu s. Howe e , Panagopoulos e al.
(2017) claim ha , al hough use pa icipa ion is necessa y o
success ul eedback-based epu a ion sys ems, mos e-comme ce
communi ies do no p o ide any kind o incen i es o encou age
i . Tha is due o he ac ha e-comme ce pla o ms usually
achie e good enough pa icipa ion h ough he mu ual exchange
o a ings be ween he membe s in ol ed in he ansac ion,
which akes place igh a e i s comple ion, by cou esy. The
a o emen ioned app oaches, based on machine lea ning and
public blockchain ne wo ks, could help o mi iga e hese
p oblems.
Cen alized s dis ibu ed a chi ec u e
In epu a ion sys ems based on a cen alized a chi ec u e, he
da a is managed only by one en i y. I a use has wo accoun s,
each in a dis inc e-comme ce pla o m based on cen alized
epu a ion sys ems, hen he has wo p o iles, each one wi h i s
own epu a ion sco e, pe haps wo incohe en alues o
epu a ion. Se e al p oposals o decen aliza ion can be ound
in he li e a u e, bu o he simila p oblems eme ge
(Panagopoulos e al., 2017). In ecen li e a u e (Ahn e al., 2018,
2019; Dennis & Owen, 2015; Dhakal e al., 2019; Ka ode e al.,
2020; Mohe e al., 2009; Schaub e al., 2016; Zeynal and e al.,
2021; Zul iqa e al., 2021), blockchain-based app oaches a e
p oposed o enable a dis ibu ed a chi ec u e in epu a ion
sys ems in e ms o sha ing da a. Acco ding o he au ho s, hese
app oaches ensu e anspa ency and could help mi iga e some
ypes o known aud.
Zul iqa e al. (2021) s a e ha he cen al au ho i ies can
po en ially il e , ampe , add, o ejec p oduc e iews based on
hei p e e ence. Schaub e al. (2016) s a e ha , po en ially, a
cen alized sys em can be abused by he cen al au ho i y.
The managemen o use s’ epu a ion, based on paymen
sys ems, a e also p one o manipula ion by malicious en i ies,
which include he ad e ise s o owne s hemsel es, who may
gi e ex emely high o low a ings on pu pose (Ahn e al., 2019;
Dennis & Owen, 2015).
Dhakal and Cui (2019) p esen he same a gumen s, s a ing
ha he cu en cen alized sys ems a e silos and no anspa en
in he e iew p ocess. Besides he lack o anspa ency, hese
isola ed cen alized sys ems do no bene i om he epu a ion
da a o each o he . Zeynal and e al. (2021) s a e ha i is ha d o
de i e us models ha a e obus o a acks such as
whi ewashing and Sybil a acks, i use s do no sha e
in o ma ion.
Pe ei a R. H. e al./ J INFORM SYSTEMS ENG, 8(1), 19218
4 / 10
Ka ode e al. (2020), in he con ex o a el e iew sys ems,
s a e ha blockchain-based epu a ion sys ems enable
consume s o be con iden ha he e iew sco e is no a ec ed
by he pla o m p o ide s. Besides, he businesses can main ain
he same a ing sco e ega dless o he pla o m hey ake pa
in. Low-quali y e iew handling is a challenge o he global-
scale e iew sys em; howe e , his p oblem can be add essed
wi h au oma ic il a ion.
METHODOLOGY
Ou e iew can be ca ego ized as a sys ema ic e iew o he
scien i ic li e a u e on secu i y p oblems in use epu a ion
sys ems.
Sys ema ic e iews a e a o m o me a-analysis designed o
collec , in es iga e, and summa ise wha is known and wha is
no known abou a “speci ic p ac ice- ela ed ques ion” (B ine
e al., 2009). Sys ema ic e iews a e used ac oss a b oad ange
o disciplines. Quali a i e s udies ha e es ablished a place o
hemsel es wi hin he me hodologies, as e idenced by
ini ia i es such as he Coch ane quali a i e me hods g oup
(Dixon-Woods & Fi zpa ick, 2001) and ex books such as
Sys ema ic Re iews in he Social Sciences (Pe ic ew & Robe s,
2005) and An In oduc ion o Sys ema ic Re iews (Thomas e
al., 2017).
In his s udy, besides conduc ing he li e a u e e iew
ollowing i s p ima y objec i es acco ding o Mohe (2009) we
also subs an ia e he esul s ob ained wi h a li e a u e e iew,
p esen ing heo e ical pe spec i es and inno a ions om
leading au ho s in he ield. Acco ding o he au ho s, he
sys ema ic li e a u e e iew is ca ied ou in 3 s eps (Mohe e
al., 2009). Fi s , he esea ch ques ion is de ined; his is ollowed
by a esea ch p o ocol o e alua ing he selec ed scien i ic
a icles. The las s ep in ol es answe ing he esea ch
ques ions (in he i s s ep), based on he scien i ic a icles
iden i ied as ele an (in he second s ep). Figu e 1 summa izes
he s eps ollowed by he adop ed me hodology.
The i s s ep o he adop ed me hodology is ela ed o he
de ini ion o he esea ch ques ion o his s udy. The main
esea ch ques ion in ends o iden i y he s a e o he a
conce ning ou s udy cha ac e is ics. The e o e, ou esea ch
ques ion can be o mula ed as ollows, as abo e men ioned in
he in oduc ion sec ion: Wha has been esea ched abou he mos
common a acks and auds on e-comme ce pla o ms ha may a ec
he use ’s us based on epu a ion sys ems?
A e he de ini ion o he esea ch ques ion, he second s ep
was ela ed o he selec ion o he empi ical da a o be analysed.
Da a collec ion ook place in Oc obe 2022. We did no apply
any ch onological il e . In he i s phase, we ied a sepa a e
sea ch o each keywo d. In Web o Science Co e Collec ion
(WOS) we applied he ollowing s a egy: Sea ch: (TITLE-ABS-
KEY(" epu a ion sys em" and axonomy and a ack) OR TITLE-
ABS-KEY(" epu a ion sys em" and classi ica ion and a ack)
OR TITLE-ABS-KEY(" epu a ion sys em" AND ype a acks)).
In SCOPUS and Google Schola (GS) we ollowed he same
c i e ia. This sea ch esul ed in 38 a icles selec ed om WoS,
75 a icles selec ed om Scopus and 29 selec ed om GS. The
lis s we e expo ed o excel o u he analysis, and he
ollowing ields we e chosen: au ho s, i le, yea , link, abs ac ,
and keywo ds.
Figu e 1. Sys ema ic e iew s uc u e
Then, we e alua ed he a icles based on he c i e ia o
inclusion o de e mine hei ele ance o he s udy. An a icle
had o include he sea ch e ms as he co e echnology unde
analysis. This was ypically demons a ed by i s i le, abs ac ,
and keywo ds. We only selec ed academic pee - e iewed jou nal
a icles and con e ence p oceedings and excluded o he s,
namely: (a) a icles no ully a ailable, (b) a icles no a ailable in
English, (c) duplica e a icles, and (d) a icles ha did no discuss
secu i y issues in use epu a ion sys ems. Ou ini ial sea ch was
ca ied ou in Oc obe 2022 and yielded 142 a icles. Once we
elimina ed duplica es, we we e le wi h a popula ion o 96
a icles. A e , ou esea ch eam, including a p o esso and a
mas e ’s s uden , e iewed his collec ion o a icles o
ele ancy. In he i s ound, we assessed he a icles o
ele ance based on i le, abs ac , and keywo ds. This p ocess led
o he selec ion o 46 a icles. Any a icles we did no ag ee upon
we e also excluded. In he second ound o e isions, we
assessed he a icles based on he ull pape . We elimina ed 29
a icles ha did no p esen de ailed e e ence o a acks and
auds on he epu a ion sys em. Thus, we iden i ied 17 ele an
a icles o analysis, which a e lis ed in Table 1.
Pe ei a R. H. e al./ J INFORM SYSTEMS ENG, 8(1), 19218
5 / 10
Table 1. Selec ed A icles
Re e ence A icle Ti le
(C. Della ocas,
2000)
Immunizing online epu a ion epo ing
sys ems agains un ai a ings and
disc imina o y beha iou
(C. Della ocas.,
2000)
Mechanisms o coping wi h un ai a ings
and disc imina ion beha iou in online
epu a ion epo ing Sys ems
(Douceu , 2002)
The Sybil A ack. In: D uschel, P., Kaashoek,
F., Rows on, A. (eds) Pee - o-Pee Sys ems.
(C. N. Della ocas,
2003)
The Digi iza ion o Wo d
-
o
-
Mou h: P omise
and Challenges o Online Feedback
Mechanisms
(Jøsang e al.,
2007)
A su ey o us and epu a ion sys ems o
online se ice p o ision
(Ho man e al.,
2009)
A su ey o a ack and de ense echniques o
epu a ion sys ems
(Swamyna han e
al., 2010) The design o a eliable epu a ion sys em
(F aga e al., 2012)
A Taxonomy o T us and Repu a ion Sys em
A acks
(Kou ouli &
Tsalga idou, 2012)
Taxonomy o a acks and de ense
mechanisms in P2P epu a ion sys ems—
Lessons o epu a ion sys em designe s
(Feng e al., 2012)
Vulne abili ies and coun e measu es in
con ex -awa e social a ing se ices
(Yao e al., 2012)
Add essing Common Vulne abili ies o
Repu a ion Sys ems o Elec onic Comme ce
(Sänge e al.,
2015)
Reusable componen s o online epu a ion
sys ems
(
Kou ouli &
Tsalga idou, 2016) Repu a ion Sys ems E alua ion Su ey
(Panagopoulos e
al., 2017)
Modeling and E alua ing a Robus
Feedback-Based Repu a ion Sys em o E-
Comme ce Pla o ms
(Camilo e al.,
2020)
A Secu e Pe sonal
-
Da a T ading Sys em
Based on Blockchain, T us , and Repu a ion
(Zul iqa e al.,
2021)
E hRe iew: An E he eum
-
based P oduc
Re iew Sys em o Mi iga ing Ra ing F auds
(Zeynal and e al.,
2021)
A Blockchain
-
Enabled Quan i a i e
App oach o T us and Repu a ion
Managemen wi h Spa se E idence
DISCUSSION
Types o ulne abili ies and a acks
Della ocas (2000, 2000, 2003) ocused his wo k on he
audulen beha iou o use s when a ing o he s, in online
ading communi ies. The au ho has iden i ied wo scena ios:
(1) un ai buye a ings and (2) disc imina o y selle beha iou .
In he case o un ai buye a ings, he e a e wo scena ios: (1.a)
Un ai ly high a ings (“ballo s u ing”) and (1.b) Un ai ly low
a ings (“bad-mou hing”). In bo h cases, a selle colludes wi h
a g oup o buye s, bu in he i s case, “ballo s u ing” o
inc ease his own epu a ion and, o “bad-mou hing” o
damage he epu a ion o o he selle s, his compe i o s. This
can, po en ially, inc ease his o de s and dec ease he o de s o
his compe i o s. The second g oup o scena ios ela es o
disc imina o y selle beha iou : (2. a) ha m ul disc imina ion -
1 h ps://en.wikipedia.o g/wiki/Sybil_(Sch eibe _book)
a selle p o ides good se ice o he majo i y o buye s, excep a
ew speci ic ones ha hey “don’ like”. This kind o ac ion does
no ha e a g ea impac on he selle ’s epu a ion i he numbe
o “ ic ims” is small; (2.b) posi i e disc imina ion – In his
s a egic ac ion, he selle can po en ially inc ease his own
epu a ion by p o iding an excep ional quali y se ice o a ew
buye s and a e age quali y se ice o he es o he buye s. I he
numbe o p i ileged cus ome s is su icien ly la ge, his ac ion
is equi alen o Ballo s u ing, bu in an impe cep ible way,
wi hou ha ing o conspi e wi h hi d pa ies.
Douceu (2002), in he con ex o P2P ne wo ks, ollowing he
sugges ion o B ian Zill, inspi ed by a book1 da ed 1973 wi h he
same name, coined he e m Sybil a ack. In his ype o a ack on
ne wo k se ices, an en i y o ges mul iple iden i ies in he
sys em in o de o inc ease his in luence. In he con ex o e-
comme ce, he ypical scena io is an en i y ha can in luence he
epu a ion o a use , o p oduc by using mul iple iden i ies o
inse un ai a ings in o he sys em. A simila ype o a ack, also
based on a lack o e ec i e iden i y managemen , is
Whi ewashing. In his ype o a ack, a dishones buye is able o
whi ewash i s low us wo hiness by s a ing a new accoun
wi h he ini ial us wo hiness alue o using some ulne abili y
in he sys em. In (F aga e al., 2012), he au ho s dis inguish
be ween Re-en y and Whi ewashing. Acco ding o he au ho s,
in he o me case, i a acke s can c ea e new “iden i ies” eely,
his p esen s he oppo uni y o emo e a bad epu a ion by
c ea ing a new iden i y. In Whi ewashing, he a acke s can
epai hei epu a ion comple ely by using some sys em
ulne abili y. In ou opinion, Re-en y is a speci ic case o a
Whi ewashing a ack, in which he malicious use uses
ulne abili ies in iden i y managemen in o de o ge a new
iden i y wi h a clean epu a ion. Despi e hei dis inc pu poses,
Sybil, Whi ewashing o Re-en y a acks a e based on limi a ions
in he iden i y managemen mechanism mainly due o low e o ,
o low cos , o ge a new iden i y. The cen alized na u e o he
epu a ion sys ems, used in e-comme ce pla o ms ha don’
sha e he use iden i y da a, in la es he p oblem (Camilo e al.,
2020; Zul iqa e al., 2021)
In Swamyna han e al. (2010), he au ho s de ine he Chu n
a ack in he con ex o P2P ne wo ks as high a es o pee
u no e . In such a scena io, a signi ican numbe o pee s will
ha e ela i ely sho - e m accumula ed epu a ion sco es as a
esul o a small numbe o pas in e ac ions. In e-comme ce
pla o ms, his undesi able scena io can be enabled by he low
e o /cos o ge se e al iden i ies.
The Sybil a acks a e equen ly coupled wi h Collusion
a acks, in which he di e en iden i ies o a single en i y conduc
coo dina ed ac ions in o de o in luence he epu a ion o a use
o p oduc . Kou ouli and Tsalga idou (2012) iden i y h ee
a ian s o Collusion: (1) collusi e badmou hing and (2)
collusi e educing ecommenda ion epu a ion and (3) Collusi e
decei .
As we can obse e, all hese ypes o a acks on epu a ion
sys ems esul om ulne abili ies in one componen o he
unde lying epu a ion model o a chi ec u e o he sys em. The
a o emen ioned p oblems o lack o anspa ency in he
managemen o he epu a ion da a, discussed in he sec ion

Pe ei a R. H. e al./ J INFORM SYSTEMS ENG, 8(1), 19218
6 / 10
Backg ound on epu a ion sys ems, subsec ion 0, he dis inc
models and c i e ia o calcula e he use s’ epu a ion sco e, as
well as he cen alized na u e o he cu en epu a ion sys ems
make he mi iga ion o hose a acks a e y di icul ask.
In he li e a u e, one can ind se e al axonomies and
ca ego iza ions o hese ypes o a acks. In he nex sec ion, we
discuss ou indings in e ms o axonomies and classi ica ions
o a acks ha de i ed om ou sys ema ic li e a u e e iew.
Taxonomies o a acks
Feng e al. (2012) discussed h ee ypes o a acks: di ec ,
disguise, and misguidance a acks. A di ec a ack is common
in mos basic a ing sys ems. The a acke s p o ide dishones
a ings only on he i ems wi hin he a ack a ge se . Then all
use a ings o an i em a e compu ed o ob ain i s agg ega e
ecommenda ion sco e. Thus, he social ecommenda ion sco e
will e lec use s’ mains eam opinions o . On he o he hand,
disguise a acks and misguidance a acks a e ep esen a i e o
us -enhanced social a ing sys ems. Acco ding o he au ho s’
de ini ion, in hese epu a ion sys ems, he use us can be
de ined as a c edibili y measu emen o he a ing. Thus, in
hese wo ypes o a acks sophis ica ed s a egies o non-di ec
a ing a e applied in o de o educe he c edibili y o hones
use s while inc easing he c edibili y o he malicious ones.
Sel -p omo ing is an example o a disguise a ack. In he case
o a misguidance a ack, he s a egy aims a s a egically
making he sys em misjudge he hones a ing beha iou o be
dishones and he dishones a ing beha iou o be hones . We
classi ied he au ho s’ p oposal as simplis ic, because each
ca ego y o a ack is e y comp ehensi e, in which many
di e en ypes o a ack can be placed.
F aga e al. (2012) p oposed an a ack axonomy based on
he epu a ion sys em a chi ec u al model and a se o well-
known secu i y opics. In one dimension, he au ho s p opose
h ee basic p ocesses: us and epu a ion (T&R) in o ma ion
ga he ing, T&R calcula ion, and T&R dissemina ion. In he
second dimension, he au ho s p opose P ima y opics:
Au hen ica ion, Au ho iza ion, A ailabili y and
U ili y/p ocess; and De i ed opics: Iden i ica ion, Non-
epudia ion, Con iden iali y, In eg i y and Time In eg i y. Fo
ins ance, bad-mou hing and ballo -s u ing ega ds T&R
in o ma ion ga he ing and U ili y/p ocess p ima y opic.
Acco ding o he au ho s, U ili y means use ulness. I means
ha he ac ion an agen wan s o pe o m o e a esou ce could
be ca ied ou co ec ly. In his example o aud, he esou ce
is he use s’ a ings. The au ho s aim o p opose a holis ic
axonomy ha may include all known a acks and p o ides
s uc u ed ools o iden i y new a acks. In ou opinion, he
p oposed amewo k is e y complex, and no complian wi h
he comp ehensibili y equi emen o a good axonomy, as
s a ed by he au ho s.
Yao e al. (2012) dis inguish he ulne abili ies o epu a ion
sys ems in o wo ca ego ies: (1) sys em-based ulne abili ies –
ha ela e o he ounda ion and en i onmen o epu a ion
sys ems, and (2) me ic-based ulne abili ies ha ie o he
selec ed epu a ion me ic and i s upda es. These wo
ca ego ies encompass six secu i y equi emen s o he
epu a ion sys em, a a lowe le el, and a a highe le el o
compu a ion o epu a ion sco es and decision-making, i.e., he
epu a ion me ic. In he i s ca ego y, he au ho s include
ulne abili ies in he message exchange be ween sys em nodes,
agili ies in he sys em nodes in e ms o da a in eg i y, when
s o ing and p ocessing i , and he lack o e ec i e iden i y
managemen ha a oids malicious ac ions igge ed by mul iple
iden i ies o he same use . The second ca ego y ela es o he
agili ies in he model in which he epu a ion sco es a e based
on decision-making.
Kou ouli and Tsalga idou (2012, 2016), in he con ex o P2P
ne wo ks, and Panagopoulos e al. (2017), o e-comme ce,
p opose he ollowing axonomy o ypes o a ack: (1) S a egy-
Based A acks, (2) Iden i y-Based A acks, and (3) Un ai Ra ings.
This p oposal s ic ly ocuses on he epu a ion model on which
he me ics a e based. This axonomy p oposal includes he ypes
o a acks and hei a ian s known in he li e a u e. Howe e ,
despi e i s co e age, we obse e ha o he possible combina ions
o a ack could po en ially exis bu a e no included in his
axonomy, such as ecip oci y and e alia ion, as discussed by he
same au ho s in ano he pape (Panagopoulos e al., 2017).
Panagopoulos e al. (2017) also e e o o he issues om he
economic and/o social pe spec i es, which a e no a acks bu
may a ec he e ec i eness o he epu a ion sys ems as a means
o p o ide us in he e-comme ce communi y. The au ho s e e
o (1) he impo ance o inducing use pa icipa ion using
incen i es, as he a e age quan i y o eed-backs is insu icien o
ge an accu a e sco e o he epu a ion o a pe son, (2) dealing
wi h ecip oci y ( he au ho s men ion s udies whe e a s ong
co ela ion be ween buye and selle a ings a e iden i ied), and
e alia ion, and (3) how o deal wi h he epu a ion o
newcome s, in e ms ini ial epu a ion o hese use s.
Addi ionally, Panagopoulos e al. (2017) s ill e e o a
numbe o issues ound in decen alized epu a ion sys ems,
such as us p opaga ion (i.e., how o e ec i ely communica e
us in o ma ion in la ge-scale ne wo ks o loosely connec ed
en i ies (Zeynal and e al., 2021), and s o age o local and global
epu a ion in o ma ion.
Sänge e al. (2015) p opose a di e en app oach o axonomy
o a acks. The au ho s p opose, a he highes le el, o
dis inguish be ween selle a acks and ad iso a acks. In hese
majo classes, he au ho s classi y e e y ype o a ack in o wo
dimensions: a acke s and beha iou . A a lowe le el, he
a acke ’s dimension e e s o he numbe and cha ac e is ics o
he digi al iden i ies pa icipa ing in an a ack (one iden i y,
mul iple iden i ies o mul iple en i ies), which dis inguishes
Sybil and Collusion, and beha iou dimension (consis en o
inconsis en ). The au ho s claim ha hey a e ocused on he
gene al cha ac e is ics and symp oma ology o a acks, such as
he con inui y and he numbe o a acke s. We conside his
app oach o a axonomy e y compac and a he same ime
comp ehensi e, which makes i e y in e es ing. Howe e ,
app oach can be limi ing in e ms o e ec i e iden i ica ion o he
ype o a ack. Fo ins ance, we do no see how i is possible o
classi y he whi ewashing a ack, and he au ho s, do no p o ide
examples o addi ional in o ma ion. Ano he example is he
scena io o a dis ibu ed epu a ion sys em in which he
epu a ion da a is manipula ed.
Pe ei a R. H. e al./ J INFORM SYSTEMS ENG, 8(1), 19218
7 / 10
Ho man e al (2009) classi y a acks agains epu a ion
sys ems based on he goals o he epu a ion sys ems a ge ed
by hese a acks. The au ho s p opose i e ca ego ies o a ack:
(1) Sel -P omo ing, (2) Whi ewashing, (3) Slande ing, (4)
O ches a ed and (5) Denial o Se ice (DoS). We conside ha
his classi ica ion includes ulne abili ies a wo le els: a a
highe le el, in he epu a ion model, which includes he i s
ou ca ego ies, and a a lowe le el, he i h ca ego y ha
ela es o he DoS a acks. We conside his classi ica ion
incomple e, namely a he lowe le el, because DoS a acks a e
jus one o he se e al possible ypes a his le el, in his case,
a he ne wo k le el. We no e ha he e a e many o he ypes
o ulne abili ies a a low le el. Below, in he p esen sec ion,
we will discuss ou p oposal o a classi ica ion in which we
e e o hose o he possible low-le el a acks. Ano he aspec
o his p oposal is i s ocus on he a ack’s goal. Fo example,
ega ding he Whi ewashing a ack, we ask i he inal goal is
o escape om he consequences o a low epu a ion o o
manipula e someone’s epu a ion sco e.
In Table 2 we summa ize ou indings in e ms o
classi ica ions, p esen ing a b ie desc ip ion o he s uc u e
and i s ocus.
Table 2. Summa y o p oposed classi ica ions
Re e ence S uc u e Focus
(Feng e al.,
2012) Th ee ypes o a ack
e-comme ce and
collabo a i e
ne wo ks
(F aga e al.,
2012)
Bi-dimensional
amewo k: basic
p ocesses and opics
Repu a ion
sys ems in gene al
(Kou ouli &
Tsalga idou,
2012, 2016;
Panagopoulos e
al., 2017)
Hie a chical
classi ica ion o ype and
a ian s
P2P and e-
comme ce
(Sänge e al.,
2015)
A highes le el: selle
a acks and ad iso
a acks.
In hese majo classes:
wo dimensions:
a acke s and beha iou .
Elec onic
ma ke places
(Ho man e al.,
2009) Fi e ypes o a ack Repu a ion
sys ems in gene al
Limi a ions o he cu en app oaches o ca ego iza ion
In he p esen wo k, an a ack is an in en ional ac ion wi h
aud as i s objec i e, which a ec he epu a ion sys ems.
Addi ionally, o he issues can comp omise he accu acy o
epu a ion sco es; howe e , hey a e no a acks. In (Jøsang e
al., 2007) he "Bias owa ds posi i e a ing" is explained as
posi i e a ings simply ep esen ing an exchange o cou esies;
ei he he posi i e a ing is gi en in he hope o ge ing a
posi i e a ing in e u n, o he nega i e a ing is a oided due
o ea o e alia ion om he o he pa y.
We conside ha he e is a gap o ex ensibili y in he
p oposed classi ica ions ound in he li e a u e, as i is di icul
o classi y all a ian s o a ype o a ack because a sligh
a ia ion can change he gi en classi ica ion. In he nex
sec ion, we will discuss hese limi a ions compa ed o ou
p oposal.
PROPOSAL FOR A NEW FRAMEWORK
OF CLASSIFICATION
Types o aud and a acks in epu a ion models
Analysing he ypes o aud and a acks o he models used
in epu a ion sys ems, ounded on he li e a u e, we obse ed
ha he e a e wo undamen al le els o a ack, o dis inc na u e
(o igin and echnique), as well as he ield o esea ch. The o me
ca ego y ega ds all ulne abili ies a he ne wo k, in as uc u e
and applica ion le els. These may esul om bad de ini ions in
he sys ems, secu i y b eaches in he so wa e, w ong choices in
e ms o ne wo k a chi ec u e, missing de ence ools, such as
i ewalls, WAFs, IDS, lack o c yp og aphy in he s o ed da a o
messaging exchanging, among o he s. On he o he hand, he
second ca ego y encompasses he agili ies o he model ha
de ines he algo i hm, which ga he s and calcula es all me ics in
o de o es ablish a epu a ion sco e, as well as a chi ec u al
issues, such as cen alized s dis ibu ed o iden i y
managemen . Mo eo e , in gene al, hese a acks a he model
le el a e accomplished by membe s o he e-comme ce
communi y, e.g., a use which has been egis e ed o a long ime
in he Amazon o eBay ma ke place, con as ing wi h he a acks
a he le els o he ne wo k, in as uc u e o applica ion, which,
in gene al, a e pe pe a ed by ou side s.
Due o he na u e o he a acks, i s i s ca ego y is ou o he
scope o ou wo k. In he p esen wo k, we ocused on he
ulne abili ies o he model and he a chi ec u al issues on which
he epu a ion o mula ion is based. Thus, we will con inue ou
discussion ocused on he ulne abili ies o he epu a ion
model.
We s a ou discussion by obse ing ha any malicious
ac ion alls in o one o wo aud cases: o inc ease o dec ease
he epu a ion o an en i y o p oduc /se ice. Fo ins ance, ballo
s u ing and bad-mou hing a e he same ulne abili y, bu wi h
a di e en ype o aud as a goal.
In ano he obse a ion, we no ice ha many a acks a e
combina ions o p imi i e ypes o a ack leading o se e al
a ia ions o he same ype o a ack. Fo ins ance, a g oup o
en i ies can collude by means o un ai a ings (collusion + un ai
a ings), o he collusion o se e al iden i ies, o he same en i y,
combined in o de o gi e un ai a ions, i.e., a Sybil a ack.
These obse a ions led us o p opose a no el app oach based
on a classi ica ion o mul idimensional a ibu es.
P oposal o a ma ix o a ibu es
Ou p oposal is based on a classi ica ion o mul idimensional
a ibu es. Each ype o a ack has he ollowing i e a ibu es,
each wi h se e al possible alues:
1) Type o aud: (a) Inc ease i s own epu a ion, (b) dec ease
he epu a ion o o he s, (c) inc ease he epu a ion o o he s
o (d) dec ease ecommenda ions epu a ion o a use .
Pe ei a R. H. e al./ J INFORM SYSTEMS ENG, 8(1), 19218
8 / 10
2) Le el: (a) Iden i y managemen , (b) model
o mula ion/calcula ion (Ho man e al., 2009), (c)
o mula ion/da a o (d) a chi ec u al – This a ibu e
iden i ies an elemen in he model whe e he ulne abili y
is.
 Sybil and whi ewashing a e examples o an iden i y
managemen -le el a ack.
 The lack o an ageing mechanism, in he model
o mula ion, can be exploi ed. A he model
o mula ion le el, we also conside he lack o
alida ion (policing) o he a ings by means o a
manual (endo se s) o au oma ic mechanisms (e.g.
machine lea ning);
 In e ms o scena ios o a chi ec u al issues, in a
cen alized sys em, he en i y ha manages he
pla o m can manipula e he epu a ion da a. In he
case o decen alized sys ems, he nodes can
po en ially manipula e he da a sha ed in he
ne wo k, e en i he da a is enc yp ed o signed.
3) Ca dinali y – (a) One en i y, (b) mul iple en i ies; (c)
mul iple iden i ies o (d) Many en i ies o many en i ies.
 In a Sybil a ack an en i y wi h mul iple iden i ies
pa icipa es;
 In he case o Collusion, he a ack is pe o med by
mul iple en i ies.
4) Beha iou – (a) One ime, (b) cons an o (c) a iable
 The scena io o un ai a ings gi en by one, o mo e
buye s o selle s in a cons an o a iable beha iou ;
 Following a a iable pa e n, e.g. Oscilla o y
(Panagopoulos e al., 2017) o T ai o s (Panagopoulos e
al., 2017) a acks.
5) Ac ion – (a) Un ai a ing, (b) disc imina o y a ing, (c)
c ea ing a new iden i y o (d) da a manipula ion
These i e dimensions p oposed o classi y he possible
a acks on he epu a ion sys ems a e ocused on e-comme ce
communi ies. Howe e , his ma ix could po en ially be applied
o o he ne wo k se ices, such as c owdsou cing o P2P.
The p oposed app oach also has he ad an age o
ex ensibili y. Tha is o say, new a ibu es can be added o he
amewo k, as well as new alues o hese a ibu es.
Addi ionally, ou app oach can handle mul iple a ian s o he
same ype o a ack, a oiding long and complex hie a chical
axonomies. This is a subs an ial ad an age ega ding he
axonomies ound in he li e a u e. Fo ins ance, one can pe o m
bad-mou hing aud applying collusion by means o Sybil, o
no . Thus, we conside bad moun ing as a ype o aud o he
a ack, lack o e ec i e iden i y managemen a he le el in he
case o a Sybil a ack and ca dinali y as mul iple iden i ies, in he
case o a collusion-based a ack.
E alua ion o he p oposed ma ix
In his sec ion, we will es ou p oposal on he ypes o
a acks on epu a ion sys ems ound in he li e a u e. In Table 3,
o each a ack ( i s column) we p esen all i e a ibu es. When
all a ibu es a e possible, we use “any”. In such cases, i means
ha he same a ack (o a ian ) has a ian s, as many as he
numbe o possible combina ions o a ibu es.
Table 3. A acks mul idimensional analyse
A ack Desc ip ion F aud Le el Ca dinali y Beha iou Ac ion
Ballo s u ing (C. Della ocas., 2000; C. Della ocas,
2000; C. N. Della ocas, 2003)
(a) (b) Any Any (a), (b) o (d)
Bad-mou hing (b) (b) Any Any (a), (b) o (d)
On-o (Alshamma i e al., 2021) Any (b) Any (c) (a) o (b)
Oscilla o y beha iou (Panagopoulos e al., 2017) Any (b) Any (c) (a) o (b)
Quali y a ia ions o e
ime (Jøsang e al., 2007) Any (b) Any (c) (a) o (b)
Sybil (Douceu , 2002) Any (a) (c) Any (c) and ((a) o (b))
Whi ewashing (F aga e al., 2012) (a) (a), (b)
o (c) (a) (a) Any
Re-en y (F aga e al., 2012) (a) (a) (a) (a) (c)
Chu n (Swamyna han e al., 2010) (a) (a) (a) (a) (c)
Collusion
(Kou ouli & Tsalga idou, 2012,
2016)
Any (b) (b) o (c) (b) o (c) (a) and/o (b)
Collusi e decei (b) and
(c) (b) (d) (b) o (c) (a)
Collusi e badmou hing (b) (b) (b) o (c) (b) o (c) (a)
Collusi e educing
ecommenda ion
epu a ion
(d) (b) (b) o (c) (b) o (c) (a)
Da a manipula ion by a
cen al au ho i y
(Schaub e al., 2016; Zul iqa e al.,
2021) Any (c) (a) Any (d)
Repu a ion T ap (Feng e al., 2012) (b) and
(c) (b) (d) (b) o (c) (a) and (b)
Bias owa d posi i e a ing (Jøsang e al., 2007) (c) (b) (a) (a) (a)
Pe ei a R. H. e al./ J INFORM SYSTEMS ENG, 8(1), 19218
9 / 10
In Table 3, we can obse e ha , only by he a ack name,
one canno know all he de ails o he malicious ac ion. Fo
ins ance, a malicious use may apply a Sybil a ack o inc ease
his own epu a ion o damage someone’s epu a ion. Thus, ou
p oposal enables secu i y analys s o classi y new ypes o
a ack, as well as iden i y wo ypes o a ack as e ec i ely
being he same, o ins ance: On-o and con lic ing-beha iou
a acks. E en i wo ypes o a ack ha e dis inc p oposals, i
hei a ibu es a e he same, hen, po en ially, he same
app oach o dealing wi h hem could be applied in bo h cases.
CONCLUSION
In he p esen wo k, we conduc ed a sys ema ic li e a u e
e iew in o de o sys ema ize he se e al ypes o a acks and
aud o epu a ion sys ems in he con ex o use epu a ion in
e-comme ce. In ou discussion, we p esen some obse a ions
ha lead us o conclude ha he ype o a ack/ aud does no
in o m us abou all he necessa y de ails o unde s anding he
malicious ac ion. In ac , each ulne abili y may be combined
wi h o he s. Thus, he same ype o a ack could ha e dis inc
names, o many a ian s, making i e y di icul o inbox i in
a hie a chical o g oup-based classi ica ion, as he ones ound
in he li e a u e.
In o de o o e come his gap, we p opose a no el
amewo k o classi ica ion. We a e con inced ha ou
app oach has ad an ages o e o he p oposals based on
axonomies, ca ego ies o hie a chical classi ica ions, which a e
complex and edundan when ying o co e all
ypes/ a ian s. We expec o con ibu e o he knowledge in
his esea ch ield by means o ou p oposal o an inno a i e
amewo k. We belie e ha ou amewo k can be use ul o
epu a ion sys em de elope s in o de o p e iew and analyse
new o ms o a ack, as well as o help o de elop e ec i e
de ence mechanisms.
Ou p oposal is s ill in i s i s e sion. Due o i s
ex ensibili y, new a ibu es and alues can be added o he
amewo k. The epu a ion sys ems s ill ha e open issues,
mo i a ing us o con inue ou wo k. Thus, we expec o p esen
new e sions o his classi ica ion amewo k in he nea
u u e.
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