工业物联网的文件中心多密钥聚合关键字搜索加密方案
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"以文件为中心的多密钥聚合关键字可搜索加密在工业物联网中的应用"
在当前的工业物联网（Industrial Internet of Things, IIoT）中，云存储已经成为降低数据管理成本和促进便捷协作的有效手段。然而，随着数据共享的增加，确保数据安全、实现云端数据搜索以及文件访问控制变得至关重要。这篇研究论文主要关注的是在IIoT环境中，如何在保护数据隐私的同时，提供安全的云数据搜索和文件访问服务。
作者们首先讨论了一种针对崔氏（Cui's）多密钥聚合可搜索加密方案的新型内部攻击。这种攻击中，未经授权的内部用户可能通过猜测其他用户的私钥来获取敏感信息。这突显了现有加密方案在面对内部威胁时的脆弱性。
为了应对这一挑战，论文提出了一个创新的文件为中心的多密钥聚合关键字可搜索加密系统（Fc-MKA-KSE）。该系统是专为IIoT数据设计的，适用于文件中心化的框架。Fc-MKA-KSE的核心目标是在保证用户数据隐私的同时，允许授权用户进行安全的关键字搜索和文件访问。
论文详细介绍了两个正式的安全模型：选择性文件选择关键字攻击下的不可区分性模型和“不敏感”选择性文件关键字攻击下的不可区分性模型。这些模型旨在确保即使在有选择地暴露部分信息的情况下，加密系统的安全性也能得到维护。此外，还提出了一种新的加密算法，该算法能够支持多用户之间的数据共享，并且允许每个用户使用自己的私钥对数据进行加密，同时还能进行聚合关键字搜索，而无需解密整个文件。
在Fc-MKA-KSE系统中，用户可以使用关键字查询加密数据，系统将返回与查询相关的加密文件列表，而无需揭示文件的具体内容。这一特性极大地提高了数据的安全性和隐私性。此外，系统还实现了细粒度的访问控制，确保只有授权的用户才能访问特定的文件。
论文通过一系列的实验和安全性分析验证了Fc-MKA-KSE的有效性和安全性。实验结果表明，尽管增加了安全特性，但系统仍能保持相对较高的效率，适合在资源受限的IIoT设备上运行。
这篇论文为IIoT环境下的数据安全提供了新的解决方案，通过多密钥聚合关键字可搜索加密技术，解决了云存储中的数据隐私和安全问题，对于推动工业物联网领域的安全发展具有重要意义。
3650 IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, VOL. 14, NO. 8, AUGUST 2018
β
2
γ
1
α
t
fH
2
=(β
2
γ
1
f)(α
t
)H
2
, one of d
i
and d
j
must be α
t
.
However, the α
t
is not in D. Hence, there are no coefficients
{x
i,j
}, {y
k
},z
1
such that the equation Σx
i,j
d
i
d
j
=Σy
k
d
k
p
1
+
z
1
holds.
Therefore, the (2n, n, 1)-MSE-DDH Problem is intractable.
Definition 2 ((2n, n, 2)-MSE-DDH Problem): Let n be an
integer and (p, G, G
T
,e) be a bilinear map group sys-
tem. Let g be the generators of G and h
1
= g
γ
1
,h
2
= g
γ
2
.
α, β
1
,β
2
,H
1
,H
2
∈ Z
∗
p
. Set f is random coprime with α, whose
order is deg(f)=1, Z ∈ G, and given the following sequences
of group elements:
g, g
β
2
,g
x
g
β
2
α
1
, ..., g
β
2
α
n −#
g
β
2
α
n + 2−#
, ..., g
β
2
α
n
g
γ
1
α
1
, ..., g
γ
1
α
n
g
γ
1
f
,g
γ
1
β
2
f
g
(β
2
H
2
+γ
2
α
1
)f
, ..., g
(β
2
H
2
+γ
2
α
# −1
)f
g
(β
2
H
2
+γ
2
α
#+1
)f
, ..., g
(β
2
H
2
+γ
2
α
n
)f
g
(β
2
H
1
+γ
2
α
1
)f
, ..., g
(β
2
H
1
+γ
2
α
n
)f
g
γ
2
α
1
, ..., g
γ
2
α
2n
where # means a random number chosen from {1,...,n}.The
problem is to distinguish whether Z equals to g
β
2
(α
n + 1−#
H
2
+x)
or some random element in G.
Intractability of (2n, 1, 2)-MSE-DDH Problem: The intract-
ability of (2n, n, 2)-MSE-DDH problem can be proved similarly
as the intractability of (2n, n, 1)-MSE-DDH problem. Therefore,
the (2n, n, 2)-MSE-DDH Problem is intractable.
III. N
EW INSIDER ATTACK TO CUI’S KEY-AGGREGATE
SEARCHABLE ENCRYPTION
A. Cui’s Key-Aggregate Searchable Encryption
We simply describe Cui’s scheme [14].
1) Setup(κ, n): The cloud server does the work as follows.
a) Generate a bilinear map group system B =
(p, G, G
1
,e(·, ·)), where p is the order of G and
2
κ
≤ p ≤ 2
κ+1
.
b) Set n as the maximum possible number of documents,
which belong to the data owner.
c) Randomly pick g ∈Gand α ∈ Z
∗
p
, and compute g
i
=
g
(α)
i
∈Gfor i =(1, 2,...,n,n+ 2,...,2n).
d) Select a one-way hash function H : {0, 1}
∗
→G.
e) Keep (α, g
1
,...,g
n
,g
n+2
,...,g
2n
) secretly, and
publicize the public parameters Params =
{p, G, G
1
,e(·, ·)),g,H(·)}.
2) KeyGen: The data owner chooses a random γ ∈ Z
∗
p
and
sets the data owner’s master-key as msk = γ and public
key as pk = v = g
γ
.
3) Encrypt(i, k, w):Forthei-th document (i ∈
{1,...,n}), the data owner picks a random t ∈
Z
p
and computes the ciphertext (c
1
,c
2
,c
w
)=(g
t
, (v ·
g
i
)
t
,
e(g,H(w ))
t
e(g
1
,g
n
)
t
).
4) Extract(msk, S): For any subset S ⊆{1,...,n},the
data owner computes k
agg
=
j∈S
g
γ
n+1−j
and sends
(k
agg
,S) to the user through a secure channel.
5) Tra pd oo r(k
agg
,w): The user generates the trapdoor
Tr = k
agg
· H(w) and sends (Tr,S) to the cloud server.
6) Adjust(i, S, T r): the cloud server adjusts the right trap-
door for all i ∈ S as Tr
i
= Tr·
j∈S,j=i
g
n+1−j + i
.
7) Tes t(Tr
i
,i):Forthei-th document, the cloud server
computes pub =
j∈S
g
n+1−j
and outputs true if c
w
=
e(Tr
i
,c
1
)
e(pub,c
2
)
holds, and false otherwise.
B. New Attack to Cui’s Scheme
Aggelos Kiayias’s attacks win the games as keyword dictio-
nary guessing. In Aggelos Kiayias’s attack, the size of guessing
keyword dictionary is same as the size of whole keyword space.
We show a new attack to Cui’s scheme, which can be done by
inside unauthorized users. In our attack, the size of guessing
keyword dictionary equals to the number of keywords in the
attacked file. Therefore, our attack is much more efficient. We
describe our attack as follows.
Assume that A is a user to be attacked whose authorized
private key is k
agg
and access set is S
A
, and B is an inside
attacker whose access set is S
B
. We assume that S
A
= S
B
,
S
A
∩ S
B
= ∅, and S
A
S
B
. To simplify our description, let
F
l
∈ (S
A
∩ S
B
) and the keywords in F
l
be {w
1
,w
2
,w
3
}.
A submits a trapdoor Tr = k
agg
· H(w
∇
) for keyword
search and the cloud server returns this keyword search result
after testing. The document F
l
is one of the results.
B eavesdrops the trapdoor Tr submitted from A, and he
computes an aggregation key set K = {k
agg
1
,k
agg
2
,k
agg
3
} =
Tr
H (w
1
)
,
Tr
H (w
2
)
,
Tr
H (w
3
)
}. Then, k
agg
∈{k
agg
1
,k
agg
2
,k
agg
3
}.
B can correctly guess k
agg
as follows: First, B guesses
w
∇
= w
1
and k
agg
= k
agg
1
, and computes Tr
= k
agg
1
· H(w
2
)
or Tr
= k
agg
1
· H(w
3
). Then, B sends Tr
to the cloud server
to do search query. Unfortunately, the cloud server cannot dis-
tinguish that the search query is submitted by A or B. Therefore,
it responds the result honestly. If F
l
is in the returned result, the
trapdoor Tr
is valid and k
agg
= k
agg
1
; otherwise, the trapdoor
Tr
is invalid. B continues to try k
agg
2
and k
agg
3
and does the
similar test until he finds the correct k
agg
. B performs the test
at most three runs to obtain A’s private key k
agg
.
In the above attack, the attacker B can only be successful if he
shares the access of F
l
. Upon obtaining A’s private key k
agg
,
B can further do the same attack to those who share file access
with A.
IV. S
YSTEM DEFINITION AND SECURITY MODEL OF
FC-MKA-KSE IN DATA SHARING
A. Formal System Definition of Fc-MKA-KSE in Data
Sharing
Definition 3: As shown in Fig. 2, the Fc-MKA-KSE system
in data sharing consists of the following eight algorithms.
1) Setup(κ): The algorithm generates the system parame-
ter GP .
Authorized licensed use limited to: University of Electronic Science and Tech of China. Downloaded on March 21,2020 at 15:13:22 UTC from IEEE Xplore. Restrictions apply.
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