Secure for Handheld Devices Against Malicious Software

8/10/2019 Secure for Handheld Devices Against Malicious Software

1/27

SECURE FOR HANDHELD DEVICES

AGAINST MALICIOUS SOFTWARE

IN MOBILE NETWORKS

Guided by, Presented by,Mr.KANNUDURAI K.SURYA,

951513405019


2/27

AIM &OBJECTIVE

Deploying an efficient defense system to protect against

infection and to help the infected nodes to recover is

important to prevent serious spreading and outbreaks.

To optimally distribute the content-based signatures of

malware, which helps to detect the corresponding

malware.

Disable further propagation to minimize the number of

infected nodes.


3/27

PROJECT SIGNIFICANCE

Most probably the target for malware attacks such as

viruses,worms etc., in mobile networks.

The other reason is the emergence of mobile Internet,

which indirectly induces the malware.

In order to prevent this kind of attacks in mobile

networks,we provided this particularly in mobile

networks.


4/27

PROJECT IMPACT

Defense system distribute the optimal signature using special

nodes.

To deploy an efficient defense system to help infected nodes

to recover and prevent healthy nodes from further infection.

Avoiding whole network unnecessary redundancy using

distribute signatures.

The efficiency of our defense scheme in reducing the amount

of infected nodes in the system.

Security and authentication mechanisms should be considered.


5/27

LITERATURE SURVEY

TITLE AUTHOR ABSTRACT DISADVANTAGES

Understanding the

spreading patterns

of mobile phone

viruses

P. Wang, M.

Gonzalez, C.

Hidalgo, and

A. Barabasi

We find that while

Bluetooth viruses can

reach all susceptible

handsets with time, they

spread slowly due to

human mobility, offering

ample opportunities to

deploy antiviral software

The Bluetooth virus to infect

all susceptible handsets

Maximum Damage

Malware Attack in

Mobile Wireless

Networks

M. Khouzani, S.

Sarkar, and E.

Altman

Malware attacks

constitute a serious

security risk that

threatens to slow down the

large-scale proliferation of

wireless applications.

The battery resources are

used according to a

decreasing function of time


6/27

LITERATURE SURVEY (CONT.)

TITLE AUTHOR ABSTRACT DISADVANTAGES

SWIM: A Simple

Model to

Generate Small

Mobile Worlds

A. Mei and J.

Stefa.

This paper presents small

world in motion (SWIM),

a new mobility model for

ad-hoc networking

Small amount of data can be

transferred and limited

contact duration time

CPMC: An

Efficient

Proximity

Malware Coping

Scheme in

Smartphone-

based MobileNetworks

F. Li, Y. Yang, and

J. Wu

CPMC utilizes the social

community structure,

which reflects a stable and

controllable granularity of

security, in smart phone-

based mobile networks

Each nodes own view is too

limited, and the signature

floodingis too costly.

Distributed

Caching over

Heterogeneous

Mobile Networks

S. Ioannidis, L.

Massoulie, and A.

Chaintreau

Sharing content over a

mobile network through

opportunistic contacts has

recently received

considerable attention

Users can retrieve content

only when they access

infrastructure or when

encounter other user storing

it.


7/27

SYSTEMARCHITECTURE

Node

creation

Create Helper Node

Distribute

dsignatures

Using DTN

model

Analysis

Malware

Encounter

Malware

Performance

evaluation


8/27

IMPLEMENTATION AND CODE

MODULES:

Node Creation

Helper node Creation

Distribute Signatures

Malware Detection and Encounter

Performance Trace


9/27

MODULES DESCRIPTION:

Node Creation:

Create a mobile networks including a number of nodes. First

defined number of nodes and also defined source node,destination node, intermediate nodes.

The network contains heterogeneous devices as nodes. Mobile

nodes are more efficient to disseminate content and information

in the network.


10/27

Helper node Creation:

Helper nodes are referred to as special nodes. Helper node is

intermediate node for every nodes in the network.

File can be transmit from source node to destination node through

the help of helpers node.

Distr ibute Signatures:

This module is used to analyzing the malware nodes through

passing the signatures.

Helper node distribute the signatures for every intermediate nodes

based on the file contents key will be generated.


11/27

Malware Detection and Encounter Malwares:

Detect the malware with the help of a content based signatures.

Exponential parameter obtained from the contact records

between helpers and general nodes.

Every intermediate node receive the signatures from helper

node and which intermediate nodes receiving the signatures

twice.

This time to detecting the malware spreading nodes and

recovering the infected nodes.


12/27

Performance Trace:

Simulate the malware spreading, and compare the simulation resultsof infected ratio with that obtained by the model.

The number of infected nodes increases with the growth of spreading

rate can observe that the number of infected nodes decreases with the

increase of recovering rate.

For proximity malware propagation, we use both realistic mobility

trace and synthetic trace for simulations.

This modules determining the malware spreading time and malware

recovering time will be calculated using the signatures receive traces.


13/27


14/27


15/27


16/27


17/27


18/27


19/27


20/27


21/27


22/27


23/27


24/27


25/27

CONCLUSION

In this paper, we investigate the problem of optimal signaturedistribution to defend mobile networks against the propagation

of both proximity and MMS-based malware.

We introduce a distributed algorithm that closely approaches

the optimal system performance of a centralized solution. To

optimally distribute the content-based signatures of malware,

which helps to detect the corresponding malware and disable

further propagation, to minimize the number of infected nodes.

Our goal is to minimize the malware infected nodes in the

system by appropriately allocating the limited storage with the

consideration of different types of malware.

Through both theoretical analysis and simulations, we

demonstrate the efficiency of our defense scheme in reducing

the amount of infected nodes in the system.


26/27

FUTURE ENHANCEMENT

Our scheme targets both the MMS and proximity malware at thesame time, and considers the problem of signature distribution.

Second, all these works assume that malware and devices are

homogeneous, we take the heterogeneity of devices into account in

deploying the system and consider the system resource limitations.

From the aspect of malware, since some sophisticated malware that

can bypass the signature detection would emerge with the

development of the defense system, new defense mechanisms will be

required.

At the same time, our work considers the case of OS-targetingmalware. Although most of the existing malware is OS targeted,

cross-OS malware will emerge and propagate in the near future. How

to efficiently deploy thecurrent defense system with the

consideration of cross-OS malware is another important problem


27/27

REFERENCES

P. Wang, M. Gonzalez, C. Hidalgo, and A. Barabasi, Under-standing the Spreading Patterns of Mobile Phone

Viruses,Science,vol. 324, no. 5930, pp. 1071-1076.

M. Hypponen, Mobile Malwar,Proc. 16th USENIX

SecuritySymp. G. Lawton, Onthe Trail of the Conficker Worm ,Computer,

vol. 42, no. 6, pp. 19-22.

Z. Zhu, G. Cao, S. Zhu, S. Ranjan, and A. Nucci, A Social

Network Based Patching Scheme for Worm Containment inCellular Networks,Proc. IEEE INFOCOM.

Secure for Handheld Devices Against Malicious Software

Documents

Transcript of Secure for Handheld Devices Against Malicious Software