A System for Denial-of-Service Attack Detection Based on
Multivariate Correlation Analysis
ABSTRACT:
Interconnected systems, such as Web servers, database servers, cloud
computing servers etc, are now under threads from network attackers. As one of
most common and aggressive means, Denial-of-Service (DoS) attacks cause
serious impact on these computing systems. In this paper, we present a DoS attack
detection system that uses Multivariate Correlation Analysis (MCA) for accurate
network traffic characterization by extracting the geometrical correlations between
network traffic features. Our MCA-based DoS attack detection system employs the
principle of anomaly-based detection in attack recognition. This makes our
solution capable of detecting known and unknown DoS attacks effectively by
learning the patterns of legitimate network traffic only. Furthermore, a trianglearea-based technique is proposed to enhance and to speed up the process of MCA.
The effectiveness of our proposed detection system is evaluated using KDD Cup
99 dataset, and the influences of both non-normalized data and normalized data on
the performance of the proposed detection system are examined. The results show
that our system outperforms two other previously developed state-of-the-art
approaches in terms of detection accuracy.
Building Confidential and Efficient Query
Services in the Cloud with RASP Data
Perturbation
ABSTRACT
With the wide deployment of public cloud computing infrastructures, using clouds to host
data query services has become an appealing solution for the advantages on scalability and costsaving. However, some data might be sensitive that the data owner does not want to move to the
cloud unless the data confidentiality and query privacy are guaranteed. On the other hand, a
secured query service should still provide efficient query processing and significantly reduce the
in-house workload to fully realize the benefits of cloud computing. We propose the RASP data
perturbation method to provide secure and efficient range query and kNN query services for
protected data in the cloud. The RASP data perturbation method combines order preserving
encryption, dimensionality expansion, random noise injection, and random projection, to provide
strong resilience to attacks on the perturbed data and queries. It also preserves multidimensional
ranges, which allows existing indexing techniques to be applied to speedup range query
processing. The kNN-R algorithm is designed to work with the RASP range query algorithm to
process the kNN queries. We have carefully analyzed the attacks on data and queries under a
precisely defined threat model and realistic security assumptions. Extensive experiments have
been conducted to show the advantages of this approach on efficiency and security.
Captcha as Graphical Passwords—A New Security
Primitive Based on Hard AI Problems
ABSTRACT
Many security primitives are based on hard mathematical problems. Using
hard AI problems for security is emerging as an exciting new paradigm, but has
been underexplored. In this paper, we present a new security primitive based on
hard AI problems, namely, a novel family of graphical password systems built on
top of Captcha technology, which we call Captcha as graphical passwords (CaRP).
CaRP is both a Captcha and a graphical password scheme. CaRP addresses a
number of security problems altogether, such as online guessing attacks, relay
attacks, and, if combined with dual-view technologies, shoulder-surfing attacks.
Notably, a CaRP password can be found only probabilistically by automatic online
guessing attacks even if the password is in the search set. CaRP also offers a novel
approach to address the well-known image hotspot problem in popular graphical
password systems, such as PassPoints, that often leads to weak password choices.
CaRP is not a panacea, but it offers reasonable security and usability and appears
to fit well with some practical applications for improving online security.
Dealing With Concept Drifts in Process Mining
ABSTRACT
Although most business processes change over time, contemporary process mining techniques tend to
analyze these processes as if they are in steady-state. Processes may change suddenly or gradually. The
drift may be periodic (e.g. due to seasonal influences) or one-of-a- kind (e.g., the effects of new
legislation). For process management it is
crucial to discover and understand such concept drifts in processes.
EXISTING SYSTEM:
The process is stable and enough example traces have been recorded in the event log, it
is possible to discover a high quality process model that can be used for performance analysis,
compliance checking, and prediction. Unfortunately, most processes are not in steady-state. In today's
dynamic marketplace, it is increasingly necessary for enterprises to streamline their processes so as to
reduce costs and to improve performance.
PROPOSED SYSTEM:
The proposed four features characterizing the control flow dependencies between activities. These
features are shown to be effective in detecting process changes. An event log can be transformed into a
data set D, which can be considered as a time series by these features. Change detection is done by
considering a series of successive populations1 of feature values and investigating if there is a significant
difference between two successive populations. The premise is that differences are expected to be
perceived at change points provided appropriate characteristics of the change are captured as features.
Decentralized Access Control with Anonymous
Authentication of Data Stored in Clouds
ABSTRACT
We propose a new decentralized access control scheme for secure data storage in clouds,
that supports anonymous authentication. In the proposed scheme, the cloud verifies the
authenticity of the ser without knowing the user’s identity before storing data. Our scheme also
has the added feature of access control in which only valid users are able to decrypt the stored
information. The scheme prevents replay attacks and supports creation, modification, and
reading data stored in the cloud. We also address user revocation. Moreover, our authentication
and access control scheme is decentralized and robust, unlike other access control schemes
designed for clouds which are centralized. The communication, computation, and storage
overheads are comparable to centralized approaches.
Key-Aggregate Cryptosystem
for Scalable Data Sharing in Cloud Storage
ABSTRACT
Data sharing is an important functionality in cloud storage. In this article, we show how
to securely, efficiently, and flexibly share data with others in cloud storage. We describe new
public-key cryptosystems which produce constant-size ciphertexts such that efficient delegation
of decryption rights for any set of ciphertexts are possible. The novelty is that one can aggregate
any set of secret keys and make them as compact as a single key, but encompassing the power of
all the keys being aggregated. In other words, the secret key holder can release a constant-size
aggregate key for flexible choices of ciphertext set in cloud storage, but the other encrypted files
outside the set remain confidential. This compact aggregate key can be conveniently sent to
others or be stored in a smart card with very limited secure storage. We provide formal security
analysis of our schemes in the standard model. We also describe other application of our
schemes. In particular, our schemes give the first public-key patient-controlled encryption for
flexible hierarchy, which was yet to be known.
Oruta: Privacy-Preserving Public Auditing
for Shared Data in the Cloud
Abstract:
With cloud storage services, it is commonplace for data to
be not only stored in the cloud, but also shared across multiple users.
However, public auditing for such shared data— while preserving
identity privacy — remains to be an open challenge. In this paper, we
propose the first privacy-preserving mechanism that allows public
auditing on shared data stored in the cloud. In particular, we exploit
ring signatures to compute the verification information needed to audit
the integrity of shared data. With our mechanism, the identity of the
signer on each block in shared data is kept private from a third party
auditor (TPA), who is still able to verify the integrity of shared data
without retrieving the entire file. Our experimental results demonstrate
the effectiveness and efficiency of our proposed mechanism when
auditing shared data.
Secure Outsourced Attribute-Based Signatures
ABSTRACT
Attribute-based signature (ABS) is a useful variant of digital signature, which enables users to
sign messages over attributes without revealing any information other than the fact that they
have attested to the messages. However, heavy computational cost is required during signing in
existing work of ABS, which grows linearly with the size of the predicate formula. As a result,
this presents a significant challenge for resource-limited users (such as mobile devices) to
perform such heavy computation independently. Aiming at tackling the challenge above, we
propose and formalize a new paradigm called OABS, in which the computational overhead at
user side is greatly reduced through outsourcing such intensive computation to an un trusted
signing-cloud service provider (S-CSP). Furthermore, we apply this novel paradigm to existing
ABS to reduce complexity and present two schemes, i) in the first OABS scheme, the number of
exponentiations involving in signing is reduced from O(d) to O(1) (nearly three), where d is the
upper bound of threshold value defined in the predicate; ii) our second scheme is built on
Herranz et al's construction with constant-size signatures. The number of exponentiations in
signing is reduced from O(d2) to O(d) and the communication overhead is O(1). Security
analysis demonstrates that both OABS schemes are secure in terms of the unforgeability and
attribute- signer privacy definitions specified in the proposed security model. Finally, to allow
for high efficiency and exibility, we discuss extensions of OABS and show how to achieve
accountability and outsourced verification as well.
Securing Brokerless Publish/Subscribe Systems
Using Identity Based Encryption
ABSTRACT
The provisioning of basic security mechanisms such as authentication and confidentiality is
highly challenging in a content based publish/subscribe system. Authentication of publishers
and subscribers is difficult to achieve due to the loose coupling of publishers and subscribers.
Likewise, confidentiality of events and subscriptions conflicts with content-based routing. This
paper presents a novel approach to provide confidentiality and authentication in a broker-less
content-based publish/subscribe system. The authentication of publishers and subscribers as
well as confidentiality of events is ensured, by adapting the pairing-based cryptography
mechanisms, to the needs of a publish/subscribe system. Furthermore, an algorithm to cluster
subscribers according to their subscriptions preserves a weak notion of subscription
confidentiality. In addition to our previous work this paper contributes 1) use of searchable
encryption to enable efficient routing of encrypted events, 2) multicredential routing a new
event dissemination strategy to strengthen the weak subscription confidentiality, and 3)
thorough analysis of different attacks on subscription confidentiality. The overall approach
provides fine-grained key management and the cost for encryption, decryption, and routing is
in the order of subscribed attributes. Moreover, the evaluations show that providing security is
affordable w.r.t. 1) throughput of the proposed cryptographic primitives, and 2) delays incurred
during the construction of the publish/subscribe overlay and the event dissemination.
Supporting Privacy Protection in Personalized
Web Search
ABSTRACT
Personalized web search (PWS) has demonstrated its effectiveness in improving the
quality of various search services on the Internet. However, evidences show that users’
reluctance to disclose their private information during search has become a major barrier for the
wide proliferation of PWS. We study privacy protection in PWS applications that model user
preferences as hierarchical user profiles. We propose a PWS framework called UPS that can
adaptively generalize profiles by queries while respecting userspecified privacy requirements.
Our runtime generalization aims at striking a balance between two predictive metrics that
evaluate the utility of personalization and the privacy risk of exposing the generalized profile.
We present two greedy algorithms, namely GreedyDP and GreedyIL, for runtime generalization.
We also provide an online prediction mechanism for deciding whether personalizing a query is
beneficial. Extensive experiments demonstrate the effectiveness of our framework. The
experimental results also reveal that GreedyIL significantly outperforms GreedyDP in terms of
efficiency.
CLOUD COMPUTING
1
2
A Privacy Leakage Upper Bound Constraint-Based Approach for CostEffective Privacy reserving of Intermediate Data Sets in Cloud
AMES-Cloud: A Framework of Adaptive Mobile Video Streaming and
Efficient Social Video
Sharing in the Clouds
3
CAM: Cloud-Assisted Privacy Preserving Mobile Health Monitoring
4
On Data Staging Algorithms for Shared Data Accesses in Clouds
5
Privacy-Preserving Public Auditing for Secure Cloud Storage
6
QoS Ranking Prediction for Cloud Services
7
Winds of Change: From Vendor Lock-In to the Meta Cloud
8
A Load Balancing Model Based on Cloud Partitioning for the Public Cloud
2013
2013
2013
2013
2013
2013
2013
2013
9
10
Collaboration in Multi cloud Computing Environments: Framework
and Security Issues
Mining Contracts for Business Events and Temporal Constraints in Service
Engagements
2013
2013
11
Outsourcing Privacy-Preserving Social Networks to a Cloud
2013
12
Scalable and Secure Sharing of Personal Health Records in Cloud Computing
using Attribute-based Encryption
2013
13
Cloud data protection for masses (DPAAS)
2012
14
Costing of Cloud Computing Services: A Total Cost of Ownership Approach
2012
15
Efficient similarity search over encrypted data
2012
16
17
Enabling Secure and Efficient Ranked Keyword Search over Outsourced
Cloud Data
Ensuring Distributed Accountability for Data Sharing in the Cloud
2012
2012
Anchor: A Versatile and Efficient Framework for Resource Management in
18
2012
the Clouds
DATA MINING
1
Spatial Approximate String Search
2
A Survey of XML Tree Patterns
3
A Fast Clustering-Based Feature Subset Selection Algorithm for High
Dimensional Data
4
Optimal Route Queries with Arbitrary Order Constraints
5
Change Detection in Streaming Multivariate Data Using Likelihood Detectors
6
A Novel Profit Maximizing Metric for Measuring Classification Performance
of Customer Churn Prediction Models
7
Crowd sourcing Predictors of Behavioral Outcomes
8
Failure-Aware Cascaded Suppression in Wireless Sensor Networks
9
Mining User Queries with Markov Chains: Application to Online Image
Retrieval
10
m-Privacy for Collaborative Data Publishing
11
Privacy Preserving Delegated Access Control in Public Clouds
2013
2013
2013
2013
2013
2013
2013
2013
2013
2013
2013
12
T-Drive: Enhancing Driving Directions with Taxi Drivers’ Intelligence
2013
13
Relationships between Diversity of Classification Ensembles and Single-Class
Performance Measures
2013
14
Ranking on Data Manifold with Sink Points
2013
15
Sampling Online Social Networks
2013
16
17
18
19
20
21
22
Real-Time Implementation of the Vertex Component Analysis Algorithm on
GPUs
Estimating Information from Image Colors: An Application to Digital Cameras
and Natural Scenes
Facilitating Document Annotation Using Content And Querying Value
FOCUS Learning to Crawl Web Forums
Incentive Compatible Privacy-Preserving Data Analysis
PMSE A Personalized Mobile Search Engine
Secure Mining of Association Rules in Horizontally Distributed Databases
2013
2013
2013
2013
2013
2013
2013
23
A Link-Based Cluster Ensemble Approach for Categorical Data Clustering
2012
24
Answering General Time-Sensitive Queries
2012
25
Creating Evolving User Behavior Profiles Automatically
2012
26
Effective Pattern Discovery for Text Mining
2012
27
Incremental Information Extraction Using Relational Databases
2012
Mining Graph Topological Patterns: Finding Co-variations Among Vertex
28
2012
Descriptors
NET WORKING & NETWORK
SECURITY
1
2
3
A Rank Correlation Based Detection against Distributed Reflection DoS
Attacks
An Empirical Interference Modeling for Link Reliability Assessment in
Wireless Networks
Diffusion Dynamics of Network Technologies With Bounded Rational Users:
2013
2013
2013
4
5
6
7
8
Aspiration-Based Learning
Exploring the Design Space of Multichannel Peer-to-Peer Live Video
Streaming Systems
Localization of Wireless Sensor Networks in the Wild: Pursuit of Ranging
Quality
Modeling the Pair wise Key Pre distribution Scheme in the Presence of
Unreliable Links
Multiparty Access Control for Online Social Networks: Model and
Mechanisms
Optimizing Cloud Resources for Delivering IPTV Services Through
Virtualization
9
PACK: Prediction-Based Cloud Bandwidth and Cost Reduction System
10
Participatory Privacy: Enabling Privacy in Participatory Sensing
11
Sink Trail: A Proactive Data Reporting Protocol for Wireless Sensor Networks
2013
2013
2013
2013
2013
2013
2013
2013
Importance of Coherence Protocols with Network Applications on Multi core
Processors
Detection and Localization of Multiple Spoofing Attackers in Wireless
Networks
2013
14
A Highly Scalable Key Pre-Distribution Scheme for Wireless Sensor Networks
2013
15
Back-Pressure-Based Packet-by-Packet Adaptive Routing in Communication
Networks
2013
16
Delay-Based Network Utility Maximization
2013
17
Dynamic Control of Coding for Progressive Packet Arrivals in DTNs
2013
18
Fast Transmission to Remote Cooperative Groups A New Key Management
Paradigm
2013
19
Minimum Cost Blocking Problem in Multi-path Wireless Routing Protocols
2013
20
On the Node Clone Detection in Wireless Sensor Networks
2013
21
Opportunistic MANETs Mobility Can Make Up for Low Transmission Power
2013
12
13
23
Using Fuzzy Logic Control to Provide Intelligent Traffic Management Service
for High-Speed Networks
DRINA A Lightweight And Reliable Routing
24
Cut Detection In Wireless Sensor Network
22
2013
2013
2012
2012
SPOC: A Secure and Privacy-preserving Opportunistic Computing Framework
25
26
for Mobile-Healthcare Emergency
AMPLE: An Adaptive Traffic Engineering System Based on Virtual Routing
2012
2012
Topologies
FireCol: A Collaborative Protection Network for the Detection of Flooding
27
2012
DDoS Attacks
The Three-Tier Security Scheme in Wireless Sensor Networks with Mobile
28
2012
Sinks
MOBILE COMPUTING
1
A Neighbor Coverage-Based Probabilistic Rebroadcast for Reducing Routing
Overhead in Mobile Ad Hoc Networks
2
IP-Geo location Mapping for Moderately Connected Internet Regions
3
Mobile Relay Configuration in Data-Intensive Wireless Sensor Networks
4
On Quality of Monitoring for Multi-channel Wireless Infrastructure Networks
5
Optimal Multicast Capacity and Delay Tradeoffs in MANETs
6
7
8
9
10
11
12
13
Optimizing Cloud Resources for Delivering IPTV Services Through
Virtualization
Relay Selection for Geographical Forwarding in Sleep-Wake Cycling Wireless
Sensor Networks
A Rank Correlation Based Detection against Distributed Reflection DoS
Attacks
Delay-Optimal Broadcast for Multi hop Wireless Networks Using SelfInterference Cancellation
A Scalable Server Architecture for Mobile Presence Services in Social
Network Applications
Community-Aware Opportunistic Routing in Mobile Social Networks
Privacy-Preserving Distributed Profile Matching in Proximity-based Mobile
Social Networks
Search Me If You Can Privacy-preserving Location Query Service
2013
2013
2013
2013
2013
2013
2013
2013
2013
2013
2013
2013
2013
14
Self Adaptive Contention Aware Routing Protocol for Intermittently
Connected Mobile Networks
2013
15
Towards a Statistical Framework for Source Anonymity in Sensor Networks
2013
16
Vampire attacks Draining life from wireless ad-hoc sensor networks
2013
17
18
Local Broadcast Algorithms in Wireless Ad Hoc Networks: Reducing the
Number of Transmissions
Energy-Efficient Cooperative Video Distribution with Statistical QoS
Provisions over Wireless Networks
2012
2012
SECURE COMPUTING
1
2
3
4
5
6
Secure Encounter-based Mobile Social Networks: Requirements, Designs, and
Tradeoffs
Extracting Spread-Spectrum Hidden Data from Digital Media
TRPF A Trajectory Privacy-Preserving Framework for Participatory Sensing
Two tales of privacy in online social networks
Utility-Privacy Tradeoff in Databases An Information-theoretic Approach
Risk-Aware Mitigation for MANET Routing Attacks
2013
2013
2013
2013
2013
2012
Detecting Automation of Twitter Accounts: Are You a Human, Bot, or
7
8
Cyborg?
Detecting Spam Zombies by Monitoring Outgoing Messages
2012
2012
PARALLEL & DISTRIBUTED SYSTEMS
A Privacy Leakage Upper-bound Constraint based Approach for Costeffective Privacy Preserving of Intermediate Datasets in Cloud
A Secure Protocol for Spontaneous Wireless Ad Hoc Networks Creation
2013
2013
6
A System for Denial-of-Service Attack Detection Based on Multivariate
Correlation Analysis
Dynamic Resource Allocation using Virtual Machines for Cloud Computing
Environment
Enabling Data Dynamic and Indirect Mutual Trust for Cloud Computing
Storage Systems
IP-Geo location Mapping for Moderately Connected Internet Regions
7
Load Rebalancing for Distributed File Systems in Clouds
2013
8
Optimal Client-Server Assignment for Internet Distributed Systems
2013
9
Optimal Multi server Configuration for Profit Maximization in Cloud
Computing
Security Analysis of a Privacy-Preserving Decentralized Key-Policy
2013
1
2
3
4
5
10
2013
2013
2013
2013
2013
11
Attribute-Based Encryption Scheme
Social Tube P2P-assisted Video Sharing in Online Social Networks
2013
12
Towards Differential Query Services in Cost-Efficient Clouds
2013