SlideShare a Scribd company logo
SECURITY EVALUATION OF PATTERN CLASSIFIERS 
UNDER ATTACK 
ABSTRACT: 
Pattern classification systems are commonly used in 
adversarial applications, like biometric authentication, network 
intrusion detection, and spam filtering, in which data can be 
purposely manipulated by humans to undermine their operation. 
As this adversarial scenario is not taken into account by classical 
design methods, pattern classification systems may exhibit 
vulnerabilities, whose exploitation may severely affect their 
performance, and consequently limit their practical utility. 
Extending pattern classification theory and design methods to 
adversarial settings is thus a novel and very relevant research 
direction, which has not yet been pursued in a systematic way. 
In this paper, we address one of the main open issues: evaluating 
at design phase the security of pattern classifiers, namely, the 
performance degradation under potential attacks they may incur 
during operation. We propose a framework for empirical
evaluation of classifier security that formalizes and generalizes 
the main ideas proposed in the literature, and give examples of 
its use in three real applications. Reported results show that 
security evaluation can provide a more complete understanding 
of the classifier’s behavior in adversarial environments, and lead 
to better design choices. 
EXISTING SYSTEM: 
PATTERN classification systems based on machine 
learning algorithms are commonly used in security-related 
applications like biometric authentication, network intrusion 
detection, and spam filtering, to discriminate between a 
“legitimate” and a “malicious” pattern class (e.g., legitimate and 
spam emails). Contrary to traditional ones, these applications 
have an intrinsic adversarial nature since the input data can be 
purposely manipulated by an intelligent and adaptive adversary 
to undermine classifier operation. This often gives rise to an 
arms race between the adversary and the classifier designer. 
Well known examples of attacks against pattern classifiers are:
submitting a fake biometric trait to a biometric authentication 
system (spoofing attack); modifying network packets belonging 
to intrusive traffic to evade intrusion detection systems (IDSs) ; 
manipulating the content of spam emails to get them past spam 
filters (e.g., by misspelling common spam words to avoid their 
detection). Adversarial scenarios can also occur in intelligent 
data analysis and information retrieval; e.g., a malicious 
webmaster may manipulate search engine rankings to artificially 
promote her website. 
DISADVANTAGES OF EXISTING SYSTEM: 
· They exhibit vulnerabilities to several potential attacks, 
allowing adversaries to undermine their effectiveness. 
· It focused on application-specific issues related to spam 
filtering and network intrusion detection. 
PROPOSED SYSTEM: 
First, to pursue security in the context of an arms race it is 
not sufficient to react to observed attacks, but it is also necessary
to proactively anticipate the adversary by predicting the most 
relevant, potential attacks through a what-if analysis; this allows 
one to develop suitable countermeasures before the attack 
actually occurs, according to the principle of security by design. 
Second, to provide practical guidelines for simulating realistic 
attack scenarios, we define a general model of the adversary, in 
terms of her goal, knowledge, and capability, which 
encompasses and generalizes models proposed in previous work. 
Third, since the presence of carefully targeted attacks may affect 
the distribution of training and testing data separately, we 
propose a model of the data distribution that can formally 
characterize this behavior, and that allows us to take into 
account a large number of potential attacks; we also propose an 
algorithm for the generation of training and testing sets to be 
used for security evaluation, which can naturally accommodate 
application-specific and heuristic techniques for simulating 
attacks.
ADVANTAGES OF PROPOSED SYSTEM: 
· It predicts the most relevant, potential attacks through a 
what-if analysis. 
· It provides practical guidelines for simulating realistic 
attack scenarios. 
SYSTEM CONFIGURATION:- 
HARDWARE REQUIREMENTS:- 
 Processor - Pentium –IV 
 Speed - 1.1 Ghz 
 RAM - 512 MB(min) 
 Hard Disk - 40 GB 
 Key Board - Standard Windows Keyboard 
 Mouse - Two or Three Button Mouse 
 Monitor - LCD/LED
SOFTWARE REQUIREMENTS: 
• Operating system : Windows XP 
• Coding Language : Java 
• Data Base : MySQL 
• Tool : Net Beans IDE 
REFERENCE: 
Battista Biggio, Giorgio Fumera, and Fabio Roli, “Security Evaluation of Pattern 
Classifiers under Attack” IEEE TRANSACTIONS ON KNOWLEDGE AND 
DATA ENGINEERING, VOL. 26, NO. 4, APRIL 2014.
SOFTWARE REQUIREMENTS: 
• Operating system : Windows XP 
• Coding Language : Java 
• Data Base : MySQL 
• Tool : Net Beans IDE 
REFERENCE: 
Battista Biggio, Giorgio Fumera, and Fabio Roli, “Security Evaluation of Pattern 
Classifiers under Attack” IEEE TRANSACTIONS ON KNOWLEDGE AND 
DATA ENGINEERING, VOL. 26, NO. 4, APRIL 2014.

More Related Content

What's hot

Confidentiality policies UNIT 2 (CSS)
Confidentiality policies UNIT 2 (CSS)Confidentiality policies UNIT 2 (CSS)
Confidentiality policies UNIT 2 (CSS)
SURBHI SAROHA
 
Tools and methods used in cyber crime
Tools and methods used in cyber crimeTools and methods used in cyber crime
Tools and methods used in cyber crime
shubhravrat Deshpande
 
Windows Security
Windows Security Windows Security
Windows Security
Pooja Talreja
 
CNIT 140: Perimeter Security
CNIT 140: Perimeter SecurityCNIT 140: Perimeter Security
CNIT 140: Perimeter Security
Sam Bowne
 
Secure architecture principles isolation and leas(CSS unit 3 Part 1)
Secure architecture principles isolation and leas(CSS unit 3 Part 1)Secure architecture principles isolation and leas(CSS unit 3 Part 1)
Secure architecture principles isolation and leas(CSS unit 3 Part 1)
SURBHI SAROHA
 
SDN( Software Defined Network) and NFV(Network Function Virtualization) for I...
SDN( Software Defined Network) and NFV(Network Function Virtualization) for I...SDN( Software Defined Network) and NFV(Network Function Virtualization) for I...
SDN( Software Defined Network) and NFV(Network Function Virtualization) for I...
Sagar Rai
 
Legal Privacy and Ethical Issues in Computer Security.pptx
Legal Privacy and Ethical Issues in Computer Security.pptxLegal Privacy and Ethical Issues in Computer Security.pptx
Legal Privacy and Ethical Issues in Computer Security.pptx
KRITARTHBANSAL1
 
Layers and types of cloud
Layers and types of cloudLayers and types of cloud
Layers and types of cloud
ANUSUYA T K
 
Limitations of memory system performance
Limitations of memory system performanceLimitations of memory system performance
Limitations of memory system performance
Syed Zaid Irshad
 
cache memory
 cache memory cache memory
cache memory
NAHID HASAN
 
Virus and its CounterMeasures -- Pruthvi Monarch
Virus and its CounterMeasures                         -- Pruthvi Monarch Virus and its CounterMeasures                         -- Pruthvi Monarch
Virus and its CounterMeasures -- Pruthvi Monarch
Pruthvi Monarch
 
Security vulnerability
Security vulnerabilitySecurity vulnerability
Security vulnerability
A. Shamel
 
Intrusion prevention system(ips)
Intrusion prevention system(ips)Intrusion prevention system(ips)
Intrusion prevention system(ips)
Papun Papun
 
key distribution in network security
key distribution in network securitykey distribution in network security
key distribution in network security
babak danyal
 
Demand paging
Demand pagingDemand paging
Demand paging
SwaroopSorte
 
Computer System Security
Computer System SecurityComputer System Security
Computer System Security
SURBHI SAROHA
 
Intrusion detection and prevention system
Intrusion detection and prevention systemIntrusion detection and prevention system
Intrusion detection and prevention system
Nikhil Raj
 
I/O System
I/O SystemI/O System
I/O System
Nagarajan
 
Operating system security
Operating system securityOperating system security
Operating system security
Ramesh Ogania
 
Virtualization in Cloud Computing and Machine reference Model
Virtualization in Cloud Computing and Machine reference ModelVirtualization in Cloud Computing and Machine reference Model
Virtualization in Cloud Computing and Machine reference Model
Dr Neelesh Jain
 

What's hot (20)

Confidentiality policies UNIT 2 (CSS)
Confidentiality policies UNIT 2 (CSS)Confidentiality policies UNIT 2 (CSS)
Confidentiality policies UNIT 2 (CSS)
 
Tools and methods used in cyber crime
Tools and methods used in cyber crimeTools and methods used in cyber crime
Tools and methods used in cyber crime
 
Windows Security
Windows Security Windows Security
Windows Security
 
CNIT 140: Perimeter Security
CNIT 140: Perimeter SecurityCNIT 140: Perimeter Security
CNIT 140: Perimeter Security
 
Secure architecture principles isolation and leas(CSS unit 3 Part 1)
Secure architecture principles isolation and leas(CSS unit 3 Part 1)Secure architecture principles isolation and leas(CSS unit 3 Part 1)
Secure architecture principles isolation and leas(CSS unit 3 Part 1)
 
SDN( Software Defined Network) and NFV(Network Function Virtualization) for I...
SDN( Software Defined Network) and NFV(Network Function Virtualization) for I...SDN( Software Defined Network) and NFV(Network Function Virtualization) for I...
SDN( Software Defined Network) and NFV(Network Function Virtualization) for I...
 
Legal Privacy and Ethical Issues in Computer Security.pptx
Legal Privacy and Ethical Issues in Computer Security.pptxLegal Privacy and Ethical Issues in Computer Security.pptx
Legal Privacy and Ethical Issues in Computer Security.pptx
 
Layers and types of cloud
Layers and types of cloudLayers and types of cloud
Layers and types of cloud
 
Limitations of memory system performance
Limitations of memory system performanceLimitations of memory system performance
Limitations of memory system performance
 
cache memory
 cache memory cache memory
cache memory
 
Virus and its CounterMeasures -- Pruthvi Monarch
Virus and its CounterMeasures                         -- Pruthvi Monarch Virus and its CounterMeasures                         -- Pruthvi Monarch
Virus and its CounterMeasures -- Pruthvi Monarch
 
Security vulnerability
Security vulnerabilitySecurity vulnerability
Security vulnerability
 
Intrusion prevention system(ips)
Intrusion prevention system(ips)Intrusion prevention system(ips)
Intrusion prevention system(ips)
 
key distribution in network security
key distribution in network securitykey distribution in network security
key distribution in network security
 
Demand paging
Demand pagingDemand paging
Demand paging
 
Computer System Security
Computer System SecurityComputer System Security
Computer System Security
 
Intrusion detection and prevention system
Intrusion detection and prevention systemIntrusion detection and prevention system
Intrusion detection and prevention system
 
I/O System
I/O SystemI/O System
I/O System
 
Operating system security
Operating system securityOperating system security
Operating system security
 
Virtualization in Cloud Computing and Machine reference Model
Virtualization in Cloud Computing and Machine reference ModelVirtualization in Cloud Computing and Machine reference Model
Virtualization in Cloud Computing and Machine reference Model
 

Similar to Security evaluation of pattern classifiers under attack

Security evaluation of pattern classifiers under attack
Security evaluation of pattern classifiers under attackSecurity evaluation of pattern classifiers under attack
Security evaluation of pattern classifiers under attack
Shakas Technologies
 
JPJ1425 Security Evaluation of Pattern Classifiers under Attack
JPJ1425  Security Evaluation of Pattern Classifiers under AttackJPJ1425  Security Evaluation of Pattern Classifiers under Attack
JPJ1425 Security Evaluation of Pattern Classifiers under Attack
chennaijp
 
IEEE 2014 JAVA DATA MINING PROJECTS Security evaluation of pattern classifier...
IEEE 2014 JAVA DATA MINING PROJECTS Security evaluation of pattern classifier...IEEE 2014 JAVA DATA MINING PROJECTS Security evaluation of pattern classifier...
IEEE 2014 JAVA DATA MINING PROJECTS Security evaluation of pattern classifier...
IEEEFINALYEARSTUDENTPROJECTS
 
2014 IEEE JAVA DATA MINING PROJECT Security evaluation of pattern classifiers...
2014 IEEE JAVA DATA MINING PROJECT Security evaluation of pattern classifiers...2014 IEEE JAVA DATA MINING PROJECT Security evaluation of pattern classifiers...
2014 IEEE JAVA DATA MINING PROJECT Security evaluation of pattern classifiers...
IEEEMEMTECHSTUDENTSPROJECTS
 
security evaluation of pattern classifiers under attack
security evaluation of pattern classifiers under attacksecurity evaluation of pattern classifiers under attack
security evaluation of pattern classifiers under attack
swathi78
 
Spam email filtering
Spam email filteringSpam email filtering
Spam email filtering
National Institute
 
Certified Ethical Hacking
Certified Ethical HackingCertified Ethical Hacking
Certified Ethical Hacking
Jennifer Wood
 
2014 IEEE DOTNET PARALLEL DISTRIBUTED PROJECT A system-for-denial-of-service-...
2014 IEEE DOTNET PARALLEL DISTRIBUTED PROJECT A system-for-denial-of-service-...2014 IEEE DOTNET PARALLEL DISTRIBUTED PROJECT A system-for-denial-of-service-...
2014 IEEE DOTNET PARALLEL DISTRIBUTED PROJECT A system-for-denial-of-service-...
IEEEGLOBALSOFTSTUDENTSPROJECTS
 
IEEE 2014 DOTNET PARALLEL DISTRIBUTED PROJECTS A system-for-denial-of-service...
IEEE 2014 DOTNET PARALLEL DISTRIBUTED PROJECTS A system-for-denial-of-service...IEEE 2014 DOTNET PARALLEL DISTRIBUTED PROJECTS A system-for-denial-of-service...
IEEE 2014 DOTNET PARALLEL DISTRIBUTED PROJECTS A system-for-denial-of-service...
IEEEMEMTECHSTUDENTPROJECTS
 
Evasion Attack Detection using Adaboost Learning Classifier
Evasion Attack Detection using Adaboost Learning ClassifierEvasion Attack Detection using Adaboost Learning Classifier
Evasion Attack Detection using Adaboost Learning Classifier
IRJET Journal
 
The Next Generation Cognitive Security Operations Center: Adaptive Analytic L...
The Next Generation Cognitive Security Operations Center: Adaptive Analytic L...The Next Generation Cognitive Security Operations Center: Adaptive Analytic L...
The Next Generation Cognitive Security Operations Center: Adaptive Analytic L...
Konstantinos Demertzis
 
A Survey of Security of Multimodal Biometric Systems
A Survey of Security of Multimodal Biometric SystemsA Survey of Security of Multimodal Biometric Systems
A Survey of Security of Multimodal Biometric Systems
IJERA Editor
 
A Survey On Intrusion Detection Systems
A Survey On Intrusion Detection SystemsA Survey On Intrusion Detection Systems
A Survey On Intrusion Detection Systems
Mary Calkins
 
Ids 013 detection approaches
Ids 013 detection approachesIds 013 detection approaches
Ids 013 detection approaches
jyoti_lakhani
 
Framework for analyzing template security and privacy in biometric authentica...
Framework for analyzing template security and privacy in biometric authentica...Framework for analyzing template security and privacy in biometric authentica...
Framework for analyzing template security and privacy in biometric authentica...nithyakarunanithi
 
A network worm vaccine architecture
A network worm vaccine architectureA network worm vaccine architecture
A network worm vaccine architectureUltraUploader
 
Iaetsd a survey on detecting denial-of-service attacks
Iaetsd a survey on detecting denial-of-service attacksIaetsd a survey on detecting denial-of-service attacks
Iaetsd a survey on detecting denial-of-service attacks
Iaetsd Iaetsd
 
A PHASED APPROACH TO INTRUSION DETECTION IN NETWORK
A PHASED APPROACH TO INTRUSION DETECTION IN NETWORKA PHASED APPROACH TO INTRUSION DETECTION IN NETWORK
A PHASED APPROACH TO INTRUSION DETECTION IN NETWORK
IRJET Journal
 
IRJET- An Intrusion Detection Framework based on Binary Classifiers Optimized...
IRJET- An Intrusion Detection Framework based on Binary Classifiers Optimized...IRJET- An Intrusion Detection Framework based on Binary Classifiers Optimized...
IRJET- An Intrusion Detection Framework based on Binary Classifiers Optimized...
IRJET Journal
 
Elevating Connectivity Exploring - Telecom Security Monitoring Solutions.pdf
Elevating Connectivity Exploring - Telecom Security Monitoring Solutions.pdfElevating Connectivity Exploring - Telecom Security Monitoring Solutions.pdf
Elevating Connectivity Exploring - Telecom Security Monitoring Solutions.pdf
SecurityGen1
 

Similar to Security evaluation of pattern classifiers under attack (20)

Security evaluation of pattern classifiers under attack
Security evaluation of pattern classifiers under attackSecurity evaluation of pattern classifiers under attack
Security evaluation of pattern classifiers under attack
 
JPJ1425 Security Evaluation of Pattern Classifiers under Attack
JPJ1425  Security Evaluation of Pattern Classifiers under AttackJPJ1425  Security Evaluation of Pattern Classifiers under Attack
JPJ1425 Security Evaluation of Pattern Classifiers under Attack
 
IEEE 2014 JAVA DATA MINING PROJECTS Security evaluation of pattern classifier...
IEEE 2014 JAVA DATA MINING PROJECTS Security evaluation of pattern classifier...IEEE 2014 JAVA DATA MINING PROJECTS Security evaluation of pattern classifier...
IEEE 2014 JAVA DATA MINING PROJECTS Security evaluation of pattern classifier...
 
2014 IEEE JAVA DATA MINING PROJECT Security evaluation of pattern classifiers...
2014 IEEE JAVA DATA MINING PROJECT Security evaluation of pattern classifiers...2014 IEEE JAVA DATA MINING PROJECT Security evaluation of pattern classifiers...
2014 IEEE JAVA DATA MINING PROJECT Security evaluation of pattern classifiers...
 
security evaluation of pattern classifiers under attack
security evaluation of pattern classifiers under attacksecurity evaluation of pattern classifiers under attack
security evaluation of pattern classifiers under attack
 
Spam email filtering
Spam email filteringSpam email filtering
Spam email filtering
 
Certified Ethical Hacking
Certified Ethical HackingCertified Ethical Hacking
Certified Ethical Hacking
 
2014 IEEE DOTNET PARALLEL DISTRIBUTED PROJECT A system-for-denial-of-service-...
2014 IEEE DOTNET PARALLEL DISTRIBUTED PROJECT A system-for-denial-of-service-...2014 IEEE DOTNET PARALLEL DISTRIBUTED PROJECT A system-for-denial-of-service-...
2014 IEEE DOTNET PARALLEL DISTRIBUTED PROJECT A system-for-denial-of-service-...
 
IEEE 2014 DOTNET PARALLEL DISTRIBUTED PROJECTS A system-for-denial-of-service...
IEEE 2014 DOTNET PARALLEL DISTRIBUTED PROJECTS A system-for-denial-of-service...IEEE 2014 DOTNET PARALLEL DISTRIBUTED PROJECTS A system-for-denial-of-service...
IEEE 2014 DOTNET PARALLEL DISTRIBUTED PROJECTS A system-for-denial-of-service...
 
Evasion Attack Detection using Adaboost Learning Classifier
Evasion Attack Detection using Adaboost Learning ClassifierEvasion Attack Detection using Adaboost Learning Classifier
Evasion Attack Detection using Adaboost Learning Classifier
 
The Next Generation Cognitive Security Operations Center: Adaptive Analytic L...
The Next Generation Cognitive Security Operations Center: Adaptive Analytic L...The Next Generation Cognitive Security Operations Center: Adaptive Analytic L...
The Next Generation Cognitive Security Operations Center: Adaptive Analytic L...
 
A Survey of Security of Multimodal Biometric Systems
A Survey of Security of Multimodal Biometric SystemsA Survey of Security of Multimodal Biometric Systems
A Survey of Security of Multimodal Biometric Systems
 
A Survey On Intrusion Detection Systems
A Survey On Intrusion Detection SystemsA Survey On Intrusion Detection Systems
A Survey On Intrusion Detection Systems
 
Ids 013 detection approaches
Ids 013 detection approachesIds 013 detection approaches
Ids 013 detection approaches
 
Framework for analyzing template security and privacy in biometric authentica...
Framework for analyzing template security and privacy in biometric authentica...Framework for analyzing template security and privacy in biometric authentica...
Framework for analyzing template security and privacy in biometric authentica...
 
A network worm vaccine architecture
A network worm vaccine architectureA network worm vaccine architecture
A network worm vaccine architecture
 
Iaetsd a survey on detecting denial-of-service attacks
Iaetsd a survey on detecting denial-of-service attacksIaetsd a survey on detecting denial-of-service attacks
Iaetsd a survey on detecting denial-of-service attacks
 
A PHASED APPROACH TO INTRUSION DETECTION IN NETWORK
A PHASED APPROACH TO INTRUSION DETECTION IN NETWORKA PHASED APPROACH TO INTRUSION DETECTION IN NETWORK
A PHASED APPROACH TO INTRUSION DETECTION IN NETWORK
 
IRJET- An Intrusion Detection Framework based on Binary Classifiers Optimized...
IRJET- An Intrusion Detection Framework based on Binary Classifiers Optimized...IRJET- An Intrusion Detection Framework based on Binary Classifiers Optimized...
IRJET- An Intrusion Detection Framework based on Binary Classifiers Optimized...
 
Elevating Connectivity Exploring - Telecom Security Monitoring Solutions.pdf
Elevating Connectivity Exploring - Telecom Security Monitoring Solutions.pdfElevating Connectivity Exploring - Telecom Security Monitoring Solutions.pdf
Elevating Connectivity Exploring - Telecom Security Monitoring Solutions.pdf
 

More from Papitha Velumani

2015 - 2016 IEEE Project Titles and abstracts in Java
2015 - 2016 IEEE Project Titles and abstracts in Java2015 - 2016 IEEE Project Titles and abstracts in Java
2015 - 2016 IEEE Project Titles and abstracts in Java
Papitha Velumani
 
2015 - 2016 IEEE Project Titles and abstracts in Android
2015 - 2016 IEEE Project Titles and abstracts in Android 2015 - 2016 IEEE Project Titles and abstracts in Android
2015 - 2016 IEEE Project Titles and abstracts in Android
Papitha Velumani
 
2015 - 2016 IEEE Project Titles and abstracts in Dotnet
2015 - 2016 IEEE Project Titles and abstracts in Dotnet 2015 - 2016 IEEE Project Titles and abstracts in Dotnet
2015 - 2016 IEEE Project Titles and abstracts in Dotnet
Papitha Velumani
 
Trajectory improves data delivery in urban vehicular networks
Trajectory improves data delivery in urban vehicular networks Trajectory improves data delivery in urban vehicular networks
Trajectory improves data delivery in urban vehicular networks
Papitha Velumani
 
Tracon interference aware scheduling for data-intensive applications in virtu...
Tracon interference aware scheduling for data-intensive applications in virtu...Tracon interference aware scheduling for data-intensive applications in virtu...
Tracon interference aware scheduling for data-intensive applications in virtu...
Papitha Velumani
 
Supporting privacy protection in personalized web search
Supporting privacy protection in personalized web searchSupporting privacy protection in personalized web search
Supporting privacy protection in personalized web searchPapitha Velumani
 
Stochastic bandwidth estimation in networks with random service
Stochastic bandwidth estimation in networks with random serviceStochastic bandwidth estimation in networks with random service
Stochastic bandwidth estimation in networks with random servicePapitha Velumani
 
Sos a distributed mobile q&a system based on social networks
Sos a distributed mobile q&a system based on social networksSos a distributed mobile q&a system based on social networks
Sos a distributed mobile q&a system based on social networksPapitha Velumani
 
Real time misbehavior detection in ieee 802.11-based wireless networks an ana...
Real time misbehavior detection in ieee 802.11-based wireless networks an ana...Real time misbehavior detection in ieee 802.11-based wireless networks an ana...
Real time misbehavior detection in ieee 802.11-based wireless networks an ana...
Papitha Velumani
 
Probabilistic consolidation of virtual machines in self organizing cloud data...
Probabilistic consolidation of virtual machines in self organizing cloud data...Probabilistic consolidation of virtual machines in self organizing cloud data...
Probabilistic consolidation of virtual machines in self organizing cloud data...
Papitha Velumani
 
Privacy preserving multi-keyword ranked search over encrypted cloud data
Privacy preserving multi-keyword ranked search over encrypted cloud dataPrivacy preserving multi-keyword ranked search over encrypted cloud data
Privacy preserving multi-keyword ranked search over encrypted cloud data
Papitha Velumani
 
Privacy preserving and content-protecting location based queries
Privacy preserving and content-protecting location based queriesPrivacy preserving and content-protecting location based queries
Privacy preserving and content-protecting location based queries
Papitha Velumani
 
Pack prediction based cloud bandwidth and cost reduction system
Pack prediction based cloud bandwidth and cost reduction systemPack prediction based cloud bandwidth and cost reduction system
Pack prediction based cloud bandwidth and cost reduction system
Papitha Velumani
 
Occt a one class clustering tree for implementing one-to-man data linkage
Occt a one class clustering tree for implementing one-to-man data linkageOcct a one class clustering tree for implementing one-to-man data linkage
Occt a one class clustering tree for implementing one-to-man data linkage
Papitha Velumani
 
Leveraging social networks for p2p content based file sharing in disconnected...
Leveraging social networks for p2p content based file sharing in disconnected...Leveraging social networks for p2p content based file sharing in disconnected...
Leveraging social networks for p2p content based file sharing in disconnected...
Papitha Velumani
 
LDBP: localized boundary detection and parametrization for 3 d sensor networks
LDBP: localized boundary detection and parametrization for 3 d sensor networksLDBP: localized boundary detection and parametrization for 3 d sensor networks
LDBP: localized boundary detection and parametrization for 3 d sensor networks
Papitha Velumani
 
Integrity for join queries in the cloud
Integrity for join queries in the cloudIntegrity for join queries in the cloud
Integrity for join queries in the cloud
Papitha Velumani
 
Improving fairness, efficiency, and stability in http based adaptive video st...
Improving fairness, efficiency, and stability in http based adaptive video st...Improving fairness, efficiency, and stability in http based adaptive video st...
Improving fairness, efficiency, and stability in http based adaptive video st...
Papitha Velumani
 
Hybrid attribute and re-encryption-based key management for secure and scala...
Hybrid attribute  and re-encryption-based key management for secure and scala...Hybrid attribute  and re-encryption-based key management for secure and scala...
Hybrid attribute and re-encryption-based key management for secure and scala...
Papitha Velumani
 
Friendbook a semantic based friend recommendation system for social networks
Friendbook a semantic based friend recommendation system for social networksFriendbook a semantic based friend recommendation system for social networks
Friendbook a semantic based friend recommendation system for social networks
Papitha Velumani
 

More from Papitha Velumani (20)

2015 - 2016 IEEE Project Titles and abstracts in Java
2015 - 2016 IEEE Project Titles and abstracts in Java2015 - 2016 IEEE Project Titles and abstracts in Java
2015 - 2016 IEEE Project Titles and abstracts in Java
 
2015 - 2016 IEEE Project Titles and abstracts in Android
2015 - 2016 IEEE Project Titles and abstracts in Android 2015 - 2016 IEEE Project Titles and abstracts in Android
2015 - 2016 IEEE Project Titles and abstracts in Android
 
2015 - 2016 IEEE Project Titles and abstracts in Dotnet
2015 - 2016 IEEE Project Titles and abstracts in Dotnet 2015 - 2016 IEEE Project Titles and abstracts in Dotnet
2015 - 2016 IEEE Project Titles and abstracts in Dotnet
 
Trajectory improves data delivery in urban vehicular networks
Trajectory improves data delivery in urban vehicular networks Trajectory improves data delivery in urban vehicular networks
Trajectory improves data delivery in urban vehicular networks
 
Tracon interference aware scheduling for data-intensive applications in virtu...
Tracon interference aware scheduling for data-intensive applications in virtu...Tracon interference aware scheduling for data-intensive applications in virtu...
Tracon interference aware scheduling for data-intensive applications in virtu...
 
Supporting privacy protection in personalized web search
Supporting privacy protection in personalized web searchSupporting privacy protection in personalized web search
Supporting privacy protection in personalized web search
 
Stochastic bandwidth estimation in networks with random service
Stochastic bandwidth estimation in networks with random serviceStochastic bandwidth estimation in networks with random service
Stochastic bandwidth estimation in networks with random service
 
Sos a distributed mobile q&a system based on social networks
Sos a distributed mobile q&a system based on social networksSos a distributed mobile q&a system based on social networks
Sos a distributed mobile q&a system based on social networks
 
Real time misbehavior detection in ieee 802.11-based wireless networks an ana...
Real time misbehavior detection in ieee 802.11-based wireless networks an ana...Real time misbehavior detection in ieee 802.11-based wireless networks an ana...
Real time misbehavior detection in ieee 802.11-based wireless networks an ana...
 
Probabilistic consolidation of virtual machines in self organizing cloud data...
Probabilistic consolidation of virtual machines in self organizing cloud data...Probabilistic consolidation of virtual machines in self organizing cloud data...
Probabilistic consolidation of virtual machines in self organizing cloud data...
 
Privacy preserving multi-keyword ranked search over encrypted cloud data
Privacy preserving multi-keyword ranked search over encrypted cloud dataPrivacy preserving multi-keyword ranked search over encrypted cloud data
Privacy preserving multi-keyword ranked search over encrypted cloud data
 
Privacy preserving and content-protecting location based queries
Privacy preserving and content-protecting location based queriesPrivacy preserving and content-protecting location based queries
Privacy preserving and content-protecting location based queries
 
Pack prediction based cloud bandwidth and cost reduction system
Pack prediction based cloud bandwidth and cost reduction systemPack prediction based cloud bandwidth and cost reduction system
Pack prediction based cloud bandwidth and cost reduction system
 
Occt a one class clustering tree for implementing one-to-man data linkage
Occt a one class clustering tree for implementing one-to-man data linkageOcct a one class clustering tree for implementing one-to-man data linkage
Occt a one class clustering tree for implementing one-to-man data linkage
 
Leveraging social networks for p2p content based file sharing in disconnected...
Leveraging social networks for p2p content based file sharing in disconnected...Leveraging social networks for p2p content based file sharing in disconnected...
Leveraging social networks for p2p content based file sharing in disconnected...
 
LDBP: localized boundary detection and parametrization for 3 d sensor networks
LDBP: localized boundary detection and parametrization for 3 d sensor networksLDBP: localized boundary detection and parametrization for 3 d sensor networks
LDBP: localized boundary detection and parametrization for 3 d sensor networks
 
Integrity for join queries in the cloud
Integrity for join queries in the cloudIntegrity for join queries in the cloud
Integrity for join queries in the cloud
 
Improving fairness, efficiency, and stability in http based adaptive video st...
Improving fairness, efficiency, and stability in http based adaptive video st...Improving fairness, efficiency, and stability in http based adaptive video st...
Improving fairness, efficiency, and stability in http based adaptive video st...
 
Hybrid attribute and re-encryption-based key management for secure and scala...
Hybrid attribute  and re-encryption-based key management for secure and scala...Hybrid attribute  and re-encryption-based key management for secure and scala...
Hybrid attribute and re-encryption-based key management for secure and scala...
 
Friendbook a semantic based friend recommendation system for social networks
Friendbook a semantic based friend recommendation system for social networksFriendbook a semantic based friend recommendation system for social networks
Friendbook a semantic based friend recommendation system for social networks
 

Recently uploaded

Honest Reviews of Tim Han LMA Course Program.pptx
Honest Reviews of Tim Han LMA Course Program.pptxHonest Reviews of Tim Han LMA Course Program.pptx
Honest Reviews of Tim Han LMA Course Program.pptx
timhan337
 
How libraries can support authors with open access requirements for UKRI fund...
How libraries can support authors with open access requirements for UKRI fund...How libraries can support authors with open access requirements for UKRI fund...
How libraries can support authors with open access requirements for UKRI fund...
Jisc
 
Instructions for Submissions thorugh G- Classroom.pptx
Instructions for Submissions thorugh G- Classroom.pptxInstructions for Submissions thorugh G- Classroom.pptx
Instructions for Submissions thorugh G- Classroom.pptx
Jheel Barad
 
Supporting (UKRI) OA monographs at Salford.pptx
Supporting (UKRI) OA monographs at Salford.pptxSupporting (UKRI) OA monographs at Salford.pptx
Supporting (UKRI) OA monographs at Salford.pptx
Jisc
 
Embracing GenAI - A Strategic Imperative
Embracing GenAI - A Strategic ImperativeEmbracing GenAI - A Strategic Imperative
Embracing GenAI - A Strategic Imperative
Peter Windle
 
Thesis Statement for students diagnonsed withADHD.ppt
Thesis Statement for students diagnonsed withADHD.pptThesis Statement for students diagnonsed withADHD.ppt
Thesis Statement for students diagnonsed withADHD.ppt
EverAndrsGuerraGuerr
 
Sha'Carri Richardson Presentation 202345
Sha'Carri Richardson Presentation 202345Sha'Carri Richardson Presentation 202345
Sha'Carri Richardson Presentation 202345
beazzy04
 
The Accursed House by Émile Gaboriau.pptx
The Accursed House by Émile Gaboriau.pptxThe Accursed House by Émile Gaboriau.pptx
The Accursed House by Émile Gaboriau.pptx
DhatriParmar
 
BÀI TẬP BỔ TRỢ TIẾNG ANH GLOBAL SUCCESS LỚP 3 - CẢ NĂM (CÓ FILE NGHE VÀ ĐÁP Á...
BÀI TẬP BỔ TRỢ TIẾNG ANH GLOBAL SUCCESS LỚP 3 - CẢ NĂM (CÓ FILE NGHE VÀ ĐÁP Á...BÀI TẬP BỔ TRỢ TIẾNG ANH GLOBAL SUCCESS LỚP 3 - CẢ NĂM (CÓ FILE NGHE VÀ ĐÁP Á...
BÀI TẬP BỔ TRỢ TIẾNG ANH GLOBAL SUCCESS LỚP 3 - CẢ NĂM (CÓ FILE NGHE VÀ ĐÁP Á...
Nguyen Thanh Tu Collection
 
Home assignment II on Spectroscopy 2024 Answers.pdf
Home assignment II on Spectroscopy 2024 Answers.pdfHome assignment II on Spectroscopy 2024 Answers.pdf
Home assignment II on Spectroscopy 2024 Answers.pdf
Tamralipta Mahavidyalaya
 
Operation Blue Star - Saka Neela Tara
Operation Blue Star   -  Saka Neela TaraOperation Blue Star   -  Saka Neela Tara
Operation Blue Star - Saka Neela Tara
Balvir Singh
 
The Roman Empire A Historical Colossus.pdf
The Roman Empire A Historical Colossus.pdfThe Roman Empire A Historical Colossus.pdf
The Roman Empire A Historical Colossus.pdf
kaushalkr1407
 
special B.ed 2nd year old paper_20240531.pdf
special B.ed 2nd year old paper_20240531.pdfspecial B.ed 2nd year old paper_20240531.pdf
special B.ed 2nd year old paper_20240531.pdf
Special education needs
 
Introduction to AI for Nonprofits with Tapp Network
Introduction to AI for Nonprofits with Tapp NetworkIntroduction to AI for Nonprofits with Tapp Network
Introduction to AI for Nonprofits with Tapp Network
TechSoup
 
Additional Benefits for Employee Website.pdf
Additional Benefits for Employee Website.pdfAdditional Benefits for Employee Website.pdf
Additional Benefits for Employee Website.pdf
joachimlavalley1
 
How to Make a Field invisible in Odoo 17
How to Make a Field invisible in Odoo 17How to Make a Field invisible in Odoo 17
How to Make a Field invisible in Odoo 17
Celine George
 
Unit 2- Research Aptitude (UGC NET Paper I).pdf
Unit 2- Research Aptitude (UGC NET Paper I).pdfUnit 2- Research Aptitude (UGC NET Paper I).pdf
Unit 2- Research Aptitude (UGC NET Paper I).pdf
Thiyagu K
 
Adversarial Attention Modeling for Multi-dimensional Emotion Regression.pdf
Adversarial Attention Modeling for Multi-dimensional Emotion Regression.pdfAdversarial Attention Modeling for Multi-dimensional Emotion Regression.pdf
Adversarial Attention Modeling for Multi-dimensional Emotion Regression.pdf
Po-Chuan Chen
 
1.4 modern child centered education - mahatma gandhi-2.pptx
1.4 modern child centered education - mahatma gandhi-2.pptx1.4 modern child centered education - mahatma gandhi-2.pptx
1.4 modern child centered education - mahatma gandhi-2.pptx
JosvitaDsouza2
 
The approach at University of Liverpool.pptx
The approach at University of Liverpool.pptxThe approach at University of Liverpool.pptx
The approach at University of Liverpool.pptx
Jisc
 

Recently uploaded (20)

Honest Reviews of Tim Han LMA Course Program.pptx
Honest Reviews of Tim Han LMA Course Program.pptxHonest Reviews of Tim Han LMA Course Program.pptx
Honest Reviews of Tim Han LMA Course Program.pptx
 
How libraries can support authors with open access requirements for UKRI fund...
How libraries can support authors with open access requirements for UKRI fund...How libraries can support authors with open access requirements for UKRI fund...
How libraries can support authors with open access requirements for UKRI fund...
 
Instructions for Submissions thorugh G- Classroom.pptx
Instructions for Submissions thorugh G- Classroom.pptxInstructions for Submissions thorugh G- Classroom.pptx
Instructions for Submissions thorugh G- Classroom.pptx
 
Supporting (UKRI) OA monographs at Salford.pptx
Supporting (UKRI) OA monographs at Salford.pptxSupporting (UKRI) OA monographs at Salford.pptx
Supporting (UKRI) OA monographs at Salford.pptx
 
Embracing GenAI - A Strategic Imperative
Embracing GenAI - A Strategic ImperativeEmbracing GenAI - A Strategic Imperative
Embracing GenAI - A Strategic Imperative
 
Thesis Statement for students diagnonsed withADHD.ppt
Thesis Statement for students diagnonsed withADHD.pptThesis Statement for students diagnonsed withADHD.ppt
Thesis Statement for students diagnonsed withADHD.ppt
 
Sha'Carri Richardson Presentation 202345
Sha'Carri Richardson Presentation 202345Sha'Carri Richardson Presentation 202345
Sha'Carri Richardson Presentation 202345
 
The Accursed House by Émile Gaboriau.pptx
The Accursed House by Émile Gaboriau.pptxThe Accursed House by Émile Gaboriau.pptx
The Accursed House by Émile Gaboriau.pptx
 
BÀI TẬP BỔ TRỢ TIẾNG ANH GLOBAL SUCCESS LỚP 3 - CẢ NĂM (CÓ FILE NGHE VÀ ĐÁP Á...
BÀI TẬP BỔ TRỢ TIẾNG ANH GLOBAL SUCCESS LỚP 3 - CẢ NĂM (CÓ FILE NGHE VÀ ĐÁP Á...BÀI TẬP BỔ TRỢ TIẾNG ANH GLOBAL SUCCESS LỚP 3 - CẢ NĂM (CÓ FILE NGHE VÀ ĐÁP Á...
BÀI TẬP BỔ TRỢ TIẾNG ANH GLOBAL SUCCESS LỚP 3 - CẢ NĂM (CÓ FILE NGHE VÀ ĐÁP Á...
 
Home assignment II on Spectroscopy 2024 Answers.pdf
Home assignment II on Spectroscopy 2024 Answers.pdfHome assignment II on Spectroscopy 2024 Answers.pdf
Home assignment II on Spectroscopy 2024 Answers.pdf
 
Operation Blue Star - Saka Neela Tara
Operation Blue Star   -  Saka Neela TaraOperation Blue Star   -  Saka Neela Tara
Operation Blue Star - Saka Neela Tara
 
The Roman Empire A Historical Colossus.pdf
The Roman Empire A Historical Colossus.pdfThe Roman Empire A Historical Colossus.pdf
The Roman Empire A Historical Colossus.pdf
 
special B.ed 2nd year old paper_20240531.pdf
special B.ed 2nd year old paper_20240531.pdfspecial B.ed 2nd year old paper_20240531.pdf
special B.ed 2nd year old paper_20240531.pdf
 
Introduction to AI for Nonprofits with Tapp Network
Introduction to AI for Nonprofits with Tapp NetworkIntroduction to AI for Nonprofits with Tapp Network
Introduction to AI for Nonprofits with Tapp Network
 
Additional Benefits for Employee Website.pdf
Additional Benefits for Employee Website.pdfAdditional Benefits for Employee Website.pdf
Additional Benefits for Employee Website.pdf
 
How to Make a Field invisible in Odoo 17
How to Make a Field invisible in Odoo 17How to Make a Field invisible in Odoo 17
How to Make a Field invisible in Odoo 17
 
Unit 2- Research Aptitude (UGC NET Paper I).pdf
Unit 2- Research Aptitude (UGC NET Paper I).pdfUnit 2- Research Aptitude (UGC NET Paper I).pdf
Unit 2- Research Aptitude (UGC NET Paper I).pdf
 
Adversarial Attention Modeling for Multi-dimensional Emotion Regression.pdf
Adversarial Attention Modeling for Multi-dimensional Emotion Regression.pdfAdversarial Attention Modeling for Multi-dimensional Emotion Regression.pdf
Adversarial Attention Modeling for Multi-dimensional Emotion Regression.pdf
 
1.4 modern child centered education - mahatma gandhi-2.pptx
1.4 modern child centered education - mahatma gandhi-2.pptx1.4 modern child centered education - mahatma gandhi-2.pptx
1.4 modern child centered education - mahatma gandhi-2.pptx
 
The approach at University of Liverpool.pptx
The approach at University of Liverpool.pptxThe approach at University of Liverpool.pptx
The approach at University of Liverpool.pptx
 

Security evaluation of pattern classifiers under attack

  • 1. SECURITY EVALUATION OF PATTERN CLASSIFIERS UNDER ATTACK ABSTRACT: Pattern classification systems are commonly used in adversarial applications, like biometric authentication, network intrusion detection, and spam filtering, in which data can be purposely manipulated by humans to undermine their operation. As this adversarial scenario is not taken into account by classical design methods, pattern classification systems may exhibit vulnerabilities, whose exploitation may severely affect their performance, and consequently limit their practical utility. Extending pattern classification theory and design methods to adversarial settings is thus a novel and very relevant research direction, which has not yet been pursued in a systematic way. In this paper, we address one of the main open issues: evaluating at design phase the security of pattern classifiers, namely, the performance degradation under potential attacks they may incur during operation. We propose a framework for empirical
  • 2. evaluation of classifier security that formalizes and generalizes the main ideas proposed in the literature, and give examples of its use in three real applications. Reported results show that security evaluation can provide a more complete understanding of the classifier’s behavior in adversarial environments, and lead to better design choices. EXISTING SYSTEM: PATTERN classification systems based on machine learning algorithms are commonly used in security-related applications like biometric authentication, network intrusion detection, and spam filtering, to discriminate between a “legitimate” and a “malicious” pattern class (e.g., legitimate and spam emails). Contrary to traditional ones, these applications have an intrinsic adversarial nature since the input data can be purposely manipulated by an intelligent and adaptive adversary to undermine classifier operation. This often gives rise to an arms race between the adversary and the classifier designer. Well known examples of attacks against pattern classifiers are:
  • 3. submitting a fake biometric trait to a biometric authentication system (spoofing attack); modifying network packets belonging to intrusive traffic to evade intrusion detection systems (IDSs) ; manipulating the content of spam emails to get them past spam filters (e.g., by misspelling common spam words to avoid their detection). Adversarial scenarios can also occur in intelligent data analysis and information retrieval; e.g., a malicious webmaster may manipulate search engine rankings to artificially promote her website. DISADVANTAGES OF EXISTING SYSTEM: · They exhibit vulnerabilities to several potential attacks, allowing adversaries to undermine their effectiveness. · It focused on application-specific issues related to spam filtering and network intrusion detection. PROPOSED SYSTEM: First, to pursue security in the context of an arms race it is not sufficient to react to observed attacks, but it is also necessary
  • 4. to proactively anticipate the adversary by predicting the most relevant, potential attacks through a what-if analysis; this allows one to develop suitable countermeasures before the attack actually occurs, according to the principle of security by design. Second, to provide practical guidelines for simulating realistic attack scenarios, we define a general model of the adversary, in terms of her goal, knowledge, and capability, which encompasses and generalizes models proposed in previous work. Third, since the presence of carefully targeted attacks may affect the distribution of training and testing data separately, we propose a model of the data distribution that can formally characterize this behavior, and that allows us to take into account a large number of potential attacks; we also propose an algorithm for the generation of training and testing sets to be used for security evaluation, which can naturally accommodate application-specific and heuristic techniques for simulating attacks.
  • 5. ADVANTAGES OF PROPOSED SYSTEM: · It predicts the most relevant, potential attacks through a what-if analysis. · It provides practical guidelines for simulating realistic attack scenarios. SYSTEM CONFIGURATION:- HARDWARE REQUIREMENTS:-  Processor - Pentium –IV  Speed - 1.1 Ghz  RAM - 512 MB(min)  Hard Disk - 40 GB  Key Board - Standard Windows Keyboard  Mouse - Two or Three Button Mouse  Monitor - LCD/LED
  • 6. SOFTWARE REQUIREMENTS: • Operating system : Windows XP • Coding Language : Java • Data Base : MySQL • Tool : Net Beans IDE REFERENCE: Battista Biggio, Giorgio Fumera, and Fabio Roli, “Security Evaluation of Pattern Classifiers under Attack” IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, VOL. 26, NO. 4, APRIL 2014.
  • 7. SOFTWARE REQUIREMENTS: • Operating system : Windows XP • Coding Language : Java • Data Base : MySQL • Tool : Net Beans IDE REFERENCE: Battista Biggio, Giorgio Fumera, and Fabio Roli, “Security Evaluation of Pattern Classifiers under Attack” IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, VOL. 26, NO. 4, APRIL 2014.