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23 Results Found

SPATIAL DATA AGGREGATION- Lightweight And Privacy-Friendly Spatial Data Aggregation For Secure Power Supply And Demand Management In Smart Grids

Domain: NETWORK SECURITY
Category: DOTNET
Year: 2022
Project Code: DNS2101

In This Paper, We Propose A Secret Group-key Generation Scheme In Physical Layer, Where An Arbitrary Number Of Multi-antenna LNs (LN) Exist In Mesh Topology With A Multi-antenna Passive Eavesdropper. In The First Phase Of The Scheme, Pilot Signals Are Transmitted From Selected Antennas Of All Nodes And Each Node Estimates Channels Linked To It. In The Second Phase, Each Node Sequentially Broadcasts A Weighted Combination Of The Estimated Channel Information Using Selected Coefficients. The Other LNs Can Obtain The Channel Information Used For Group-key Generation While The Eavesdropper Cannot. Each Node Then Can Generate A Group Key By Quantizing And Encoding The Estimated Channels Into Keys. We Apply Well-known Quantization Schemes, Such As Scalar And Vector Quantizations, And Compare Their Performance. To Further Enhance The Key-generation Performance, We Also Provide How To Determine The Antennas At Each Node Used For Group-key Generation And The Coefficients Used In The Broadcast Phase. The Simulation Results Verify The Performance Of The Proposed Secret Group-key Generation Scheme Using Various Key-related Metrics. We Also Verify The Practical Robustness Of Our Scheme By Implementing A Testbed Using Universal Software Radio Peripheral. After Generating Secret Common Key Among Three Nodes, We Also Test It Using The National Institute Of Standards And Technology Test Suit. The Generated Key Passes The Test And It Is Random Enough For Communication Secrecy.

DDOS ATTACK DETECTION- Modeling Behavioural Dynamics For Asymmetric Application Layer DDoS Detection

Domain: NETWORK SECURITY
Category: DOTNET
Year: 2022
Project Code: DNS2102

Asymmetric Application Layer DDoS Attacks Using Computationally Intensive HTTP Requests Are An Extremely Dangerous Class Of Attacks Capable Of Taking Down Web Servers With Relatively Few Attacking Connections. These Attacks Consume Limited Network Bandwidth And Are Similar To Legitimate Traffic, Which Makes Their Detection Difficult. Existing Detection Mechanisms For These Attacks Use Indirect Representations Of Actual User Behaviour And Complex Modelling Techniques, Which Leads To A Higher False Positive Rate (FPR) And Longer Detection Time, Which Makes Them Unsuitable For Real Time Use. There Is A Need For Simple, Efficient And Adaptable Detection Mechanisms For Asymmetric DDoS Attacks. In This Work, An Attempt Is Made To Model The Actual Behavioural Dynamics Of Legitimate Users Using A Simple Annotated Probabilistic Timed Automata (PTA) Along With A Suspicion Scoring Mechanism For Differentiating Between Legitimate And Malicious Users. This Allows The Detection Mechanism To Be Extremely Fast And Have A Low FPR. In Addition, The Model Can Incrementally Learn From Run-time Traces, Which Makes It Adaptable And Reduces The FPR Further. Experiments On Public Datasets Reveal That Our Proposed Approach Has A High Detection Rate And Low FPR And Adds Negligible Overhead To The Web Server, Which Makes It Ideal For Real Time Use.

BIOCHEMICAL ATTACK ON DNA FINGERPRINTING Molecular Barcoding As A Defense Against Bench Top Biochemical Attacks On DNA Fingerprinting And Information Forensics

Domain: NETWORK SECURITY
Category: DOTNET
Year: 2022
Project Code: DNS2103

DNA Fingerprinting Can Offer Remarkable Benefits, Especially For Point-of-care Diagnostics, Information Forensics, And Analysis. However, The Pressure To Drive Down Costs Is Likely To Lead To Cheap Untrusted Solutions And A Multitude Of Unprecedented Risks. These Risks Will Especially Emerge At The Frontier Between The Cyberspace And DNA Biology. To Address These Risks, We Perform A Forensic-security Assessment Of A Typical DNA-fingerprinting Flow. We Demonstrate, For The First Time, Benchtop Analysis Of Biochemical-level Vulnerabilities In Flows That Are Based On A Standard Quantification Assay Known As Polymerase Chain Reaction (PCR). After Identifying Potential Vulnerabilities, We Realize Attacks Using Benchtop Techniques To Demonstrate Their Catastrophic Impact On The Outcome Of The DNA Fingerprinting. We Also Propose A Countermeasure, In Which DNA Samples Are Each Uniquely Barcoded (using Synthesized DNA Molecules) In Advance Of PCR Analysis, Thus Demonstrating The Feasibility Of Our Approach Using Benchtop Techniques. We Discuss How Molecular Barcoding Could Be Utilized Within A Cyber-biological Framework To Improve DNA-fingerprinting Security Against A Wide Range Of Threats, Including Sample Forgery. We Also Present A Security Analysis Of The DNA Barcoding Mechanism From A Molecular Biology Perspective.

MULTI ANTENNA MESH TOPOLOGY- Secret Group-Key Generation At Physical Layer For Multi-Antenna Mesh Topology

Domain: NETWORK SECURITY
Category: DOTNET
Year: 2022
Project Code: DNS2104

PRIVARY PROTECTION BASED ON ANONYMITY- Source-Location Privacy Protection Based On Anonymity Cloud In Wireless Sensor Networks

Domain: NETWORK SECURITY
Category: DOTNET
Year: 2022
Project Code: DNS2105

An Adversary Can Deploy Parasitic Sensor Nodes Into Wireless Sensor Networks To Collect Radio Traffic Distribu-tions And Trace Back Messages To Their Source Nodes. Then, He Can Locate The Monitored Targets Around The Source Nodes With A High Probability. In This Paper, A Source-location Pri-vacy Protection Scheme Based On Anonymity Cloud (SPAC) Is Proposed. We First Design A Light-weight (t,n) -threshold Message Sharing Scheme And Map The Original Message To A Set Of Message Shares Which Are Shorter In Length And Can Be Processed And Delivered With Minimal Energy Consumption. Based On The Shares, The Source Node Constructs An Anonym-ity Cloud With An Irregular Shape Around Itself To Protect Its Location Privacy. Specifically, An Anonymity Cloud Is A Set Of Active Nodes With Similar Radio Actions And They Are Statisti-cally Indistinguishable From Each Other. The Size Of The Cloud Is Controlled By The Preset Number Of Hops That The Shares Can Walk In The Cloud. At The Border Of The Cloud, The Fake Source Nodes Independently Send The Shares To The Sink Node Through Proper Routing Algorithms. At Last, The Original Message Can Be Recovered By The Sink Node Once At Least T Shares Are Re-ceived. Simulation Results Demonstrate That SPAC Can Strongly Protect The Source-location Privacy With An Efficient Manner. Moreover, The Message Sharing Mechanism Of SPAC Increases Confidentiality Of Network Data And It Also Brings High Tolerance For The Failures Of Sensor Nodes To The Data Transmission Process.

ANALYSIS OF ATTACK- Classification Of Attack Types And Analysis Of Attack Methods For Profiling Phishing Mail Attack Groups

Domain: NETWORK SECURITY
Category: DOTNET
Year: 2022
Project Code: DNS2106

In Recent Years, There Has Been An Increase In The Number Of Phishing Attacks Targeting People In The Fields Of Defense, Security, And Diplomacy Around The World. In Particular, Hacking Attack Group Kimsuky Has Been Conducting Phishing Attacks To Collect Key Information From Public Institutions Since 2013. The Main Feature Of The Attack Techniques Used By The Kimsuky Attack Group Are To Conceal Malicious Code In Phishing E-mails Disguised As Normal E-mails To Spread A Document File That Is Vulnerable To Security, Such As A Hangul File, Or To Induce Interest Through A Social Engineering Attack Technique To Collect Account Information. This Study Classified The Types Of Phishing E-mail Attacks Into Spoofed E-mails, E-mail Body Vulnerability Use, And Attached File Spoofing, And Detailed Analyses Of Their Attack Methods, Such As Commonality And Characteristic Analyses, Were Performed To Analyze The Profile Of This Phishing E-mail Attack Group. Based On The Results, The Purpose Of The Attacking Group Was Determined To Be Intelligence Gathering Because It Focused On Phishing Attacks Targeting Korean Diplomatic And Defense Public Institutions And Related Foreign Institutions. Finally, A Countermeasure That Can Be Used By Mail Service Providers And Mail Users To Respond To Phishing E-mails Is Suggested.

KEY DISTRIBUTION OVER OPTICAL BACKBONE NETWORKS- Hybrid Trusted - Untrusted Relay-Based Quantum Key Distribution Over Optical Backbone Networks

Domain: NETWORK SECURITY
Category: DOTNET
Year: 2022
Project Code: DNS2107

Quantum Key Distribution (QKD) Has Demonstrated A Great Potential To Provide Future-proofed Security, Especially For 5G And Beyond Communications. As The Critical Infrastructure For 5G And Beyond Communications, Optical Networks Can Offer A Cost-effective Solution To QKD Deployment Utilizing The Existing Fiber Resources. In Particular, Measurement-device-independent QKD Shows Its Ability To Extend The Secure Distance With The Aid Of An Untrusted Relay. Compared To The Trusted Relay, The Untrusted Relay Has Obviously Better Security, Since It Does Not Rely On Any Assumption On Measurement And Even Allows To Be Accessed By An Eavesdropper. However, It Cannot Extend QKD To An Arbitrary Distance Like The Trusted Relay, Such That It Is Expected To Be Combined With The Trusted Relay For Large-scale QKD Deployment. In This Work, We Study The Hybrid Trusted/untrusted Relay Based QKD Deployment Over Optical Backbone Networks And Focus On Cost Optimization During The Deployment Phase. A New Network Architecture Of Hybrid Trusted/untrusted Relay Based QKD Over Optical Backbone Networks Is Described, Where The Node Structures Of The Trusted Relay And Untrusted Relay Are Elaborated. The Corresponding Network, Cost, And Security Models Are Formulated. To Optimize The Deployment Cost, An Integer Linear Programming Model And A Heuristic Algorithm Are Designed. Numerical Simulations Verify That The Cost-optimized Design Can Significantly Outperform The Benchmark Algorithm In Terms Of Deployment Cost And Security Level. Up To 25% Cost Saving Can Be Achieved By Deploying QKD With The Hybrid Trusted/untrusted Relay Scheme While Keeping Much Higher Security Level Relative To The Conventional Point-to-point QKD Protocols That Are Only With The Trusted Relays.

ONLINE SOCIAL NETWORK DATA SHARING USING PATTER ANALYSIS- Disclose More And Risk Less - Privacy Preserving Online Social Network Data Sharing Using Pattern Analysis

Domain: NETWORK SECURITY
Category: DOTNET
Year: 2022
Project Code: DNS2108

Social Networks Pervaded Human Lives In Mostly Each Aspect. The Vast Amount Of Sensitive Data That Users Produce And Exchanged On These Platforms Call For Intensive Concern About Information And Privacy Protection. Moreover, The Users’ Statistical Usage Data Collected For Analysis Is Also Subject To Leakage And Therefor Require Protection. Although There Is An Availability Of Privacy Preserving Methods, They Are Not Scalable, Or Tend To Underperform When It Comes To Data Utility And Efficiency. Thus, In This Paper, We Develop A Novel Approach For Anonymizing Users’ Statistical Data. The Data Is Collected From The User’s Behavior Patterns In Social Networks. In Particular, We Collect Specific Points From The User’s Behavior Patterns Rather Than The Entire Data Stream To Be Fed Into Local Differential Privacy (LDP). After The Statistical Data Has Been Anonymized, We Reconstruct The Original Points Using Nonlinear Techniques. The Results From This Approach Provide Significant Accuracy When Compared With The Straightforward Anonymization Approach.

SECURE AND PRIVACY PRESERVING- Enforcing Secure And Privacy-Preserving Information Brokering In Distributed Information Sharing

Domain: NETWORK SECURITY
Category: DOTNET
Year: 2022
Project Code: DNS2110

Today's Organizations Raise An Increasing Need For Information Sharing Via On-demand Access. Information Brokering Systems (IBSs) Have Been Proposed To Connect Large-scale Loosely Federated Data Sources Via A Brokering Overlay, In Which The Brokers Make Routing Decisions To Direct Client Queries To The Requested Data Servers. Many Existing IBSs Assume That Brokers Are Trusted And Thus Only Adopt Server-side Access Control For Data Confidentiality. However, Privacy Of Data Location And Data Consumer Can Still Be Inferred From Metadata (such As Query And Access Control Rules) Exchanged Within The IBS, But Little Attention Has Been Put On Its Protection. In This Paper, We Propose A Novel Approach To Preserve Privacy Of Multiple Stakeholders Involved In The Information Brokering Process. We Are Among The First To Formally Define Two Privacy Attacks, Namely Attribute-correlation Attack And Inference Attack, And Propose Two Countermeasure Schemes Automaton Segmentation And Query Segment Encryption To Securely Share The Routing Decision-making Responsibility Among A Selected Set Of Brokering Servers. With Comprehensive Security Analysis And Experimental Results, We Show That Our Approach Seamlessly Integrates Security Enforcement With Query Routing To Provide System-wide Security With Insignificant Overhead.

COOPERATIVE QUERY ANSWER AUTHENTICATION - Cooperative Query Answer Authentication Scheme Over Anonymous Sensing Data

Domain: NETWORK SECURITY
Category: DOTNET
Year: 2022
Project Code: DNS2111

In Cloud Service Over Crowd-sensing Data, The Data Owner (DO) Publishes The Sensing Data Through The Cloud Server, So That The User Can Obtain The Information Of Interest On Demand. But The Cloud Service Providers (CSP) Are Often Untrustworthy. The Privacy And Security Concerns Emerge Over The Authenticity Of The Query Answer And The Leakage Of The DO Identity. To Solve These Issues, Many Researchers Study The Query Answer Authentication Scheme For Cloud Service System. The Traditional Technique Is Providing DO's Signature For The Published Data. But The Signature Would Always Reveal DO's Identity. To Deal With This Disadvantage, This Paper Proposes A Cooperative Query Answer Authentication Scheme, Based On The Ring Signature, The Merkle Hash Tree (MHT) And The Non-repudiable Service Protocol. Through The Cooperation Among The Entities In Cloud Service System, The Proposed Scheme Could Not Only Verify The Query Answer, But Also Protect The DO's Identity. First, It Picks Up The Internal Nodes Of MHT To Sign, As Well As The Root Node. Thus, The Verification Computation Complexity Could Be Significantly Reduced From O(log 2 N) To O(log 2 N 0.5 ) In The Best Case. Then, It Improves An Existing Ring Signature To Sign The Selected Nodes. Furthermore, The Proposed Scheme Employs The Non-repudiation Protocol During The Transmission Of Query Answer And Verification Object To Protect Trading Behavior Between The CSP And Users. The Security And Performance Analysis Prove The Security And Feasibility Of The Proposed Scheme. Extensive Experimental Results Demonstrate Its Superiority Of Verification Efficiency And Communication Overhead

MALWARE DETACTION- Search Rank Fraud And Malware Detection In Google Play

Domain: NETWORK SECURITY
Category: DOTNET
Year: 2022
Project Code: DNS2112

Fraudulent Behaviors In Google Play, The Most Popular Android App Market, Fuel Search Rank Abuse And Malware Proliferation. To Identify Malware, Previous Work Has Focused On App Executable And Permission Analysis. In This Paper, We Introduce FairPlay, A Novel System That Discovers And Leverages Traces Left Behind By Fraudsters, To Detect Both Malware And Apps Subjected To Search Rank Fraud. FairPlay Correlates Review Activities And Uniquely Combines Detected Review Relations With Linguistic And Behavioral Signals Gleaned From Google Play App Data (87 K Apps, 2.9 M Reviews, And 2.4M Reviewers, Collected Over Half A Year), In Order To Identify Suspicious Apps. FairPlay Achieves Over 95 Percent Accuracy In Classifying Gold Standard Datasets Of Malware, Fraudulent And Legitimate Apps. We Show That 75 Percent Of The Identified Malware Apps Engage In Search Rank Fraud. FairPlay Discovers Hundreds Of Fraudulent Apps That Currently Evade Google Bouncer's Detection Technology. FairPlay Also Helped The Discovery Of More Than 1,000 Reviews, Reported For 193 Apps, That Reveal A New Type Of “coercive” Review Campaign: Users Are Harassed Into Writing Positive Reviews, And Install And Review Other Apps.

MALICIOUS APPLICATION-Detecting Malicious Facebook Applications

Domain: NETWORK SECURITY
Category: DOTNET
Year: 2022
Project Code: DNS2113

With 20 Million Installs A Day , Third-party Apps Are A Major Reason For The Popularity And Addictiveness Of Facebook. Unfortunately, Hackers Have Realized The Potential Of Using Apps For Spreading Malware And Spam. The Problem Is Already Significant, As We Find That At Least 13% Of Apps In Our Dataset Are Malicious. So Far, The Research Community Has Focused On Detecting Malicious Posts And Campaigns. In This Paper, We Ask The Question: Given A Facebook Application, Can We Determine If It Is Malicious? Our Key Contribution Is In Developing FRAppE-Facebook's Rigorous Application Evaluator-arguably The First Tool Focused On Detecting Malicious Apps On Facebook. To Develop FRAppE, We Use Information Gathered By Observing The Posting Behavior Of 111K Facebook Apps Seen Across 2.2 Million Users On Facebook. First, We Identify A Set Of Features That Help Us Distinguish Malicious Apps From Benign Ones. For Example, We Find That Malicious Apps Often Share Names With Other Apps, And They Typically Request Fewer Permissions Than Benign Apps. Second, Leveraging These Distinguishing Features, We Show That FRAppE Can Detect Malicious Apps With 99.5% Accuracy, With No False Positives And A High True Positive Rate (95.9%). Finally, We Explore The Ecosystem Of Malicious Facebook Apps And Identify Mechanisms That These Apps Use To Propagate. Interestingly, We Find That Many Apps Collude And Support Each Other; In Our Dataset, We Find 1584 Apps Enabling The Viral Propagation Of 3723 Other Apps Through Their Posts. Long Term, We See FRAppE As A Step Toward Creating An Independent Watchdog For App Assessment And Ranking, So As To Warn Facebook Users Before Installing Apps

PRIVACY PRESERVING LOCATION BASED QUERY- EPLQ Efficient Privacy-Preserving Location -Based Query Over Outsourced Encrypted Data

Domain: NETWORK SECURITY
Category: DOTNET
Year: 2022
Project Code: DNS2114

Now A Day’s Malwares Are Becoming Increasingly Stealthy, More And More Malwares Are Using Cryptographic Algorithms To Protect Themselves From Being Analyzed. To Enable More Effective Malware Analysis, Forensics And Reverse Engineering, We Have Developed CipherXRay – A Novel Binary Analysis Framework That Can Automatically Identify And Recover The Cryptographic Operations And Transient Secrets From The Execution Of Potentially Obfuscated Binary Executables. Based On The Avalanche Effect Of Cryptographic Functions, CipherXRay Is Able To Accurately Pinpoint The Boundary Of Cryptographic Operation And Recover Truly Transient Cryptographic Secrets That Only Exist In Memory For One Instant In Between Multiple Nested Cryptographic Operations. In Existing Mechanism Not Fully Detect The Malwares. Our Proposed Method CipherXRay Can Further Identify Certain Operation Modes Of The Identified Block Cipher And Tell Whether The Identified Block Cipher Operation Is Encryption Or Decryption In Certain Cases.

CIPHERXRAY CRYPTOGRAPHIC OPERATIONS- Exposing Cryptographic Operations And Transient Secrets From Monitored Binary Execution

Domain: NETWORK SECURITY
Category: DOTNET
Year: 2022
Project Code: DNS2115

Malwares Are Becoming Increasingly Stealthy, More And More Malwares Are Using Cryptographic Algorithms (e.g., Packing, Encrypting C&C Communication) To Protect Themselves From Being Analyzed. The Use Of Cryptographic Algorithms And Truly Transient Cryptographic Secrets Inside The Malware Binary Imposes A Key Obstacle To Effective Malware Analysis And Defense. To Enable More Effective Malware Analysis, Forensics, And Reverse Engineering, We Have Developed CipherXRay - A Novel Binary Analysis Framework That Can Automatically Identify And Recover The Cryptographic Operations And Transient Secrets From The Execution Of Potentially Obfuscated Binary Executables. Based On The Avalanche Effect Of Cryptographic Functions, CipherXRay Is Able To Accurately Pinpoint The Boundary Of Cryptographic Operation And Recover Truly Transient Cryptographic Secrets That Only Exist In Memory For One Instant In Between Multiple Nested Cryptographic Operations. CipherXRay Can Further Identify Certain Operation Modes (e.g., ECB, CBC, CFB) Of The Identified Block Cipher And Tell Whether The Identified Block Cipher Operation Is Encryption Or Decryption In Certain Cases. We Have Empirically Validated CipherXRay With OpenSSL, Popular Password Safe KeePassX, The Ciphers Used By Malware Stuxnet, Kraken And Agobot, And A Number Of Third Party Softwares With Built-in Compression And Checksum. CipherXRay Is Able To Identify Various Cryptographic Operations And Recover Cryptographic Secrets That Exist In Memory For Only A Few Microseconds. Our Results Demonstrate That Current Software Implementations Of Cryptographic Algorithms Hardly Achieve Any Secrecy If Their Execution Can Be Monitored.

INTRUSION DETECTION-Network Intrusion Detection And Countermeasure Selection In Virtual Network Systems-NICE

Domain: NETWORK SECURITY
Category: DOTNET
Year: 2022
Project Code: DNS2116

Cloud Security Is One Of Most Important Issues That Has Attracted A Lot Of Research And Development Effort In Past Few Years. Particularly, Attackers Can Explore Vulnerabilities Of A Cloud System And Compromise Virtual Machines To Deploy Further Large-scale Distributed Denial-of-Service (DDoS). DDoS Attacks Usually Involve Early Stage Actions Such As Multi-step Exploitation, Low Frequency Vulnerability Scanning, And Compromising Identified Vulnerable Virtual Machines As Zombies, And Finally DDoS Attacks Through The Compromised Zombies. Within The Cloud System, Especially The Infrastructure-as-a-Service (IaaS) Clouds, The Detection Of Zombie Exploration Attacks Is Extremely Difficult. This Is Because Cloud Users May Install Vulnerable Applications On Their Virtual Machines. To Prevent Vulnerable Virtual Machines From Being Compromised In The Cloud, We Propose A Multi-phase Distributed Vulnerability Detection, Measurement, And Countermeasure Selection Mechanism Called NICE, Which Is Built On Attack Graph Based Analytical Models And Reconfigurable Virtual Network-based Countermeasures. The Proposed Framework Leverages OpenFlow Network Programming APIs To Build A Monitor And Control Plane Over Distributed Programmable Virtual Switches In Order To Significantly Improve Attack Detection And Mitigate Attack Consequences. The System And Security Evaluations Demonstrate The Efficiency And Effectiveness Of The Proposed Solution.

ROUTING PROTOCOL - EIGRP Routing Protocol In Wireless Ad Hoc Sensor Networks

Domain: NETWORK SECURITY
Category: DOTNET
Year: 2022
Project Code: DNS2117

Routing Protocol Is Taking A Vital Role In The Modern Internet Era. A Routing Protocol Determines How The Routers Communicate With Each Other To Forward The Packets By Taking The Optimal Path To Travel From A Source Node To A Destination Node. In This Paper We Have Explored Two Eminent Protocols Namely, Enhanced Interior Gateway Routing Protocol (EIGRP) And Open Shortest Path First (OSPF) Protocols. Evaluation Of These Routing Protocols Is Performed Based On The Quantitative Metrics Such As Convergence Time, Jitter, End-to- End Delay, Throughput And Packet Loss Through The Simulated Network Models. The Evaluation Results Show That EIGRP Routing Protocol Provides A Better Performance Than OSPF Routing Protocol For Real Time Applications. Through Network Simulations We Have Proved That EIGRP Is More CPU Intensive Than OSPF And Hence Uses A Lot Of System Power. Therefore EIGRP Is A Greener Routing Protocol And Provides For Greener Internetworking.

CLICK POINT- Secure Process Monitoring In Cooperative Bank Using Click Point

Domain: NETWORK SECURITY
Category: DOTNET
Year: 2022
Project Code: DNS2118

Every Customer Should Have Confidential Information. These Are Wants To Maintain In A Secure Manner. Online Banking System Can Be Considered As The One Of The Great Tool Supporting Many Customers As Well As Banks And Financial Institutions To Make May Bank Activities. Every Day Banks Need To Perform Many Activities Related To Users Which Needs Huge Infrastructure With More Staff Members Etc. But The Online Banking System Allows The Banks To Perform These Activities In A Simpler Way Without Involving The Employees For Example Consider Online Banking, Mobile Banking And ATM Banking. But Banking System Needs To Be More Secure And Reliable Because Each And Every Task Performed Is Related To Customer’s Money. Especially Authentication And Validation Of User Access Is The Major Task In The Banking Systems. Usable Security Has Unique Usability Challenges Because The Need For Security Often Means That Standard Human-computer-interaction Approaches Cannot Be Directly Applied. An Important Usability Goal For Authentication Systems Is To Support Users In Selecting Better Passwords. Users Often Create Memorable Passwords That Are Easy For Attackers To Guess, But Strong System-assigned Passwords Are Difficult For Users To Remember. So Researchers Of Modern Days Have Gone For Alternative Methods Wherein Graphical Pictures Are Used As Passwords. The Major Goal Of This Work Is To Reduce The Guessing Attacks As Well As Encouraging Users To Select More Random, And Difficult Passwords To Guess. Well Known Security Threats Like Brute Force Attacks And Dictionary Attacks Can Be Successfully Abolished Using This Method.

SYBIL DEFENDER - A Defense Mechanism For Sybil Attacks In Large Social Networks

Domain: NETWORK SECURITY
Category: DOTNET
Year: 2022
Project Code: DNS2119

Distributed Systems Without Trusted Identities Are Particularly Vulnerable To Sybil Attacks, Where An Adversary Creates Multiple Bogus Identities To Compromise The Running Of The System. This Paper Presents SybilDefender, A Sybil Defense Mechanism That Leverages The Network Topologies To Defend Against Sybil Attacks In Social Networks. Based On Performing A Limited Number Of Random Walks Within The Social Graphs, SybilDefender Is Efficient And Scalable To Large Social Networks. Our Experiments On Two 3,000,000 Node Real-world Social Topologies Show That SybilDefender Outperforms The State Of The Art By More Than 10 Times In Both Accuracy And Running Time. SybilDefender Can Effectively Identify The Sybil Nodes And Detect The Sybil Community Around A Sybil Node, Even When The Number Of Sybil Nodes Introduced By Each Attack Edge Is Close To The Theoretically Detectable Lower Bound. Besides, We Propose Two Approaches To Limiting The Number Of Attack Edges In Online Social Networks. The Survey Results Of Our Facebook Application Show That The Assumption Made By Previous Work That All The Relationships In Social Networks Are Trusted Does Not Apply To Online Social Networks, And It Is Feasible To Limit The Number Of Attack Edges In Online Social Networks By Relationship Rating.

PASSWORD AUTHENTICATED GROUP KEY AGREEMENT- Password-Authenticated Group Key Agreement With Adaptive Security And Contributiveness

Domain: NETWORK SECURITY
Category: DOTNET
Year: 2022
Project Code: DNS2120

Adaptively-secure Key Exchange Allows The Establishment Of Secure Channels Even In The Presence Of An Adversary That Can Corrupt Parties Adaptively And Obtain Their Internal States. In This Paper, We Give A Formal Definition Of Contributory Protocols And Define An Ideal Functionality For Password-based Group Key Exchange With Explicit Authentication And Contributiveness In The UC Framework. As With Previous Definitions In The Same Framework, Our Definitions Do Not Assume Any Particular Distribution On Passwords Or Independence Between Passwords Of Different Parties. We Also Provide The First Steps Toward Realizing This Functionality In The Above Strong Adaptive Setting By Analyzing An Efficient Existing Protocol And Showing That It Realizes The Ideal Functionality In The Random-oracle And Ideal-cipher Models Based On The CDH Assumption.

Online Password Guessing Attacks

Domain: NETWORK SECURITY
Category: DOTNET
Year: 2022
Project Code: DNS2121

Passwords Are The Most Commonly Used Means Of Authentication As Passwords Are Very Convenient For Users, Easier To Implement And User Friendly. Password Based Systems Suffer From Two Types Of Attacks: I) Offline Attacks Ii) Online Attacks. Eavesdropping The Communication Channel And Recording The Conversations Taking Place On The Communication Channel Is An Example For Offline Attack. Brute Force And Dictionary Attacks Are The Two Types Of Online Attacks Which Are Widespread And Increasing. Enabling Convenient Login For Legitimate Users While Preventing Such Attacks Is A Difficult Problem. The Proposed Protocol Called Password Guessing Resistant Protocol (PGRP), Helps In Preventing Such Attacks And Provides A Pleasant Login Experience For Legitimate Users. PGRP Limits The Number Of Login Attempts For Unknown Users To One, And Then Challenges The Unknown User With An Automated Turing Test (ATT). There Are Different Kinds Of ATT Tests Such As CAPTCHA (Completely Automated Public Turing Test To Tell Computers And Humans Apart), Security Questions Etc. In This System, A Distorted Textbased CAPTCHA Is Used. If The ATT Test Is Correctly Answered, The User Is Granted Access Else The User Is Denied Access. The Proposed Algorithm Analyzes The Efficiency Of PGRP Based On Three Conditions: I) Number Of Successful Login Attempts Ii) Number Of Failed Login Attempts With Invalid Password Iii) Number Of Failed Login Attempts With Invalid Password And ATT Test. PGRP Log Files Are Used As Data Sets. The Analysis Helps In Determining The Efficiency Of PGRP Protocol.

VEHICULAR COMMUNICATION- An Efficient Message Authentication Scheme For Vehicular Communication

Domain: NETWORK SECURITY
Category: DOTNET
Year: 2022
Project Code: DNS2122

In This Paper, We Introduce A Novel Roadside Unit (RSU)-aided Message Authentication Scheme Named RAISE, Which Makes RSUs Responsible For Verifying The Authenticity Of Messages Sent From Vehicles And For Notifying The Results Back To Vehicles. In Addition, RAISE Adopts The $k$- Anonymity Property For Preserving User Privacy, Where A Message Cannot Be Associated With A Common Vehicle. In The Case Of The Absence Of An RSU, We Further Propose A Supplementary Scheme, Where Vehicles Would Cooperatively Work To Probabilistically Verify Only A Small Percentage Of These Message Signatures Based On Their Own Computing Capacity. Extensive Simulations Are Conducted To Validate The Proposed Scheme. It Is Demonstrated That RAISE Yields A Much Better Performance Than Previously Reported Counterparts In Terms Of Message Loss Ratio (LR) And Delay.

DETECTION AND PREVENTION OF SYBIL ATTACK- Detection And Prevention Of Sybil Attack In MANET Using Mac Address

Domain: NETWORK SECURITY
Category: DOTNET
Year: 2022
Project Code: DNS2123

A Mobile Adhoc Network Is A Network That Does Not Relay On Fixed Infrastructure .It Is A Collection Of Independent Mobile Nodes That Can Communicate To Each Other Via Radio Waves. These Networks Are Fully Distributed, And Can Work At Any Place Without The Help Of Any Fixed Infrastructure As Access Points Or Base Stations. As In Ad- Hoc Network Communication Medium Is Air So It Would Be Easy For Attacker To Fetch Information From Air Medium Using Sniffing Software Tool. There Is An Attack Which Causes So Much Destruction To A Network Called Sybil Attack. In The Sybil Attack A Single Node Presents Multiple Fake Identities To Other Nodes In The Network. In This Research, We Implemented The Sybil Attack Detection Technique Which Is Used To Detect The Sybil Nodes In The Network And Also Prevent It. Simulation Tool Used For The Implementation Is NS2.35.

VOTING SYSTEM - Voting Systems With Trust Mechanisms In Cyberspace Vulnerabilities And Defenses

Domain: NETWORK SECURITY
Category: DOTNET
Year: 2022
Project Code: DNS2124

With The Popularity Of Voting Systems In Cyberspace, There Is Growing Evidence That Current Voting Systems Can Be Manipulated By Fake Votes. This Problem Has Attracted Many Researchers Working On Guarding Voting Systems In Two Areas: Relieving The Effect Of Dishonest Votes By Evaluating The Trust Of Voters, And Limiting The Resources That Can Be Used By Attackers, Such As The Number Of Voters And The Number Of Votes. In This Paper, We Argue That Powering Voting Systems With Trust And Limiting Attack Resources Are Not Enough. We Present A Novel Attack Named As Reputation Trap (RepTrap). Our Case Study And Experiments Show That This New Attack Needs Much Less Resources To Manipulate The Voting Systems And Has A Much Higher Success Rate Compared With Existing Attacks. We Further Identify The Reasons Behind This Attack And Propose Two Defense Schemes Accordingly. In The First Scheme, We Hide Correlation Knowledge From Attackers To Reduce Their Chance To Affect The Honest Voters. In The Second Scheme, We Introduce Robustness-of-evidence, A New Metric, In Trust Calculation To Reduce Their Effect On Honest Voters. We Conduct Extensive Experiments To Validate Our Approach. The Results Show That Our Defense Schemes Not Only Can Reduce The Success Rate Of Attacks But Also Significantly Increase The Amount Of Resources An Adversary Needs To Launch A Successful Attack.

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