The Widespread Adoption Of QR Codes Has Revolutionized Various Industries, Streamlined Transactions And Improved Inventory Management. However, This Increased Reliance On QR Code Technology Also Exposes It To Potential Security Risks That Malicious Actors Can Exploit. QR Code Phishing, Or “Quishing”, Is A Type Of Phishing Attack That Leverages QR Codes To Deceive Individuals Into Visiting Malicious Websites Or Downloading Harmful Software. These Attacks Can Be Particularly Effective Due To The Growing Popularity And Trust In QR Codes. This Paper Examines The Importance Of Enhancing The Security Of QR Codes Through The Utilization Of Artificial Intelligence (AI). The Abstract Investigates The Integration Of AI Methods For Identifying And Mitigating Security Threats Associated With QR Code Usage. By Assessing The Current State Of QR Code Security And Evaluating The Effectiveness Of AI-driven Solutions, This Research Aims To Propose Comprehensive Strategies For Strengthening QR Code Technology’s Resilience. The Study Contributes To Discussions On Secure Data Encoding And Retrieval, Providing Valuable Insights Into The Evolving Synergy Between QR Codes And AI For The Advancement Of Secure Digital Communication.
Phishing Is An Internet Scam In Which An Attacker Sends Out Fake Messages That Look To Come From A Trusted Source. A URL Or File Will Be Included In The Mail, Which When Clicked Will Steal Personal Information Or Infect A Computer With A Virus. Traditionally, Phishing Attempts Were Carried Out Through Wide-scale Spam Campaigns That Targeted Broad Groups Of People Indiscriminately. The Goal Was To Get As Many People To Click On A Link Or Open An Infected File As Possible. There Are Various Approaches To Detect This Type Of Attack. One Of The Approaches Is Machine Learning. The URL’s Received By The User Will Be Given Input To The Machine Learning Model Then The Algorithm Will Process The Input And Display The Output Whether It Is Phishing Or Legitimate. There Are Various ML Algorithms Like SVM, Neural Networks, Random Forest, Decision Tree, XG Boost Etc. That Can Be Used To Classify These URLs. The Proposed Approach Deals With The Random Forest, Decision Tree Classifiers. The Proposed Approach Effectively Classified The Phishing And Legitimate URLs With An Accuracy Of 87.0% And 82.4% For Random Forest And Decision Tree Classifiers Respectively.
As Seen In The Past Few Decades, It Is Very Common To Observe The Patient’s Paper Work At The Hospital. Even Though The Same Personal Information Is Used, An Unusual Way To Actually Decrement The Amount Of These Paper Works Does Not Exist. The Development Of Mobile Web Provides Development Direction For Medical Industry And A New Service Mode. In This Paper, We Introduce QR Code Based E-health Authentication System To Obtain Patient’s Health Record Easily And Securely In The Local Hospital And Also To Reduce The Redundant Paper Work. One Of The Aims Of This Project Is To Use The Dataset And Machine Learning Techniques To Predict The Type Of Disease Based On The Symptoms. A QR Code Which Includes Predicted Disease And Personal Information Of Patient Is Sent To The Doctor Automatically Via Email. Further The Doctor Sends A QR Code Generated Prescription To The Patient Which Is Scanned By The Pharmacist .Here, We Describe An Integrated System, Developed For Use By The Healthcare Personnel Within Healthcare Facilities, Adapted To All Handheld Devices .With Our Proposed Scheme, We Believe That It Will Improve Efficiency In Terms Of The Cost And Time For The Patient, Hospital And The Doctor And Protect Patient’s Personal Information.
Text-based Password Authentication Is A Common Method Used To Verify The Identity Of Users Who Are Trying To Access A Secure System Or Service. In Order To Use This Authentication Method, The User Must Input A Password Or Other Secret Phrase That Is Then Compared To A Server-side Copy Of The Same Password. Access Is Given If The Password Typed Matches The One Saved. Graphical Password Authentication Is A Type Of User Authentication That Involves Using Images Or Visual Elements Instead Of Alphanumeric Characters To Verify The Identity Of The User. Unlike Traditional Text-based Passwords, Graphical Passwords Offer An Intuitive And User-friendly Way Of Authentication, As They Rely On The User's Ability To Remember Pictures, Shapes, And Patterns. This Technology Has Been Developed To Address The Limitations Of Traditional Text-based Passwords, Such As The Difficulty Of Creating And Remembering Complex Passwords, And The Vulnerability To Brute-force Attacks. Compared To Conventional Text-based Passwords, Graphical Password Authentication Has A Number Of Benefits, Including Better Usability And Higher Security.
Films Are A Significant Form Of Entertainment Form Of Entertainment In Modern Society, With Filmmakers Investing Substantial Resources Into Their Production. However, This Effort Is Undermined By Piracy, Where Individuals Copy And Distribute Film Content Illegally, Often By Recording Movies With Portable Often By Recording Movies With Portable Cameras And Uploading Them To Online Platforms. Camcorder Theft In Particular Has A Significant Impact On The Film Industry. Despite Efforts To Track Pirates, Watermarking In Pirated Movies Is Often Undetectable, Making It Difficult To Deter Piracy Effectively.To Address This Issue, This Paper Proposes Two Innovative Solutions. Firstly, It Suggests Embedding A Secret Key Using Steganography Via MATLAB To Secure Movies Files. Steganography Allows For The Concealment Of Information Within Digital Media, Providing A Covert Means Of Protection. Secondly, This Recommendation Involves Constructing A Screen Fitted With An Infrared Transmitter Which Would Prevent People From Filming Illegally In Cinemas. The Idea Behind This System Is That It Emits Infrared Signals At The Same Time As Films Are Being Shown Thereby Making Recording Impossible. Also GSM Technology Can Be Used To Send Quick SMS Alerts To Authorized Personal Whenever There Is An Attempt At Piracy For Immediate Response. On The Whole, These Measures Are Designed To Combat Theater Piracy By Making Movies More Secure Against Illegal Duplication While At The Same Time Preventing People From Recording Them Without Permission.
It Is Estimated That Globally 425 Million Subjects Have Moderate To Severe Obstructive Sleep Apnea (OSA). The Accurate Prediction Of Sleep Apnea Events Can Offer Insight Into The Development Of Treatment Therapies. However, Research Related To This Prediction Is Currently Limited. We Developed A Covert Framework For The Prediction Of Sleep Apnea Events Based On Low-frequency Breathing-induced Vibrations Obtained From Piezoelectric Sensors. A CNN-transformer Network Was Utilized To Efficiently Extract Local And Global Features From Respiratory Vibration Signals For Accurate Prediction. Our Study Involved Overnight Recordings Of 105 Subjects. In Five-fold Cross-validation, We Achieved An Accuracy Of 85.9% And An F1 Score Of 85.8%, Which Are 3.5% And 5.3% Higher Than The Best-performed Classical Model, Respectively. Additionally, In Leave-one-out Cross-validation, 2.3% And 3.8% Improvements Are Observed, Respectively. Our Proposed CNN-transformer Model Is Effective In The Prediction Of Sleep Apnea Events. Our Framework Can Thus Provide A New Perspective For Improving OSA Treatment Modes And Clinical Management.
As Quantum Computing Evolves From Theoretical Promise To Emerging Reality, The Urgency To Develop Quantum-resilient Data Protection Mechanisms Becomes Increasingly Paramount-particularly Within Critical Infrastructure Systems Dependent On Multi-cloud Architectures. This Study Explores The Design And Deployment Of Quantum-resilient Encryption Protocols Tailored To Secure Sensitive Data Flows Across Heterogeneous And Decentralized Cloud Environments Supporting Energy, Transportation, Defense, And Healthcare Infrastructures. Beginning From A Broader Analysis Of Cryptographic Vulnerabilities Posed By Quantum Adversaries-especially Those Exploiting Shor's And Grover's Algorithms-the Paper Highlights The Limitations Of Current Asymmetric Key Systems And Symmetric Encryption Practices In Multi-cloud Data Orchestration. Building On This Foundation, The Research Narrows In On Post-quantum Cryptographic (PQC) Frameworks, Including Lattice-based, Code-based, And Multivariate Polynomial Schemes, Evaluating Their Performance And Adaptability For Dynamic Cloud-native Systems. A Key Focus Is Placed On Designing Lightweight, Interoperable Encryption Protocols That Can Seamlessly Integrate With Federated Identity Management, Zero-trust Security Models, And Real-time Data Streams Without Introducing Prohibitive Latency Or Computational Burden. The Study Also Presents An Architectural Model That Allows For Real-time Key Negotiation, Distributed Trust Management, And Algorithm Agility, Ensuring Compliance With Both Current And Forward-looking Regulatory Standards (e.g., NIST PQC Guidelines). Simulation And Benchmarking Conducted Across Hybrid Cloud Environments Demonstrate That Carefully Optimized Quantum-resilient Protocols Can Be Implemented Without Compromising System Availability Or Scalability. The Results Validate The Feasibility Of Transitioning From Conventional Cryptography To Quantum-safe Models In Mission-critical Multi-cloud Operations. The Paper Concludes By Offering A Strategic Roadmap For Organizations Seeking To Future-proof Their Cloud Infrastructures Against Quantum-era Threats.
Nowadays, Distributed Data Processing In Cloud Computing Has Gained Increasing Attention From Many Researchers. The Intense Transfer Of Data Has Made The Network An Attractive And Vulnerable Target For Attackers To Exploit And Experiment With Different Types Of Attacks. Therefore, Many Intrusion Detection Techniques Have Been Evolving To Protect Cloud Distributed Services By Detecting The Different Attack Types On The Network. Machine Learning Techniques Have Been Heavily Applied In Intrusion Detection Systems With Different Algorithms. This Paper Surveys Recent Research Advances Linked To Machine Learning Techniques. We Review Some Representative Algorithms And Discuss Their Proprieties In Detail. We Compare Them In Terms Of Intrusion Accuracy And Detection Rate Using Different Data Sets.
Because Of The Fast Expansion Of Internet Users, Phishing Attacks Have Become A Significant Menace Where The Attacker Poses As A Trusted Entity In Order To Steal Sensitive Data, Causing Reputational Damage, Loss Of Money, Ransomware, Or Other Malware Infections. Intelligent Techniques Mainly Machine Learning (ML) And Deep Learning (D L) Are Increasingly Applied In The Field Of Cyber Security Due To Their Ability To Learn From Available Data In Order To Extract Useful Insight And Predict Future Events. The Effectiveness Of Applying Such Intelligent Approaches In Detecting Phishing Web Sites Is Investigated In This Paper. We Used Two Separate Datasets And Selected The Highest Correlated Features Which Comprised Of A Combination Of Content-based, URL Lexical-based, And Domain-based Features. A Set Of ML Models Were Then Applied, And A Comparative Performance Evaluation Was Conducted. Results Proved The Importance Of Features Selection In Improving The Models' Performance. Furthermore, The Results Also Aimed To Identify The Best Features That Influence The Model In Identifying Phishing Websites. For Classification Performance, Random Forest (RF) Algorithm Achieved The Highest Accuracy For Both Datasets.
Credit Card Fraud Detection Is Presently The Most Frequently Occurring Problem In The Present World. This Is Due To The Rise In Both Online Transactions And E-commerce Platforms. Credit Card Fraud Generally Happens When The Card Was Stolen For Any Of The Unauthorized Purposes Or Even When The Fraudster Uses The Credit Card Information For His Use. In The Present World, We Are Facing A Lot Of Credit Card Problems. To Detect The Fraudulent Activities The Credit Card Fraud Detection System Was Introduced. This Project Aims To Focus Mainly On Machine Learning Algorithms. The Algorithms Used Are Random Forest Algorithm And The ExtraTreesClassifier Algorithm. The Results Of The Two Algorithms Are Based On Accuracy, Precision, Recall, And F1-score. The ROC Curve Is Plotted Based On The Confusion Matrix. The Random Forest And The Extra-Trees Classifier Algorithms Are Compared And The Algorithm That Has The Greatest Accuracy, Extra-Trees Classifier Is Considered As The Best Algorithm That Is Used To Detect The Fraud.
The Security Of Any Public Key Cryptosystem Depends On The Private Key Thus, It Is Important That Only An Authorized Person Can Have Access To The Private Key. The Paper Presents A New Algorithm That Protects The Private Key Using The Transposition Cipher Technique. The Performance Of The Proposed Technique Is Evaluated By Applying It In The Random Forest Algorithm’s Generated Private Keys Using 512-bit, 1024-bit, And 2048-bit, Respectively. The Result Shows That The Technique Is Practical And Efficient In Securing Private Keys While In Storage As It Produced High Avalanche Effect. Key Generator Is Part Of The Stream Cipher System That Is Responsible For Generating A Long Random Sequence Of Binary Bits Key That Used In Ciphering And Deciphering Processes In Everyday Life, Image Security Is Important These Days As Data Is Increasing A Lot. These Data Can Be Images, Videos, Text, Audio, Etc. So To Protect These Images From Attackers Who Can Destroy The Image Quality Or Modify The Images, Some Technologies Like AES, DES, RSA, Etc. Have Been Invented. With The Generation, Data Security Has Also Become An Essential Issue. Considering These Issues, The Proposed Technique Ensures Confidentiality, Integrity, And Authentication. Using These Techniques, The Host Can Encrypt And Decrypt The Image ,text ,video ,audio. The Digital Technology Was Completely Different From Today And The Scale Of Challenges Was Smaller, So With Recent Advanced Technology And The Emergence Of New Applications Such As Big Data Applications, In Addition To Applications Running With 64-bit And Many Other Applications Have Become Necessary To Design A New Current Algorithm For Current Requirements. Advanced Encryption Algorithm (AES) Is A Symmetric Algorithm, Which We Will Further And In Addition To New Recommendations For Future Work, A List Of Shortcomings And Vulnerabilities Of The Internal Structure Of The AES Algorithm Will Be Diagnosed.
For Secure Data Transmission Over Internet, It Is Important To Transfer Data In High Security And High Confidentiality, Information Security Is The Most Important Issue Of Data Communication In Networks And Internet. Either Image Or Video To Secure Transferred Information From Intruders, It Is Important To Convert The Information Into Cryptic Format The Image And Video Work On The Same Process. Different Methods Used To Ensure Data Security And Confidentiality During Transmission Like Steganography And Cryptography. This Paper We Convert Plaintext To Cipher Text For Doing So We Have Used RC6 Encryption Algorithm The Proposed Algorithm Ensure The Encryption And Decryption Using RC6 Stream Cipher And RGB Pixel Shuffling With Steganography By Using Hash-least Significant Bit (HLSB) That Make Use Of Hash Function To Developed Significant Way To Insert Data Bits In LSB Bits Of RGB Pixels Of Cover Image. The Security Evaluations For The Steganography Part We Will Be Using Modified LSB Algorithm Where We Overwrite The LSB Bits Of The Selected Frame (given By The User) From The Cover Video, With The Bit Of Text Message Character With Help Of Secret Key And Using KSA And PRGA.
Student Attendance System Is Used To Measure Student Participation In A Classroom. Before Pandemic Attendance Was Taken Manually Like In Sheets Or Registers. But When The Pandemic Hit, Everything Was Online, So Even The Classes. The Attendance Count Is A Very Important Problem That The Administrator Needs To Be More Careful About Taking During The Online Classes As There Are Many Chances Of A Proxy Happening. So, We Came Up With This Proposed System “Student Attendance Using QR Code” This Paper Proposes An Attendance System That Is Based On The QR Code-based Attendance System. The Students Need To Scan The QR In The Class According To The Professor Instruction. The Paper Explains The High Level Implementation Details Of The Proposed System. It Also Discusses How The System Verifies Student Identity To Eliminate False Registrations.
Nowadays, Dependency On Banking In The Virtual World Has Been Increased To The Peak Position. To Make It Consistent Advanced Technologies Should Be Used. As OTP Is Currently Used Worldwide For Security Purposes, It Can Be Overruled By QR Code. Main Advantage Of QR Code Over OTP Data Storage. OTP Can Only Confirm That The User Is Authorised User And Not Some Third Party Is Involved In This Transaction While QR Code Not Only Confirms The Authorised User But QR Code Itself Can Store Information Such As Transaction Id, Transaction Date, Time And Also Amount Of Transaction. So, There Is No Need Of Explicitly Keeping Track Of Transaction Every Transaction. Aim Of This Paper To Enhance The Functionality Of ATM Machine Using Android Application. Proposed System Is Combining The ATM And Mobile Banking And Minimizes The Time Of Withdrawing Cash From ATM. This Will Increase The Speed Of Transaction Almost Three Times Fast; Could Have Excellent Impact On Customer's Satisfaction. With The Help Of QR Code Information Get Encrypted So It Also Increases Security. As The Population Increasing ATM Queues Will Be Longer Day By Day. By Implementing Proposed System Current System Will Not Hampered, By Doing Some Minor Changes In Existing System It Will Be Possible To Get Cash Within Seconds. According To Analyst Report, Cost Of Transaction Using Mobile Application Is Almost Ten Times Less Than ATM And About Fifty Times Less, If Physical Bank Branch Used.
In Order To Prevent Health Risks And Provide A Better Service To The Patients That Have Visited The Hospital, There Is A Need For Monitoring The Patients After Being Released And Providing The Data Submitted By The Patient E-Health Enablers To The Medical Personnel. This Article Proposes Architecture For Providing The Secure Exchange Of Data Between The Patient And The Hospital Infrastructure. The Implemented Solution Is Validated On A Laboratory Tested. When It Comes To Exchanging Health Data Between Departments Or Across Institutions, There Are So Many Variables At Play That Additional Rules And Descriptions Are Absolutely Necessary. There Can’t Be Any Ambiguity When Transferring And Interpreting Information About The Patient's Allergies Or The Procedures, Materials, And Medications Required.
Nowadays, Quick Response (QR) Codes Seem To Be Present Everywhere. They Can Be Found On Advertisements In Magazines, Websites, Product Packaging, And Other Places. Since Mobile Phones Have Become A Basic Necessity For Everyone, Using QR Codes Is One Of The Most Fascinating Ways To Link Patients To The Internet Digitally. QR Codes Consist Of Black Squares Arranged In A Grid (matrix) On A White Background And Are Read By Specialized Software That Is Able To Extract Data From The Patterns That Are Present In The Matrix. Now Days It Is Used Widely In Many Organizations. In This Project, We Proposed QR Code-based For Hospital Management System. The Emergence Of QR Has Opened A Vast Variety Of Possibilities In The Technology Sector Which Made Accessing, Retrieving And Viewing Information And Data From Anywhere With Great Speed And Low Fault. It Is A Captivating Way Of Accessing Anything From A Website. Nowadays Due To The Ample Use Of Mobile Devices, Using QR Code Technology We Can Easily Establish Connections And Communicate With People And Share Information. It Is Also A Secure Way To Share Or Secure The Data Because Without The Correct Tool Retrieving Of Data For Someone Else Who Is Not Intended To View Is Impossible. Introducing QR Code Will Increase This Security One More Level Further. In This Paper, This Is A Patient Management App That Uses Both Quick Response (QR) Code Technology Hospital And Accesses Those Data In A Secure And Fast Manner. It Also Can Be Used By Patients To Recollect The Doctor Consultation Data And Retrieving Their Medical Records And Doctor-prescribed Medicines.
Graphical Password Is One Of Technic For Authentication Of Computer Security. The Most Crucial Aspect Of Computer Science Nowadays Is Digital/computer Security, Which Protects User Or Customer Data. And One Of The Hazards Is Shoulder-surfing, In Which A Criminal Can Acquire A Password By Watching Directly Or By Recording The Authentication Session. There Are A Number Of Methods For This Authentication, But The Most Popular And Straightforward Is The Graphic Password Method. A Bank Is Essential To People's Daily Lives. The Bank's Top Priority Is The Security Of Its Customers. To Safeguard User Accounts, The Authentication Process Must Be Secure. Textual Passwords Are A Frequently Used Method. The System Uses The Graphical Password To Demonstrate The Banking Website's Security In Order To Offer A Possible Substitute For The Traditional Alphanumeric Password Techniques To Prevent Shoulder Surfing Techniques.
The Security Of Any Public Key Cryptosystem Depends On The Private Key Thus, It Is Important That Only An Authorized Person Can Have Access To The Private Key. The Paper Presents A New Algorithm That Protects The Private Key Using The Transposition Cipher Technique. The Performance Of The Proposed Technique Is Evaluated By Applying It In The Random Forest Algorithm’s Generated Private Keys Using 512-bit, 1024-bit, And 2048-bit, Respectively. The Result Shows That The Technique Is Practical And Efficient In Securing Private Keys While In Storage As It Produced High Avalanche Effect.
With The Evolution In Wireless Communication, There Are Many Security Threats Over The Internet. The Intrusion Detection System (IDS) Helps To Find The Attacks On The System And The Intruders Are Detected. Previously Various Machine Learning (ML) Techniques Are Applied On The IDS And Tried To Improve The Results On The Detection Of Intruders And To Increase The Accuracy Of The IDS. This Paper Has Proposed An Approach To Develop Efficient IDS By Using The Principal Component Analysis (PCA) And The Random Forest Classification Algorithm. Where The PCA Will Help To Organise The Dataset By Reducing The Dimensionality Of The Dataset And The Random Forest Will Help In Classification. Results Obtained States That The Proposed Approach Works More Efficiently In Terms Of Accuracy As Compared To Other Techniques Like SVM, Naive Bayes, And Decision Tree. The Results Obtained By Proposed Method Are Having The Values For Performance Time (min) Is 3.24 Minutes, Accuracy Rate (%) Is 96.78 %, And The Error Rate (%) Is 0.21 %.
The Phenomenon Of Fake News Is Experiencing A Rapid And Growing Progress With The Evolution Of The Means Of Communication And Social Media. Fake News Detection Is An Emerging Research Area Which Is Gaining Big Interest. It Faces However Some Challenges Due To The Limited Resources Such As Datasets And Processing And Analyzing Techniques. In This Work, We Propose A System For Fake News Detection That Uses Machine Learning Techniques. We Used Term Frequency Inverse Document Frequency Of Bag Of Words And N-grams As Feature Extraction Technique, And Naïve Bayes As A Classifier. We Propose Also A Dataset Of Fake And True News To Train The Proposed System. Obtained Results Show The Efficiency Of The System
With Daily Installs, Third-party Apps Can Be A Important Cause For The Popularity And Attractiveness Of Facebook Or Any Online Social Media. Sadly, Cyber Criminals Get Came To The Realization That The Capability Of Using Apps For Spreading Spam And Malware. We Realize That At The Least 13% Of Facebook Apps In The Dataset Are Usually Malevolent. However With Their Findings , Several Issues Like Faux Profiles, Malicious Application Have Conjointly Full-grown. There Aren't Any Possible Method Exist To Regulate These Issues. During This Project, We Tend To Came Up With A Framework With That Automatic Detection Of Malicious Applications Is Feasible And Is Efficient. Suppose There's Facebook Application, Will The Facebook User Verify That The App Is Malicious Or Not. First We Identify A Set Of Features That Help Us To Analyze Malicious From Benign Ones. Second, Leveraging These Distinguishing Features ,where We Show That Post Of Application As Malicious With 95.9% Accuracy. Finally, We Explore The Ecosystems Of Malicious Facebook Apps And Identify Mechanisms That These Apps Use To Spread.
In Order To Prevent Health Risks And Provide A Better Service To The Patients That Have Visited The Hospital, There Is A Need For Monitoring The Patients After Being Released And Providing The Data Submitted By The Patient EHealth Enablers To The Medical Personnel. This Article Proposes Architecture For Providing The Secure Exchange Of Data Between The Patient Mobile Application And The Hospital Infrastructure. The Implemented Solution Is Validated On A Laboratory Testbed.
Real-time Communication (RTC) Is A New Standard And Industry-wide Effort That Expand The Web Browsing Model, Allowing Access To Information In Areas Like Social Media, Chat, Video Conferencing, And Television Over The Internet, And Unified Communication. These Systems Users Can View, Record, Remark, Or Edit Video And Audio Content Flows Using Time-critical Cloud Infrastructures That Enforce The Quality Of Services. However, There Are Many Proprietary Protocols And Codecs Available That Are Not Easily Interoperable And Scalable To Implement Multipoint Videoconference Systems. WebRTC (Web Real-Time Communication) Is A State-of-the-Art Open Technology That Makes Real-time Communication Capabilities In Audio, Video, And Data Transmission Possible In Real-time Communication Through Web Browsers Using JavaScript APIs (Application Programming Interfaces) Without Plug-ins. This Paper Aims To Introduce The P2P Video Conferencing System Based On Web Real-Time Communication (WebRTC). In This Paper, We Have Proposed A Web-based Peer-to-peer Real-time Communication System Using The Mozilla Firefox Together With The ScaleDrone Service That Enables Users To Communicate With Highspeed Data Transmission Over The Communication Channel Using WebRTC Technology, HTML5 And Use Node.js Server Address. Our Experiments Show That WebRTC Is A Capable Building Block For Scalable Live Video Conferencing Within A Web Browser.
Recent Developments In The Speed Of The Internet And Information Technology Have Made The Rapid Exchange Of Multimedia Information Possible. However, These Developments In Technology Lead To Violations Of Information Security And Private Information. Digital Steganography Provides The Ability To Protect Private Information That Has Become Essential In The Current Internet Age. Among All Digital Media, Digital Video Has Become Of Interest To Many Researchers Due To Its High Capacity For Hiding Sensitive Data. Numerous Video Steganography Methods Have Recently Been Proposed To Prevent Secret Data From Being Stolen. Nevertheless, These Methods Have Multiple Issues Related To Visual Imperceptibly, Robustness, And Embedding Capacity. To Tackle These Issues, This Paper Proposes A New Approach To Video Steganography Based On The Corner Point Principle And LSBs Algorithm. The Proposed Method First Uses Shi-Tomasi Algorithm To Detect Regions Of Corner Points Within The Cover Video Frames. Then, It Uses 4-LSBs Algorithm To Hide Confidential Data Inside The Identified Corner Points. Besides, Before The Embedding Process, The Proposed Method Encrypts Confidential Data Using Arnold’s Cat Map Method To Boost The Security Level.
The Security Of Any Public Key Cryptosystem Depends On The Private Key Thus, It Is Important That Only An Authorized Person Can Have Access To The Private Key. The Paper Presents A New Algorithm That Protects The Private Key Using The Transposition Cipher Technique. The Performance Of The Proposed Technique Is Evaluated By Applying It In The RSA Algorithm’s Generated Private Keys Using 512-bit, 1024-bit, And 2048-bit, Respectively. The Result Shows That The Technique Is Practical And Efficient In Securing Private Keys While In Storage As It Produced High Avalanche Effect.
Initially The Barcodes Have Been Widely Used For The Unique Identification Of The Products. Quick Response I.e. QR Codes Are 2D Representation Of Barcodes That Can Embed Text, Audio, Video, Web URL, Phone Contacts, Credentials ¬¬and Much More. This Paper Primarily Deals With The Generation Of QR Codes For Question Paper. We Have Proposed Encryption Of Question Paper Data Using AES Encryption Algorithm. The Working Of The QR Codes Is Based On Encrypting It To QR Code And Scanning To Decrypt It. Furthermore, We Have Reduced The Memory Storage By Redirecting To A Webpage Through The Transmission And Online Acceptance Of Data.
Communication Technology Has Completely Occupied All The Areas Of Applications. Last Decade Has However Witnessed A Drastic Evolution In Information And Communication Technology Due To The Introduction Of Social Media Network. Business Growth Is Further Achieved Via These Social Media. Nevertheless, Increase In The Usage Of Online Social Networks (OSN) Such As Face Book, Twitter, Instagrametc Has However Led To The Increase In Privacy And Security Concerns. Third Party Applications Are One Of The Many Reasons For Facebook Attractiveness. Regrettably, The Users Are Unaware Of Detail That A Lot Of Malicious Facebook Applications Provide On Their Profile. The Popularity Of These Third Party Applications Is Such That There Are Almost 20 Million Installations Per Day. But Cyber Criminals Have Appreciated The Popularity Of Third Party Applications And The Possibility Of Using These Apps For Distributing The Malware And Spam. This Paper Proposes A Method To Categorize A Given Application As Malicious Or Safe By Using FRAppE (Facebook’s Rigorous Application Evaluator), Possibly One Of The First Tool For Detecting Malicious Apps On The Facebook. To Develop The FRAppE, The Data Is Gathered From MyPagekeeper Application, A Website That Provides Significant Information About Various Third Party Applications And Their Insight Into Their Behavior.
We do code in matlab for all domains, Image Processing, Simulink Design and Power Electronics.
Our Complete portfolio describes how stuff we are watch our demo @ Youtube Link.
2025 © All Rights Reserved. Site Map