Graphical Object-Oriented And Interne Programming docx.

Running head: GRAPHICAL OBJECT-ORIENTED AND INTERNET PROGRAMMING
GRAPHICAL OBJECT-ORIENTED AND INTERNET PROGRAMMING
Name of the Student
Name of the University
Author Note

1GRAPHICAL OBJECT-ORIENTED AND INTERNET PROGRAMMING
Table of Contents
Part A...............................................................................................................................................2
Part A, Question 1........................................................................................................................2
Part A, Question 2........................................................................................................................3
Part A, Question 3........................................................................................................................3
Part A, Question 4......................................................................................................................10
Part B: Query.................................................................................................................................12
Part C: Normalization....................................................................................................................19
Part C, Question 1......................................................................................................................19
Part C, Question 2......................................................................................................................19
Part C, Question 3......................................................................................................................20
Part D Entity Relationship Diagram..............................................................................................20
Part D, Question 1......................................................................................................................21
Part D, Question 2......................................................................................................................22
Part D, Question 3......................................................................................................................23
Part E: Brief Definitions................................................................................................................24
Part F: Database hacking...............................................................................................................25
Referencing....................................................................................................................................28

2GRAPHICAL OBJECT-ORIENTED AND INTERNET PROGRAMMING
Part A
Part A, Question 1
i. In terms of the Cardinality representation the downloaded ERD does not show any cardinality
between the tables. Whereas the ERD in subject guide uses (min, max) notation for showing the
cardinality between the tables.
ii. A strong entity has a primary key which is denoted by a Rectangle in ERD. On other hand, the
weak entities only have partial keys which is used to discriminate between tuples. It is denoted
by the double rectangle in ERD.
iii. Yes, the weak entities can be identified by the double rectangle used for the tables in the ER
diagram. Weak entities are the entities which do not have any key attribute or depend on the
other entities.
iv. The relationship between the Country and Religion is created in a way that the Country table
is the Parent table for the ‘country’ attribute in the Religion table. It is possible to enter any
country without even entering any religion record for that country. On other hand, a religion
record cannot be created for a country which has not be entered in the Country table as the
‘country’ in the Religion table is a foreign key referenced to the ‘code’ attribute in the Country
table (Powers 2019). Entering religion without inputting country will invoke the foreign key
constrain on Religion table.
v. In order to convert the Religion table into a strong entity type, key attributes have to be added
or created in the table. Currently there are no key attributes present in the table which can be
identified uniquely. The conversion can be done by adding a ReligionID attribute as primary key

3GRAPHICAL OBJECT-ORIENTED AND INTERNET PROGRAMMING
or creating the religion name as primary key. In both the cases, the values cannot be repeated in
the religion table. In this scenario, any value can be recorded into the Religion table without
having respective Country. As the religion table will become string entity, to maintain the
relationship with the Country table, the primary keys of both the tables must be added into
another table (Countryhasreligion) as foreign keys and composite primary keys (Schwichtenberg
2018).
Part A, Question 2
i. There are total 43 tables in the diagram.
ii. Total 33 table listed after running SHOW TABLES; command in Part A Question
3.
iii. The attributes are Country, dependent,independence ,wasdependent and government.
iv. The attributes are the Country, dependent,independence and government.
v. The conclusion can be drawn about the database documentation can have more
relations on a conceptual level and it can explain the structure of the database. The
dependencies, set of relations and schema can be very helpful in understanding the
database. However, the physical schema of the database can be little different from
the conceptual schema.
Part A, Question 3
Show Tables
MariaDB [mondial]> show tables;
+-------------------+
| Tables_in_mondial |
+-------------------+

4GRAPHICAL OBJECT-ORIENTED AND INTERNET PROGRAMMING
| borders |
| city |
| continent |
| country |
| desert |
| economy |
| encompasses |
| ethnicgroup |
| geo_desert |
| geo_estuary |
| geo_island |
| geo_lake |
| geo_mountain |
| geo_river |
| geo_sea |
| geo_source |
| island |
| islandin |
| ismember |
| lake |
| language |
| located |
| locatedon |
| mergeswith |
| mountain |
| mountainonisland |
| organization |
| politics |
| population |
| province |

5GRAPHICAL OBJECT-ORIENTED AND INTERNET PROGRAMMING
| religion |
| river |
| sea |
+-------------------+
33 rows in set (0.002 sec)
ECONOMY
MariaDB [mondial]> DESCRIBE economy;
+-------------+------------+------+-----+---------+-------+
| Field | Type | Null | Key | Default | Extra |
+-------------+------------+------+-----+---------+-------+
| Country | varchar(4) | NO | PRI | NULL | |
| GDP | float | YES | | NULL | |
| Agriculture | float | YES | | NULL | |
| Service | float | YES | | NULL | |
| Industry | float | YES | | NULL | |
| Inflation | float | YES | | NULL | |
+-------------+------------+------+-----+---------+-------+
6 rows in set (0.039 sec)
MariaDB [mondial]> select count(*) from economy;
+----------+
| count(*) |
+----------+
| 238 |
+----------+
1 row in set (0.001 sec)
MariaDB [mondial]> show index from economy;

6GRAPHICAL OBJECT-ORIENTED AND INTERNET PROGRAMMING
+---------+------------+----------+--------------+-------------+-----------+-------------+----------+--------
+------+------------+---------+---------------+
| Table | Non_unique | Key_name | Seq_in_index | Column_name | Collation | Cardinality |
Sub_part | Packed | Null | Index_type | Comment | Index_comment |
+---------+------------+----------+--------------+-------------+-----------+-------------+----------+--------
+------+------------+---------+---------------+
| economy | 0 | PRIMARY | 1 | Country | A | 214 | NULL | NULL |
| BTREE | | |
+---------+------------+----------+--------------+-------------+-----------+-------------+----------+--------
+------+------------+---------+---------------+
1 row in set (0.002 sec)
ISMEMBER
MariaDB [mondial]> describe ismember;
+--------------+-------------+------+-----+---------+-------+
| Field | Type | Null | Key | Default | Extra |
+--------------+-------------+------+-----+---------+-------+
| Country | varchar(4) | NO | PRI | NULL | |
| Organization | varchar(12) | NO | PRI | NULL | |
| Type | varchar(35) | YES | | member | |
+--------------+-------------+------+-----+---------+-------+
3 rows in set (0.046 sec)
MariaDB [mondial]> select count(*) from ismember;
+----------+
| count(*) |
+----------+
| 8008 |
+----------+
1 row in set (0.006 sec)
MariaDB [mondial]> show index from ismember;

7GRAPHICAL OBJECT-ORIENTED AND INTERNET PROGRAMMING
+----------+------------+----------+--------------+--------------+-----------+-------------+----------
+--------+------+------------+---------+---------------+
| Table | Non_unique | Key_name | Seq_in_index | Column_name | Collation | Cardinality |
Sub_part | Packed | Null | Index_type | Comment | Index_comment |
+----------+------------+----------+--------------+--------------+-----------+-------------+----------
+--------+------+------------+---------+---------------+
| ismember | 0 | PRIMARY | 1 | Country | A | 454 | NULL | NULL |
| BTREE | | |
| ismember | 0 | PRIMARY | 2 | Organization | A | 7732 | NULL | NULL
| | BTREE | | |
+----------+------------+----------+--------------+--------------+-----------+-------------+----------
+--------+------+------------+---------+---------------+
2 rows in set (0.002 sec)
LANGUAGE
MariaDB [mondial]> describe language;
+------------+-------------+------+-----+---------+-------+
| Field | Type | Null | Key | Default | Extra |
+------------+-------------+------+-----+---------+-------+
| Country | varchar(4) | NO | PRI | NULL | |
| Name | varchar(50) | NO | PRI | NULL | |
| Percentage | float | YES | | NULL | |
+------------+-------------+------+-----+---------+-------+
3 rows in set (0.035 sec)
MariaDB [mondial]> select count(*) from language;
+----------+
| count(*) |
+----------+
| 144 |
+----------+

8GRAPHICAL OBJECT-ORIENTED AND INTERNET PROGRAMMING
1 row in set (0.001 sec)
MariaDB [mondial]> show index from language;
+----------+------------+----------+--------------+-------------+-----------+-------------+----------+--------
+------+------------+---------+---------------+
| Table | Non_unique | Key_name | Seq_in_index | Column_name | Collation | Cardinality |
Sub_part | Packed | Null | Index_type | Comment | Index_comment |
+----------+------------+----------+--------------+-------------+-----------+-------------+----------+--------
+------+------------+---------+---------------+
| language | 0 | PRIMARY | 1 | Name | A | 144 | NULL | NULL |
| BTREE | | |
| language | 0 | PRIMARY | 2 | Country | A | 144 | NULL | NULL |
| BTREE | | |
+----------+------------+----------+--------------+-------------+-----------+-------------+----------+--------
+------+------------+---------+---------------+
2 rows in set (0.002 sec)
ORGANIZATION
MariaDB [mondial]> select count(*) from organization;
+----------+
| count(*) |
+----------+
| 153 |
+----------+
1 row in set (0.001 sec)
MariaDB [mondial]> show index from organization;
+--------------+------------+---------------+--------------+--------------+-----------+-------------+----------
+--------+------+------------+---------+---------------+
| Table | Non_unique | Key_name | Seq_in_index | Column_name | Collation |
Cardinality | Sub_part | Packed | Null | Index_type | Comment | Index_comment |
+--------------+------------+---------------+--------------+--------------+-----------+-------------+----------
+--------+------+------------+---------+---------------+

9GRAPHICAL OBJECT-ORIENTED AND INTERNET PROGRAMMING
| organization | 0 | PRIMARY | 1 | Abbreviation | A | 153 | NULL |
NULL | | BTREE | | |
| organization | 0 | OrgNameUnique | 1 | Name | A | 153 | NULL |
NULL | | BTREE | | |
+--------------+------------+---------------+--------------+--------------+-----------+-------------+----------
+--------+------+------------+---------+---------------+
2 rows in set (0.002 sec)
POPULATION
MariaDB [mondial]> describe population;
+-------------------+------------+------+-----+---------+-------+
| Field | Type | Null | Key | Default | Extra |
+-------------------+------------+------+-----+---------+-------+
| Country | varchar(4) | NO | PRI | NULL | |
| Population_Growth | float | YES | | NULL | |
| Infant_Mortality | float | YES | | NULL | |
+-------------------+------------+------+-----+---------+-------+
3 rows in set (0.042 sec)
MariaDB [mondial]> select count(*) from population;
+----------+
| count(*) |
+----------+
| 238 |
+----------+
1 row in set (0.001 sec)
MariaDB [mondial]> show index from population;
+------------+------------+----------+--------------+-------------+-----------+-------------+----------
+--------+------+------------+---------+---------------+

10GRAPHICAL OBJECT-ORIENTED AND INTERNET PROGRAMMING
| Table | Non_unique | Key_name | Seq_in_index | Column_name | Collation | Cardinality |
Sub_part | Packed | Null | Index_type | Comment | Index_comment |
+------------+------------+----------+--------------+-------------+-----------+-------------+----------
+--------+------+------------+---------+---------------+
| population | 0 | PRIMARY | 1 | Country | A | 238 | NULL | NULL |
| BTREE | | |
+------------+------------+----------+--------------+-------------+-----------+-------------+----------
+--------+------+------------+---------+---------------+
1 row in set (0.002 sec)
Part A, Question 4
i. The Size of the Mondial database is approximate 1.4 Megabytes.
MariaDB [mondial]> select table_schema as `Database`,
-> table_name AS `Table`,
-> round(((data_length + index_length) / 1024 / 1024), 2) `Size in MB`
-> FROM information_schema.TABLES
-> WHERE table_schema = 'mondial'
-> ORDER BY (data_length + index_length) DESC ;
+----------+------------------+------------+
| Database | Table | Size in MB |
+----------+------------------+------------+
| mondial | ismember | 0.44 |
| mondial | city | 0.27 |
| mondial | province | 0.19 |
| mondial | geo_sea | 0.08 |
| mondial | located | 0.08 |
| mondial | islandin | 0.05 |
| mondial | religion | 0.05 |
| mondial | geo_island | 0.05 |
| mondial | ethnicgroup | 0.05 |
| mondial | locatedon | 0.05 |

11GRAPHICAL OBJECT-ORIENTED AND INTERNET PROGRAMMING
| mondial | organization | 0.03 |
| mondial | country | 0.03 |
| mondial | borders | 0.02 |
| mondial | island | 0.02 |
| mondial | sea | 0.02 |
| mondial | geo_source | 0.02 |
| mondial | river | 0.02 |
| mondial | geo_river | 0.02 |
| mondial | geo_mountain | 0.02 |
| mondial | population | 0.02 |
| mondial | geo_lake | 0.02 |
| mondial | politics | 0.02 |
| mondial | geo_estuary | 0.02 |
| mondial | mountainonisland | 0.02 |
| mondial | geo_desert | 0.02 |
| mondial | mountain | 0.02 |
| mondial | mergeswith | 0.02 |
| mondial | encompasses | 0.02 |
| mondial | economy | 0.02 |
| mondial | desert | 0.02 |
| mondial | language | 0.02 |
| mondial | lake | 0.02 |
| mondial | continent | 0.02 |
+----------+------------------+------------+
33 rows in set (0.003 sec)
ii. The largest relation is ‘ismember’ of total 0.44 Megabytes and smallest are the, continent,
lake, language, desert, economy etc. of 0.02 Megabytes.

12GRAPHICAL OBJECT-ORIENTED AND INTERNET PROGRAMMING
iii. Yes the table ismember has the largest size and highest degree as largest cardinality between
ismember and country relation.
iv. No this is not the case, ismember table has the highest degree but it has the lowest number of
columns than the country relation.
v. Yes the first should be necessarily larger than second if first has highest columns and tuple
both. For example, geo-sea have both high column and tuple than sea relation in mondial
database.
Part B: Query
B(1) What is the query that will list the names of all countries that have a GDP less than 15,000
and an infant mortality greater than 6?
Query:
SELECT DISTINCT country.name
FROM country,
population,
economy
WHERE economy.country = country.code
AND country.code = population.country
AND economy.gdp > 15000
AND population.infant_mortality > 6
LIMIT 5;
Result:
+------------+
| Name |
+------------+
| Austria |

13GRAPHICAL OBJECT-ORIENTED AND INTERNET PROGRAMMING
| Belgium |
| Bangladesh |
| Bulgaria |
| Bolivia |
+------------+
5 rows in set (0.001 sec)
B(2) What is the query that will list the names of all cities that have populations greater than the
population of New York?
Query:
SELECT DISTINCT name
FROM city
WHERE population > (SELECT population
FROM city
WHERE name = 'New York')
LIMIT 5;
Result:
+-------------+
| name |
+-------------+
| Istanbul |
| Jakarta |
| Karachi |
| Mexico City |
| Moscow |
+-------------+
5 rows in set (0.002 sec)

14GRAPHICAL OBJECT-ORIENTED AND INTERNET PROGRAMMING
B(3) What is the query that will list the world’s lakes, and for each one, the total number of
countries where each is found?
Query:
SELECT DISTINCT lake,
Count(country)
FROM geo_lake
GROUP BY lake
LIMIT 5;
Result:
+--------------------+----------------+
| lake | Count(country) |
+--------------------+----------------+
| Ammersee | 1 |
| Arresoe | 1 |
| Atlin Lake | 2 |
| Balaton | 4 |
| Barrage de Mbakaou | 1 |
+--------------------+----------------+
5 rows in set (0.002 sec)
B(4) What is the query that will list the world’s rivers that pass through at least two countries,
and for each one, the total number of countries where it runs?
Query:
SELECT DISTINCT river,
Count(country)
FROM geo_river
GROUP BY river
HAVING Count(country) > 2

15GRAPHICAL OBJECT-ORIENTED AND INTERNET PROGRAMMING
LIMIT 5;
Result:
+---------+----------------+
| river | Count(country) |
+---------+----------------+
| Dalaelv | 4 |
| Dnjestr | 8 |
| Donau | 30 |
| Doubs | 3 |
| Douro | 7 |
+---------+----------------+
5 rows in set (0.002 sec)
B(5) What is the query that will list the names of all countries that are full members (not
observers or non-regional members) of the World Health Organization and have GDP’s greater
than 3,000,000?
Query:
SELECT DISTINCT country.name
FROM country,
ismember,
economy
WHERE country.code = economy.country
AND country.code = ismember.country
AND ismember.type = 'member'
AND economy.gdp > 3000000
LIMIT 5;
Result:

16GRAPHICAL OBJECT-ORIENTED AND INTERNET PROGRAMMING
+---------------+
| name |
+---------------+
| China |
| United States |
+---------------+
2 rows in set (0.002 sec)
B(6) What is the query that will list the names of all countries that are NOT members (or
observers or non-regional members) of the World Health Organization and have GDP’s greater
than 100,000?
Query:
SELECT DISTINCT country.name
FROM country,
ismember,
economy
WHERE country.code = economy.country
AND country.code = ismember.country
AND ismember.type != 'member'
AND economy.gdp > 100000
LIMIT 5;
Result:
+------------+
| name |
+------------+
| Austria |
| Australia |
| Belgium |

17GRAPHICAL OBJECT-ORIENTED AND INTERNET PROGRAMMING
| Bangladesh |
| Brazil |
+------------+
5 rows in set (0.002 sec)
B(7) What is the query that will list the total population for all countries (all countries'
populations added together)?
Query:
SELECT Sum(population)
FROM country
LIMIT 5;
Result:
+-----------------+
| Sum(population) |
+-----------------+
| 5774449258 |
+-----------------+
1 row in set (0.002 sec)
B(8) What is the query that will list the name of the country with the highest population density?
Query:
SELECT NAME,
( population / area ) AS Density
FROM country
WHERE ( population / area ) = (SELECT Max(population / area)
FROM country)
ORDER BY ( population / area ) DESC;
Result:

18GRAPHICAL OBJECT-ORIENTED AND INTERNET PROGRAMMING
+-------+------------+
| NAME | Density |
+-------+------------+
| Macau | 31052.3125 |
+-------+------------+
1 row in set (0.003 sec)
B(9) What is the query that will list the world’s languages, and for each one, the total number of
countries where each is represented?
Query:
SELECT DISTINCT name,
COUNT(country)
FROM language
GROUP BY name
LIMIT 5;
Result:
+----------------+----------------+
| name | Count(country) |
+----------------+----------------+
| Afghan Persian | 1 |
| Afrikaans | 1 |
| Albanian | 2 |
| Arabic | 3 |
| Armenian | 3 |
+----------------+----------------+
5 rows in set (0.001 sec)
B(10) What is the query that will list the world’s languages that are present in at least 5 countries
and for each one, the total number of countries where it is represented?

19GRAPHICAL OBJECT-ORIENTED AND INTERNET PROGRAMMING
Query:
SELECT DISTINCT name,
COUNT(country)
FROM language
GROUP BY name
HAVING COUNT(country)>5
LIMIT 5;
Result:
+---------+----------------+
| name | COUNT(country) |
+---------+----------------+
| English | 21 |
| French | 10 |
| Russian | 6 |
| Spanish | 8 |
+---------+----------------+
4 rows in set (0.001 sec)
Part C: Normalization
Part C, Question 1
i. Functional dependencies: A non-key attribute depends on the key attribute of the table is
known as Functional Dependency.
a. BANDNAME + DATE  BANDTOWN, AGENT, AGENT TOWN, VENUE.
ii. Partial Dependencies: Some attributes only depends on a part of the composite key.
a. BANDNAME  BANDTOWN
b. DATE  VENUE

20GRAPHICAL OBJECT-ORIENTED AND INTERNET PROGRAMMING
c. AGENT  AGENTTOWN
Transitive Functional Dependencies: where one attribute is determined by second and
second is determined by third.
a. BANDNAME+DATE  AGENT
b. AGENT does not  BANDNAME+DATE
c. AGENT  AGENTTOWN
Part C, Question 2
Insertion Anomaly: An inconsistency in data adding is present in the table when entering a
band name, the Date should be consistent with all rows.
Update Anomaly: In this Anomaly, if an Agent changes his/her town, then the all rows need to
be updated where the agent is repeatedly present in the table. Here, the existing information is
getting changed incorrectly (Schindler 2018).
Delete Anomaly: This anomaly results in loosing information in the current CONCERT
structure. Suppose if a record of The Discords concert on 03.07.2019 is deleted, the venue
details, agent and agent town will be lost with it.
Part C, Question 3
Current Relation
CONCERT (BANDNAME, BANDTOWN, AGENT, AGENTTOWN, DATE, VENUE)
Boyce-Codd Normal Form
BAND (BANDNAME, BANDTOWN)

21GRAPHICAL OBJECT-ORIENTED AND INTERNET PROGRAMMING
AGENT (AGENTNAME, AGENTTOWN)
CONCERT (AGENTNAME, BANDNAME, DATE, VENUE)
Part D Entity Relationship Diagram
Entity Relationship diagram represents the real world objects as entities, attributes and
relationship between them (Rossi 2014). It can be used in representing the conceptual, logical
and physical schema of the database.

22GRAPHICAL OBJECT-ORIENTED AND INTERNET PROGRAMMING
Part D, Question 1
Figure 1: Entity relationship diagram
Source: created by author

23GRAPHICAL OBJECT-ORIENTED AND INTERNET PROGRAMMING
Part D, Question 2
Figure 2: Normalized schema
Source: created by author

24GRAPHICAL OBJECT-ORIENTED AND INTERNET PROGRAMMING
Part D, Question 3
Figure 3: Normalized relational schema (up to 3nf)
Source: created by author

25GRAPHICAL OBJECT-ORIENTED AND INTERNET PROGRAMMING
Part E: Brief Definitions
i. Relation: In database a relation is referred to a table. It stores the relation between the
data as attribute and tuple.
ii. Tuple: A single row in the table in DBMS is called Tuple. It holds a single record for
a table.
iii. Intension: It provides the structure, constraints and name of the table and does not
depend on time.
iv. Extension: Extension is the count of the tuples available in a table at any instance
which depends on time.
v. Candidate Key: It is an attribute or set of attribute which can identify a row in a
table uniquely.
vi. Primary Key: It is similar to the Candidate key, however; candidate key can qualify
to identify uniquely and primary keys are set to identify tuples uniquely.
vii. Compound (or composite) Key: It is a combination of two or more than two
columns in a table to identify the records uniquely.
viii. NULL value: Null value is used to represent a vacant, missing or blank field in a
table. It simply means that the attribute has no value for any row.
ix. Functional dependency: It determines the relation between the attributes in a table.
For example, student name is functionally dependent on the roll no of the student
(Shora and Alam 2014). It mean that the student name is identified by the student’s
roll no which is a key attribute.
x. Determinant: It is basically an attribute and used to determine the assigned values to
the other attributes in a table.

26GRAPHICAL OBJECT-ORIENTED AND INTERNET PROGRAMMING
xi. Degree: It is the number of columns in a table and the cardinality of the relation in
the table.
xii. Cardinality: It determines the repetition and uniqueness of a column for a table to
another table in DBMS.
xiii. Transaction: It is a logical unit of process in database which makes changes in the
contents of the database. It uses the read and write operation in database.
xiv. Deadlock: Deadlock is a situation in database where two or more transaction
requires same resources and waits for each other to release the lock on the resource
(Khedkar et al. 2017).
xv. View: It is a subset in a database which can be generated by query and stored as a
permanent entity.
Part F: Database hacking
Database are the collection of the data which is kept in a structural and organized way. It
is consisting of the schema, tables and relations between them. Many organizations maintain
databases for their company, software and customers. The information contained in a database is
very sensitive in terms of accessing. The database engines accepts the request of query from an
authorized user to show the results in form of the information. Database security is an important
aspect of the security of the organizations’ information as well as the data integrity and
performance (Holt et al. 2015). The information stored in the database attracts the hackers. They
try to gain control over the database system to access or steal important data. Usually the
database is secured with different layers of security of web protection and encryption etc. The
hacker needs to go pass all the layers in order to get the access.

27GRAPHICAL OBJECT-ORIENTED AND INTERNET PROGRAMMING
Currently, there are several techniques of hacking a database which depends on the
security parameters of the database and loopholes in the whole system. The highly secure the
database will require highly complex hacking and effort form the hackers (Perevozchikov,
Shaymardanov and Chugunkov 2017). It can vary from simplest types of reaches to complex
events. The techniques used in hacking are discussed below
i. Password Cracking: Password cracking is can be obtained by brute force attack or
simply a guess. The password can depend on the users’ personality and it can be weak
in terms of complexity and number of characters. The weak passwords are usually
guessable and cracked using brute force attack.
ii. Software Vulnerabilities: A software product can have multiple loops holes in its
security which is continuously searched by the hackers. The more you get to know
about the software including its functionalities, it will become easier to find loopholes
and its vulnerabilities. Apart from that, a malware can be designed to exploit the
software.
iii. Packet Sniffing: Packet sniffing is type of hacking where a hacker keeps an eye over
a network where the traffic is being watched. The network traffic can contain several
information and data which is stored in the database (Awodele et al. 2015).
Specifically for the username and passwords the network is continuously watched.
iv. SQL Injection: It is a combination of web and database vulnerability and widely
known. The query statements are used in the attack in web forms. The forms are
usually filled by the user with the targeted information. Lastly the form sends the
bogus request to the database and then hacker can be able to dump all the database
with the help of select statement (Qian et al. 2015).

28GRAPHICAL OBJECT-ORIENTED AND INTERNET PROGRAMMING
To achieve high security in a database system certain practices can be standardize in the system
maintenance. The major thing can be done to protect the database is to use cryptographic
techniques to encrypt the entire database. The encryption should be an end to end. Next, the web
server and database server should be kept separately. Web application firewalls, blocking Third
party apps, using private network, and enabling operating system security can help in the security
of the database.

29GRAPHICAL OBJECT-ORIENTED AND INTERNET PROGRAMMING
Referencing
Awodele, O., Oluwabukola, O., Ogbonna, A.C. and Adebowale, A., 2015, June. Packet Sniffer–
A comparative characteristic evaluation study. In Proceedings of Informing Science & IT
Education Conference (InSITE) (pp. 91-100).
Holt, V., Ramage, M., Kear, K. and Heap, N., 2015. The usage of best practices and procedures
in the database community. Information Systems, 49, pp.163-181.
Khedkar, S., Thube, S., Estate, W.I. and Naka, C., 2017. Real time databases for
applications. International Research Journal of Engineering and Technology (IRJET), 4(06),
pp.2078-2082.
Perevozchikov, V.A., Shaymardanov, T.A. and Chugunkov, I.V., 2017, February. New
techniques of malware detection using FTP Honeypot systems. In 2017 IEEE Conference of
Russian Young Researchers in Electrical and Electronic Engineering (EIConRus) (pp. 204-207).
IEEE.
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